Working Papers

Working Papers The Future of Key
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Research Actors in the
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Table of content
1. Civil Society..
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9
Henning Banthien, IFOK GmbH (in cooperation with Dr. Jörg Mayer-Ries and Indre Zetzsche, IFOK GmbH)
1. Definitions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.1 Knowledge and knowledge production. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.2 Civil society.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2. C
ivil society and knowledge production – sketches of the current landscape.. . . . . . . . . . . . . . . . . . . . . . . . . . . 13
3. R
ecent key trends in civil society dynamics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.1 IT society. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.2 Open and transparent decision-making.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.3 Inclusive knowledge production. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.4 Emerging knowledge business. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.5 Outsourcing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.6 Applied research dominates.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.7 Ageing and shrinking societies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.8 Globalisation.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
4. D
riving forces for change and future trends. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
4.1 Global knowledge economy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
4.2 S
ocial cohesion and individual identity in the knowledge society. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
4.3 New governance mix. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
5. Scenarios.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
5.1 Scenario I: Citizens for Innovation or The Role of Civil Society in an Economically-Governed Europe. . . . . . . . . . . . . . . . . . . . 20
5.2 S
cenario II: The Knowledge Stock Exchange – Europe’s Civil Society Melts into the Market. . . . . . . . . . . . . . . . . . . . . . . . . 22
5.3 S
cenario III: Politically-powerful civil society. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
6. I mpact analysis of scenarios on ERA and the European Knowledge Society.. . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
7. Bibliography.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2. Researchers (Part 1)..
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
Andrea Bonaccorsi, University of Pisa
1. Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2. P
reparing for the future: the international mobility of undergraduate students. .
3. The competition for talent: doctoral education – a global perspective.. . . . . . . .
4. The ageing of researchers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5. A
radical interpretation and a proposal. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6. A
proposal for a pan-European market for PhDs and post-doc positions. . . . . . .
7. Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3. Researchers (Part 2).
. . . . . . . . . . . . . . . . . . . . . . . . 37
. . . . . . . . . . . . . . . . . . . . . . . . 37
. . . . . . . . . . . . . . . . . . . . . . . . 39
. . . . . . . . . . . . . . . . . . . . . . . . 41
. . . . . . . . . . . . . . . . . . . . . . . . 42
. . . . . . . . . . . . . . . . . . . . . . . . 45
. . . . . . . . . . . . . . . . . . . . . . . . 46
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
Andrea Bonaccorsi, University of Pisa
1. The role of actors in the knowledge production and research system: some methodological remarks..
2. Recent key trends. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3. D
riving forces for change and future trends. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1 Production of new knowledge..
3.2 Circulation of valid knowledge.
3.3 Legitimation. . . . . . . . . . . .
3.4 Selection. . . . . . . . . . . . . .
3.5 Funding. . . . . . . . . . . . . . .
3.6 Accountability. . . . . . . . . . .
3.7 Relevance.. . . . . . . . . . . . .
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4. I mpact analysis of scenarios on the ERA and the European knowledge society.
4. SMEs..
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54
54
57
58
59
63
66
67
68
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
Bart Clarysse, Ghent University and Vlerick Leuven Gent Management School
1. Introduction .. . . . . . . . .
2. D
ifferent types of SMEs..
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
. . . . . . . . . . .
2.1 SMEs in Traditional Sectors. . . . . . . . . . . .
2.2 I ndependent New Technology Based Firms.. .
2.3 Corporate Spin-offs. . . . . . . . . . . . . . . . .
2.4 Academic Spin-offs .. . . . . . . . . . . . . . . .
2.5 Venture Capital Backed Firms.. . . . . . . . . .
3. C
hanges in the Innovation System.
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. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1 The Increased Mobility of Researchers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2 The Evolution of the Risk Capital Market .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3 The Increased Professionalisation of the Market for New Ideas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
72
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75
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77
78
79
5
4. C
hallenges for the different groups of SMEs . .
4.1 Traditional SMEs.. . . . . . . . . . . . . . . . .
4.2 I ndependent New Technology Based Firms..
4.3 Corporate Spin-offs. . . . . . . . . . . . . . . .
4.4 Academic Spin-offs. . . . . . . . . . . . . . . .
4.5 Venture Capital Backed Start-ups. . . . . . .
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. 80
. 80
. 80
. . 81
. . 81
. . 82
5. S
cenarios on the relative importance of the different types of SMEs in knowledge production and diffusion.. . . . . 82
5.1 Scenario 1: 2020 – Academic spin-offs: from hype to reality. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
5.2 S
cenario 2: 2020 – An increasing focus on business model innovation as a source of competitive advantage. . . . . . . . . . . . . . 83
5.3 S
cenario 3: 2020 – The demise of locally embedded generation SMEs?. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
6. Bibliography. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
5. Universities..
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
Attila Havas, Institute of Economics, Hungarian Academy of Sciences, Budapest
1. Introduction. . . . . . . . . . . . . . . . . . . . . . . . . .
2. The role of universities in the research system..
3. Recent key trends. . . . . . . . . . . . . . . . . . . . . .
4. D
riving forces for change and future trends. . . .
5. Visions (future states) for universities.. . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
88
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
5.1 Visions for HE/R derived from the perspective of the EU and ERIA.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
5.2 Visions from the perspective of universities. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
6. I mpact analysis of scenarios on the ERIA.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
7. Bibliography.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
6. Universities – Statistical Annex. .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7. The future of RTOs: a few likely scenarios.
111
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
Jos Leijten, Head of Innovation Policy group, TNO
6
1. Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
1.1 What are RTOs?.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
1.2 The origin of RTOs (some examples).. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
1.3 A short RTO history. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
2. ( Re-)shaping RTO roles in progress.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
2.1 Open innovation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
2.2 Globalisation.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
2.3 C
hanging location of the public interest. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
2.4 The fear factor. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
2.5 Growing managerial freedom. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
2.6 Fading boundaries: technology convergence. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
2.7 F ading boundaries: fundamental and applied research. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
2.8 Fading boundaries: users and producers.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
2.9 Fading boundaries: science, technology and socio-economic analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
2.10 Fading boundaries: institutional convergence. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
2.11 I nstitutional forces: the RTO perspective.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
3. Future outlook. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
3.1 Drivers for change summarised.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
3.2 Uncertainties.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
4. Scenarios.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
4.1 Words come true: strong RTOs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
4.2 D
inosaurs lose: the dissolution of RTOs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132
4.3 N
etworks of networks for innovation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
5. S
cenario evaluation: policies and RTO strategies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
5.1 The policy perspective on the scenarios.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
5.2 The scenarios and RTO strategy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
6. Bibliography. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
7. Curriculum Vitae. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
8. Multinational Enterprises.
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
Guido Reger, University of Potsdam
Executive Summary.
1. Introduction. . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
1.1 Objectives. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
1.2 Approach. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
2. The Role of Multinational Enterprises in the Knowledge Production and Research System. . . . . . . . . . . . . . . . . 142
2.1 Defining the Main Terms. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142
2.2 Q
uantitative Importance of MNEs for Knowledge Production.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
2.3 Q
ualitative Importance of MNEs for Knowledge Production and the Relationship with New Technology-based Firms. . . . . . . . 144
3. Recent Key Trends.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
3.1 Main Changes in the Management of Technology and R&D. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
3.2 Generalised Models of Changes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
4. D
riving Forces for Change and Future Trends. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
4.1 Influence Analysis and the Identification of Key Factors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
4.2 Alternative Projections. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
4.3 C
lustering Alternatives – Consistency Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
5. S
cenarios on the Knowledge Production of Multinational Enterprises.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160
5.1 Scenario 1: 2020 – The Long Boom.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160
5.2 Scenario 2: 2020 – Ups and Downs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
5.3 S
cenario 3: 2020 – Handpicked Innovation.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
5.4 Scenario 4: 2020 – Zero Growth. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
6. I mpact Analysis of the Scenarios of MNEs on the European Research Area and the European Knowledge Society. 164
6.1 ‘ The Long Boom’ – Impact and Policy Recommendations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
6.2 ‘Ups and Downs’ – Impact and Policy Recommendations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
6.3 ‘Handpicked Innovation’ – Impact and Policy Recommendations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
6.4 ‘Zero Growth’ – Impact and Policy Recommendations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
7. Bibliography.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166
8. Appendix.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168
9. Bibliography. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
10. C
urriculum Vitae. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174
9. National governments..
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
175
Jari Romanainen, Helsinki University of Technology
1. Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
1.1 Types of government organisations and their role in STI. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
1.2 Changes in STI policy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
2. M
ajor driving forces shaping government organisations.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
2.1 External drivers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
2.2 Internal drivers.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184
2.3 Key policy implications.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
3. Future outlook. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187
3.1 Quality of STI-policy processes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187
3.2 Blurring systemic boundaries.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188
3.3 Attractive environments for innovation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189
3.4 Weak signals. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190
4. Scenarios.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191
4.1 Introduction.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191
4.2 Global context of STI in 2020. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193
4.3 Scenario A: Business as usual. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194
4.4 Scenario B: Radical transformation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198
4.5 Scenario C: Europe of regions.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202
5. E
valuation: The policy goals perspective. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204
6. Bibliography. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206
7. Curriculum Vitae. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206
10. Regional Governments..
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207
Luis Sanz-Menéndez (with the collaboration of Laura Cruz-Castro), CSIC-UPC-SPRITTE
Presentation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1. I ntroduction: The Europe of Regions?. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2. The role of Regional Governments in the Knowledge Production and Research Systems..
. . . . . . . . . . . . . . . . . 207
. . . . . . . . . . . . . . . . . 207
. . . . . . . . . . . . . . . . . 209
2.1 Rationales for science and technology policy at the regional level.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209
2.2 The diversity of regional intervention in the science and technology domain. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211
3. R
ecent key trends affecting the role of regional government. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214
3.1 Europeanisation and Regionalisation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214
3.2 I ncreased involvement of regional governments in science and innovation issues and the role of Structural Funds.. . . . . . . . . 218
3.3 Other trends. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219
4. D
riving forces for change and future trends. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220
4.1 Regional Governments as actors in the ERA governance.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220
4.2 R
egional governments as arenas in which other S&T actors play political games. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222
5. S
cenarios for regional governments’ functions in knowledge production and research systems.. . . . . . . . . . . . . 224
5.1 Business as usual. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224
5.2 Radical transformation.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225
5.3 R
eduction in the role of regional governments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225
6. I mpact analysis of scenarios on ERA and the European Knowledge Society: The policy goals perspective. . . . . . 226
6.1 Business as usual. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226
6.2 Radical transformation.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226
6.3 Reduction in the role of regional government. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227
7. Bibliography.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228
7
8
1
W o r k in g
Paper
Civil Society
Henning Banthien, IFOK GmbH
(in cooperation with Dr. Jörg Mayer-Ries and Indre Zetzsche, IFOK GmbH)
There is also a very special need for further clarifications
related to the specific actor of civil society:
• as far as civil society has to be distinguished from
other actors like industry, which sometimes are
seen as part of civil society; and
• as far as especially civil society is also in several
other aspects a very open concept, much more
open than the perception of other actor groups.
Both the underlying conceptions of the field of
knowledge production and of the actor civil society
have to be outlined before trends, key drivers and
scenarios can be looked at. Both concepts are
understood very broadly here, according to the
recent scientific and political discourses. That is
even more the case for this exploratory analysis,
which has to focus on new emerging dynamics
which are based on the drastically changing forms of
civil society, knowledge production and their mutual
linkages. Having said that, it becomes evident that
the conceptions of knowledge production and civil
society are interdependent ones and should be
framed in an approximately coherent way.
A third dimension to clarify is the conception of the
European Research Area. This can be done quickly:
the notion ‘ERA’ implies very different levels and
dimensions of European research structures and
activities, such as:
• the EU level of research policy institutions and
research policy instruments;
• the area of participation of European Union (EU)
non-Member-States;
• the area of other social actor groups and individual
citizens involved in research; and
• the broader context of knowledge production
(see also 1.1).
1.1 Knowledge and knowledge production
9
‘In the knowledge-based economy and society there
is a growing and diversified demand for specialised
knowledge, at a time when the organisational,
methodological and disciplinary borders of that
knowledge are changing as well. The result is a very
dynamic and rapidly expanding demand and supply of
knowledge, which is translated into shortened product
life cycles, rapid and world-wide standardisation
processes, new forms of organising production,
new consumer-producer relations, and new societal
demands about knowledge regarding risk and safety
matters’ (The Europe of knowledge 2020: a vision for
university-based research and innovation, 2004).
According to the recent discussion in science theory,
knowledge sociology, innovation theory and other
relevant related debates, this study and its scenarios
build on a knowledge concept which is substantially
broader than classical definitions. Classical
definitions refer to an exclusive model of knowledge
insofar as scientific knowledge is classified as
the only legitimate knowledge. According to this,
knowledge is characterised by the following criteria:
• it is produced by scientists or academics;
• it consists of revisable hypotheses and objective
facts; and
• it is structured by disciplines and resorts.
Paper 1
Civil Society
T
he issue of civil society as a ‘key research actor
in the European Research Area’ needs to be
specified with regard to the mandated field of
analysis. There is a need of defining what shall be
understood by knowledge and knowledge production
insofar as this is the central field of social activity
that this prospective analysis looks at.
• the levels of trans- and supra-national, national,
regional and local research actors, fields and
policies;
W or ki ng
1. Definitions
The Future of Key Research Actors in the European Research Area
10
In contrast, our concept of knowledge includes a
wider spectrum which also encompasses other
actors and kinds, other production places and
applications. The hegemonic meaning of scientific
knowledge is increasingly questioned, for example in
recent scenario processes on future developments of
research, science and knowledge (EUROPOLIS 2002,
STRATA-Workshop 2003, Visions of ERA 2020, 2005).
Even the field of non-knowledge, to be explored or
to be taken out of any social function, enters the
modern analysis of the knowledge society.
co-evolution, e.g. between producers and users
(Coombs 2002, von Hippel 2005), within innovation
systems (Nelson 1994), between science, society
and markets (Rip 2002, Callon 1992). Of course
all these concepts imply new relationships
and meanings of civil society in the knowledge
production process. They take into account
mental and cultural frames of citizens engaged in
science, consumers’ innovative role, emerging civil
intermediaries as mediators between different
knowledge actors, etc.
Context of knowledge production
Mechanisms and modes of knowledge
production
The European industrial societies can more and
more be characterised as knowledge societies.
Knowledge is becoming the crucial resource of social
and economic welfare, and this resource is more and
more distributed in highly specific forms amongst
different actors. There is a widespread discussion on
a new ‘social contract’ between science and society
(Nowotny 2001, Jasanoff ). It is focusing on the coevolutionary way knowledge, technology and society
are developing and engaged in the implications of
the new form of knowledge production. According to
Nowotny, Jasanoff and others, knowledge production
takes its economic, political, social and cultural
context early into consideration (reflexivity) and
gets socially more robust (contextualisation). With
these contexts knowledge production encompasses
new areas, for example:
• innovation and implementation;
• education, training and learning;
• knowledge management;
• research governance;
• science-society dialogue (as parts of the
formation of the appliance of knowledge, and as
the economic, cultural or social environment of
research).
The
new
dynamics,
interactions
and
interdependencies of knowledge production are
described in several concepts. Nowotny, Gibbons
and others state a shift from knowledge of mode 1
(classical, basic science) towards knowledge of
mode 2 as applied, robust knowledge (Nowotny
2001). Leydesdorff and Etzkowitz conceptualise
the dynamics in the notion of the triple helix of
knowledge production in clusters of universities,
industry and policy (Leydesdorff/Etzkowitz 1998).
In addition, there are the different notions of
As a consequence of distributed knowledge,
the production of ‘legitimate knowledge’ has
changed from scientific knowledge production
to ‘trans-institutional knowledge production’ (in
clusters, networks and teams of diverse actors).
Interdisciplinary and transdisciplinary knowledge
production is increasingly important. The boundaries
between disciplines and between scientific and
non-scientific areas are losing their predominant
meaning, as a structuring frame on the one hand,
and as a barrier on the other, for research and
knowledge creation. There is incremental knowledge
growth and at the same time radical changes. The
high-speed acceleration of knowledge production
goes hand in hand with the identification of unknown
areas and the loss or even destruction of knowledge
bases. The degree of complexity of knowledge will
increase, and the places of knowledge production
can be very different: it is not only ‘the university’ or
‘the research department within companies’ that are
the locations and modes of knowledge production.
There are increasingly the technologies to create,
collect, share, transfer and store knowledge that will
become more sophisticated and important. Therefore
knowledge production on the one hand will perhaps
be more and more manageable in a global virtual
space; on the other hand, the local place could be of
increasing relevance for the production of specific,
but relevant, types of knowledge.
Actors of knowledge production
Thus the knowledge producer is a hybrid actor:
• In the emerging shape of future knowledge
production there is a multiplicity of actors
beyond scientists and science funders that has to
be taken in account: industrial representatives,
consultants, politicians, administrative experts,
teachers, consumers, artists, media persons,
intermediaries etc.
New concepts, with their variety of actors and
interdependent relationships, are a better reflection
of modern knowledge production systems than
former linear dualistic concepts – from the purist
researcher to the applying businessman.
Different kinds of knowledge
Recent contributions to the knowledge debate make
it evident that the widespread notion of knowledge
as a scientific-based construction falls short. It
excludes important dimensions like non-sciencebased knowledge, institutional, social or cultural
knowledge, and it ignores that values, ethical
orientations, cognitive frames and social contexts
influence other knowledge forms like scientific
reflection and even the material design of technology.
From a much wider perspective, knowledge includes
diverse kinds and levels of knowledge, which can be
divided into implicit and explicit knowledge:
Implicit Knowledge
Daily-life knowledge
Common-sense knowledge
Experience knowledge
Local knowledge
Indigenous knowledge
Action knowledge
Explicit Knowledge
Practical knowledge
Theoretical knowledge
Orientation knowledge
Creative knowledge
In addition to the kinds of knowledge, there are
also different forms of knowledge – like normative
and descriptive knowledge, strategic and operative
knowledge, scientific and empirical knowledge as
well as past- and future-oriented knowledge, etc.
All these kinds and forms of knowledge have one
Knowledge access
Alongside the described transformation of the
knowledge production context (see ‘context of
knowledge production’), the state of knowledge
is also changing. Currently, two contradictory
developments can be observed: on the one hand,
knowledge seems to be turning into a public good,
since the internet in principle opens free access to
everyone. The open source movement, increasingly
shaping the software sector, is the most frequently
cited example here, but also the knowledge of sport
article users or clinical surgeons can be cited as
advanced forms of free knowledge for practical uses
and product innovations (von Hippel 2005). On the
other hand there is a contrary development. With
its increasing economical relevance, knowledge is
becoming a private good or product. The intensive
discussions in the European Parliament concerning
the outreach of business models for knowledge
management, and intellectual property rights
specifically, are a good indicator for the powerful
challenges societies have to deal with.
1.2 Civil society
The traditional concept or notion of civil society,
which was influenced by elite and direct democratic
theorists, is transforming. ‘Comparative and
historical studies have largely shifted the discussion
from normative, idealised conceptions of civil
society to real approximations of that concept.
These empirical studies, in addition to those reexaminations of the term’s intellectual history which
have shown it to be far less monochromatic than
had been previously assumed, have led civil society
researchers to consider anew what, exactly, they
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Civil Society
• It is not only one specific kind of knowledge
which can be attributed to one specific person
or institution. Different kinds of knowledge
are produced simultaneously: a researcher in
stem-cell biology for example may produce
abstract knowledge for biological theory and at
the same time practical knowledge on how to
use new analytical instruments and to work in
interdisciplinary teams, knowledge of economic
and organisational interests supporting or
hindering his research work, and ethical
knowledge about the implications of specific
experiments. Specific expertise contains different
kinds of knowledge, although often this is not
made explicit.
common characteristic: they have to be seen within
a cultural context insofar as they all have to be seen
in cultural traditions. Daily-life knowledge or local
knowledge are not the only types to contain cultural
values and biases; soft and even hard sciences
are not completely independent of history, place,
social context and values either. Besides that, it is
very important to add this: beyond the horizon of
the ‘known’, the field of knowledge also includes
uncertainty and risk as well as openness, holistic
and long-term orientations. ‘The validation of
scientific knowledge outside laboratory conditions
is a critical stage, where questions from lay people
and other forms of knowledge come into play. It is a
central element for the modes of governance in the
European knowledge-based society’ (Commissioner
Janez Potočnik, World Science Forum Budapest, 10
November 2005).
W or ki ng
• Secondly each of these actors has more than one
distinctive role, specifically if civil society and the
citizen are taken into account. Scientists can be
part of research institutions, administrations or
business, and they often act as singular citizens
or in civil society organisations as well.
The Future of Key Research Actors in the European Research Area
claim to study.’ (G. Rosen 2003). Civil society can be
characterised by the following traits:
1.Civil society is an autonomous system besides
the economy, polity, science, media and culture;
Civil society engagement takes place in a variety of
formats and depends on the degree of participation.
According to the Danish Board of Technology it can
be differentiated into the following categories:
• Providing information (for example pamphlets);
2.Civil society is orientated, to a greater or lesser
extent, towards democratic values, e.g. equality
or justice;
3.Civil society is characterised by a discursive,
deliberative practice;
4.Civil society has a high critical potential, i.e. it
has a controlling and corrective function;
• Taking feedback (for example Eurobarometer);
• Getting into dialogue (for example citizen
hearings);
• Supporting articulation (for example consensus
conferences);
• Giving influence (for example mediation);
5.As the result of the characteristics described
above civil society has a socially integrative
function.
Rationale and function of civil society
12
As democratic, discursive and deliberate practices,
civil society actions can be described to a large extent
by the democratic principle and by democratic values
in general. Civil society organisations are generally
organisations whose members have objectives and
responsibilities that are of general interest and who
also act as mediators between the public authorities
and citizens (cf. EU Commission, Science and Society
Action Plan, 2001). Thus their function can be
defined in correspondence to the main criteria for the
assessment of public participation described below:
• Strengthening
the
accountability
transparency of decision-making;
• Improving the
decisions;
quality
and
legitimacy
and
of
• Creating acceptance and a consensus concerning
decisions;
• Building trust between administration and civil
society;
• Stimulating
networking;
individual
and
institutional
• Raising public awareness and knowledge on
scientific issues;
• Improving the active involvement of citizens in
the democratic process;
• Being cost-efficient.
• Giving power (for example direct democracy).
Currently the civil society rationale and function is
transforming, which may open new opportunities
but also risks, as Kuhlen has shown in the example
of non-governmental organisations (NGOs): ‘NGOs
might seek to become more isomorphic with
businesses or government agencies with which
they compete. The scarcity of donors forces some
NGOs to turn to business solutions to survive
and to intensify their relations with business and
government. Thus self-interest compels increased
co-operation with public and private sectors. This
opens new opportunities for sustainability, yet if
they work too closely with the state or business,
NGOs risk serious accountability problems,
including co-optation, loss of legitimacy and
failure. Conversely, if NGOs reject co-operation
with state and market forces too radically they
risk slipping into an exclusively oppositional role
with diminished opportunities for agenda setting.
Co-optation by state and market forces are the
Scylla and Charibdis of NGOs’ (Kuhlen 2003).
Actors of civil society
Like the actor of knowledge production, civil society
does not exist as one solid entity, nor is there a
clearly defined set of stakeholders and institutions,
but rather it consists of hybrid actors. According to
the European Commission, civil society includes
‘trade unions and employers’ organisations (‘social
partners’);
non-governmental
organisations;
professional associations; charities; grassroots
organisations; organisations that involve citizens
in local and municipal life; churches and religious
communities’ (European Commission, Science and
Society Action Plan, 2001). According to the concept
of hybrid identities of individuals, each actor of civil
• One is the institutional dimension of civil society,
consisting of global networks, associations
like NGOs, large institutions like churches and
foundations, local advocacy groups, single-issueor short-term-movements. The institutional
dimension of civil society is often represented
in round-tables, lobbying or managing huge
programmes for development aid for example;
• Secondly there is the notion of civil society as one
compact actor, like the third sector, which plays a
relevant role for the economy and democracy;
• Another dimension of civil society is its character
as individual citizens or loose groups of citizens,
relatively unorganised parts of society, which
engage in common interests by participating in
demonstrations or engaging as volunteers for
common interests, for example.
Moreover civil society can be conceived on a local,
national, international or European level and
differentiated into local, national, European and
global civil society, whereas this differentiation
partly corresponds with the three dimensions
described above. The local civil society corresponds
with the third dimension of individual citizens, civil
society on the European or global level corresponds
with the institutional dimension, and the national
actor can be compared with the compact actor.
2. C
ivil society and
knowledge production
– sketches of the
current landscape
Knowledge production does not belong to
traditional civil society fields of action, like
advocating general interests or mediating between
the public authorities and citizens. All analytical
frameworks for civil society participation refer
to the problem of insufficient knowledge or
uncertainty, as well as to the problem of differing
or conflicting interests. The distinction between
insufficient knowledge on the one side, and the
The common discourse about the role of civil society
in research and knowledge production can be
differentiated along a variety of main activities:
• Information for transparency includes the setting
up of databases as a means of achieving more
transparency (e.g. CONECCS), internet-based
activities aimed at information and feedback (e.g.
Your Voice in Europe, DECIDE), or conferences;
• Understanding science is oriented towards civil
society as citizens, participating as a way of being
informed (e.g. through media or science fairs), or
getting exemplary experiences (e.g. in hands-onscience-museums);
• Technology acceptance is about civil society as
individual or organised citizens, being informed
about science and technology developments and
asked for their opinion concerning specific risky
technologies (e.g. participative technology and
risk assessments, science and ethics dialogues);
• Consulting research policy is the role of specific
parts of civil society mainly in its associated
forms, being informed about research strategies
and asked for advice concerning forthcoming
research policies, including activities concerned
with understanding science and technology
acceptance (e.g. participatory technology
foresight);
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Civil Society
Civil society’s actor roles have three dimensions:
problem of conflicting interests on the other,
helps to identify typical problem constellations
policymakers are faced with. Both on the
national and European level, various programmes
engage civil society in more participation for RTD
policymaking, for instance the Science and society
action plan, which is a basis for initiatives that
are meant to establish a true dialogue between
science and society, or CREST, a programme that
initiates, facilitates, and reviews participatory
processes in member states and the accession
countries and gives advice on the application of
civil society involvement within the Community.
Besides, many internet-based information and
consultation forums and conferences including civil
society actors are initiated to help to shape the
ERA. DG Research has recently started initiatives to
reform civil society participation procedures, e.g.
innovative civil society participation procedures
(consensus conferences, citizens’ juries), European
conferences with a wide range of stakeholders,
local and regional ‘science and society’ forums,
science shops, open dialogue, science weeks, and
research forums for interactive debates.
W or ki ng
society may have different and distinct functions
inside and outside civil society.
The Future of Key Research Actors in the European Research Area
• Lobbying on research and innovation issues is
also a field of activity for specialised civil society
organisations, trying to influence decisions ex
ante or ex post (e.g. health and environmental
policy NGOs, E-Governance).
Generally most of these activities have a very limited
influence on science as structure and process, on
research and research policy. Especially related
to the quantity and quality of activities of other
key actors and their importance to knowledge
production, this influence appears to be nearly
marginal. Civil society’s part in knowledge production
as it is currently discussed is neither situated in the
centre of creating and producing knowledge nor is it
managing or governing it. Research priority-setting
tends to revolve around key stakeholders, but not
including civil society. Science and technology
are still predominantly seen as value-free, and
the public as requiring education about scientific
principles (mainly in order to alleviate needless
fears). ‘Decisions about research are thus really the
domain of the research scientist or expert, but they
need to be communicated and justified better to the
public at large’ (Grant-Pearce 1998).1
14
Nevertheless it has to be stated that within
broader schemes of civil society and knowledge
production, the actual spectrum of civil society’s
role in knowledge production and its subsystem of
research is more multifaceted. Citizen involvement
in knowledge production thus includes:
• Financing knowledge production processes:
Individuals, advocacy groups or powerful
foundations in civil society are engaged in fundraising, as ordering party or institutional employer
for research, innovation, education or science
communication activities2. Environmental NGOs,
human rights alliances, women’s associations and
a wide range of other organisations increasingly
ask for expertise from outside;
• Understanding, questioning and financing
knowledge production: Civil society is an
important actor in knowledge production as both
user and consumer of innovations, products, and
services. In the field of health, it is acknowledged
in the literature that consumers have insights and
1.The contrasting look at science and technology takes it as socially
constructed and reflecting particular social interests (and thus potentially
neglecting others), which fits to recent concepts on knowledge production
(see 1.1 above) and changing potentials and challenges for civil societies
involvement.
2.‘The non-profit (or voluntary) sector – which includes charities (foundations) –
has become an important social and economic actor all over Europe
– although differences are still to be found among countries – and its
importance as a source of funds for RTD activities is increasing everywhere’
(Sessano 2002: 4).
expertise that complement those of healthcare
professionals and researchers (Grant-Pearce
1998, von Hippel 2005);
• Involvement in competence development for
knowledge production: Civil society is to a
great extent involved in education and training
processes, at the level of primary and secondary
schools, academic or vocational training etc.;
• Transferring
and
brokering
knowledge:
Knowledge transfer and brokering are core
activities of civil society organisations, e.g. the
science-shop movement or other specified NGOs
(Bach/Stark 2003).
In the socio-geographical and cultural dimension of
today’s Europe, civil society is also multifaceted. Civil
society’s structures, functions, power and potentials
are strongly dependent on the historical, political
and economic as well as the cultural and religious
context. Even very general attitudes therefore differ
from context to context. There are regional cultures
which believe in consultation with social partners
and stakeholder dialogues, in others the role of
civil society is seen as a challenge of multilevel
governance, or as the key factor for reforming the
legal and political system as a whole. Another
example of the differences concerns exposure to
conflicts. Conflict resolution methods strongly
depend on the cultural context, and thus successful
forms of conflict management, for instance, cannot
simply be transferred from one country or region to
another. However, especially due to its decentralised
structure and its multiplicity of cultures, Europe also
offers a broad field for experimentation with new
modes of civil society participation in knowledge
production and research.
3. Recent key trends in civil society dynamics
The authors of this draft have collected information on key trends with regard to the dynamics of civil society
and knowledge production, and analysed them by taking into consideration their low or high impact as well as
their low or high uncertainty. These trends are arranged in the two-by-two matrix below. This chapter refers to
the trends, which have been identified as high impact and low uncertainty (see two-by-two matrix field I).
Demographic
change
Combination of different
areas and types of knowledge
Globalisation
Use of market mechanisms
for n.n. interests
Need to
professionalize
Knowledge
production,
role of institutions
Culture as
European USP
Market of
knowledges
> tradability
Mobilisation
of interests
Development of
funding sources
Trust
Education,
learning process
Values, ethics,
identity
Visibility of (new)
knowledge
(non-research
indicators)
Access
Self-organizing
capacity
(networking,
skills)
Integration of
value-chain driven
by few players
Giving culture
Control over
knowledge
concentration
Orientation knowledge
> google?
IT-Revolution
Transformation of
intermediaries
Governance
I
II
Outsourcing of research
> India, ...
Mobility
Fragmentation
of biographies
Transparency in resource
flows (finance)
Migration
Security
> robustness of
research system
III
IV
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Civil Society
Integration of
indigenous knowledge
W or ki ng
Service economy
(Dienstleistungsge sellschaft)
The Future of Key Research Actors in the European Research Area
3.1 IT society
New generations of information and communication
technologies will have a high impact on the
production, distribution and organisation of
knowledge.3 The technical standardisation in ICT,
the enlargement of mobility networks, ambient
intelligence or ubiquitous computing will foster
the exchange of information and knowledge
and become important in expanding the web
of social interaction, increasing its density, and
promoting new connections among diverse and
dispersed social actors.4 Organisations become
more flexible, temporary and spontaneous, and
further development will possibly foster this
transformation.
16
In addition, there will be increasing access to
diverse forms and kinds of knowledge via the
internet. Besides that, specialised and technological
knowledge, orientation and action knowledge,
and local knowledge will be provided through
the internet and accessed via search engines
like Google. However, the so-called digital divide
continues to expand in quantitative and/or
qualitative dimensions. Beyond that, the issue of
knowledge organisation is becoming more and more
virulent since digital memory capacities are limited
both spatially and temporally.
3.2 Open and transparent decision-making
The technological potentials for opening governance
patterns coincide partially with other factors
that make political and administrative decisionmaking more open and transparent on all levels.
This trend answers not least to the demands of
citizens and interest groups for more information
on the legitimacy, specific issues and procedures
of decision-making. One of its consequences is
an increased accountability of involved actors.
The arena of political decision-making tends
to move from ‘lobbies’ to other, more open
and transparent locations. This also applies to
traditional intermediaries between different interest
groups as well as different societal systems. For
example, the relationship between science and
society is shifting from a top-down approach with
‘public understanding of science’ conceived as
3.For example the new IPv6-protocol replaces the 20 year-old current
version of the Internet protocol IPv4, allowing for a significant quantitative
expansion of IP-addresses and access opportunities.
4.‘Digital technologies make it easier for people to reconstruct what counts
as information so that its definition, or at least its circulation, is no longer
the exclusive prerogative of those with power, money and connections. The
increased ability of individuals to gain access to large amounts of disparate
information is justly celebrated as empowering. At the same time this kind
of access presents serious problems for any organisation that seeks to exert
control over information collection or dissemination’ (Kuhlen 2003).
the dissemination of scientific knowledge, to an
approach of mutual receptivity in the sense of
‘science in society’. Nevertheless this trend has to be
set in relationship to developments like increasing
multi-level, globalised and complex structures of
problems, decisions and political actions, which
have contrary effects on transparency, openness and
access to decision-making processes.
3.3 Inclusive knowledge production
Policymaking with respect to science and
technology is also becoming more inclusive. This
means that previously closed policy-circles are
breaking up, and new actors, including parts of
civil society, are becoming involved. The monopoly
of scientific experts on the supply of expertise is
increasingly questioned and the specific knowledge
of stakeholders and practitioners is asked for
as ‘democratised’ expertise. The open source
movement in the IT-sector actually broadens up
to a more general open-innovation dynamic in the
economic sector. This trend also has the potential
for consumers, users or patients to gain growing
importance for evaluating policy options. Science
itself is held accountable by society for its choice
of research topics and comes under pressure to
serve societal and economic demands. Applied
research and applied basic research gain increasing
political support and social meaning related to basic
research (see the national foresight process Futur
in Germany5, which is based on the principles of
dialogue and demand-orientation as an example
for this emerging trend). As a consequence, there
is a growing demand for policy tools to raise the
‘scientific literacy’ of the public.
3.4 Emerging knowledge business
With the knowledge society as the emerging
economic core, there is a strong trend to define
successful and sustainable private business
models of knowledge management, production,
dissemination and storage. These models have to
deal with the different characteristics of ‘classical’
and ‘knowledge’ products and processes, to design
profitable interactions of these different sectors
and to meet the challenge of a huge variety of
different knowledge modes. ‘In the knowledgebased economy and society there is a growing and
diversified demand of specialised knowledge, at a
time when the organisational, methodological and
disciplinary borders of that knowledge are changing
as well. The result is a very dynamic and rapidly
5.www.futur.de
Companies and public institutions increasingly give
up specific activities previously done in-house.
Depending on the sector, size and strategic position
of companies, outsourcing also includes R&D as
an integrated part of the business, in order to save
costs and seek competitive advantage. SMEs in
particular have to face the challenge of requiring
highly complex research and development on the
one hand, and having very restricted financial
and personal resources (in the context of global
competition) on the other. Beyond its impact on the
technology’s quality, the final product or service
cost, and the potential market, outsourcing may
offer the ability to access a wider range and higher
quality of equipment and/or expertise for the firms.
On the other hand, this trend has a high impact
on knowledge production, the involved actors,
and on the location and governance of knowledge
production. It may force the economisation of
science, the integration of new actors and new
kinds of knowledge, and the decentralisation of
production.
3.6 Applied research dominates
Research activities – whether on the national
or European level or in industry – are becoming
more application- and service-oriented. In the
last decade, investment in R&D for instance was
concentrated in the fast-growing ICT sector but also
in pharmaceuticals, chemicals and food insofar as
they were related to biotechnology. The service
sector is to a large extent based on the application
of knowledge on non-physical products. R&D and
technical knowledge in particular, but also practical
knowledge (e.g. consulting knowledge), have grown
out of a subset of activities of industrial enterprises
and have become businesses in their own right.
Trade in intellectual property, and particularly
in technological knowledge, seems to become
a strategic element in knowledge production.
Foundations, NGOs and other organisations are
increasingly engaged in this business in order to
achieve a higher impact through knowledge-sharing
and knowledge creation.
The demographic changes incurred by ageing and
shrinking populations will have multiple effects on
the economic and social transformation. The literate
generation is shrinking, and for this reason so are
traditional knowledge, values and human capital.
As a consequence, the gap is widening between
demand for, and resource of, highly-qualified
knowledge specialists. This development could also
strengthen civil society by giving it an important role
in education, in knowledge transfer and the creation
of human capital (education has been one of the
core values of civil society ever since its formation
during the Enlightenment). Demographic change will
also have an impact on knowledge production itself,
since an old society has different needs and makes
different demands on knowledge.
3.8 Globalisation
Globalisation has today been applied virtually to
every aspect of human life already. The production
and dissemination of inventions and innovations
have become much more global. ‘The need to cut
the costs of innovation has created new forms
of industrial organisation and new proprietary
arrangements, which are now expanding beyond
the technological sphere as such. Both small and
large firms are active in this form of transmission of
knowledge; in particular, small firms can use it as
an alternative source to innovate preserving their
ownership. In reality, enterprises have imitated a
method of generating and transmitting knowledge
typical of the academic community. The academic
world has always had a transnational range of
action, with knowledge being transmitted from
one scholar to another, then disseminated, without
economic compensation being invariably necessary’
(Archibugi 2000).
4. Driving forces for
change and future
trends
Driving forces are dynamic factors in the sense of
being high impact key trends or combinations of
key trends, which are uncertain with respect to their
development path and their implications. These
implications will have a wide-ranging influence on
the role of civil society in knowledge production,
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Civil Society
3.5 Outsourcing
3.7 Ageing and shrinking societies
Wo rki ng
expanding demand for and supply of knowledge,
which is translated into shortened product life cycles,
rapid and world-wide standardisation processes,
new forms of organising production, new consumerproducer relations, and new societal demands about
knowledge regarding risk and safety matters (food
safety, environmental protection, etc)’ (The Europe
of Knowledge 2020, Liege 2004:4).
The Future of Key Research Actors in the European Research Area
but will differ significantly depending on their future
development and interaction with other trends.
Driving forces shaping the future of civil society and
knowledge production are taken as the essential
background for the alternative scenarios.
4.1 Global knowledge economy
Europe is a globally-connected economy which
is increasingly competing with Asia and other
players for resources, human capital, markets and
strategic innovations (China, India). Knowledge
production will be the decisive field for sustainable
welfare growth.
Organisation of value chains
18
Within the context of global competition,
technological innovations and socio-political
developments, new and powerful organisations
and re-organisations of the economic system
along value chains will prevail. The vertical and
horizontal integration of production and service
industries creates highly complex and powerful
clusters, acting globally and shaping international
systems, but also shaping life in its local,
individual and collective forms. Integration on this
global level nevertheless includes outsourcing
and loose-networking in subsidiary fields. The
emerging units which manage huge parts of the
economy and their socio-political environment
will be highly hybrid forms of management.
These follow the strategy of integrating all aspects
around product cycles, life and consumer styles,
or resource bases, in order to gain power in a
globalised market.
However, there is still a lot of uncertainty about
which powers, cultures and persons with which
interests, values and ambitions, will act in these
agglomerations. What balance of inclusion and
exclusion, what degree of freedom and hierarchy,
will shape these global value chains? To what
extent can actors like civil society gain influence
from outside and from inside these emerging
‘economic structures’? What is the business model
of knowledge production, if open-source systems
overcome the status of niche markets – who earns
money by which mechanisms, if at all? Will it be
a marginal or a dominant role, or will civil society
transform itself in this context? Where exactly is
the future of research, in geographic terms and
also in the public/private spectrum, assuming
hybrid global structures demanding and paying
for knowledge, which always try to be highly
flexible?
Access to and visibility of knowledge
Access, control, visibility and tradability of
knowledge, as the new key production factor,
are crucial aspects for society’s future shape, its
knowledge production, and the role of civil society in
the ERA. The regimes which distribute power, control
knowledge access and the mechanisms which allow
knowledge to be socially visible and economically
tradable, will also decide about political power
structures, the form of social cohesion and the
cultural meaning of knowledge and research in
Europe.6
According to the question of future powers and
values, the potential of civil society to have access
to and control knowledge production is not certain
and neither are the areas of knowledge where
these potentials will have influence. Will civil
society influence basic values, ethics and political
orientations (will churches increasingly influence the
agenda of stem-cell research, for example?) or will
civil society shift to influence the local, the specific,
the single-market processes? Will public research
remain and grow as the sphere for civil society
engagement? If so, with which power and with what
benefit to global competition? Or will today’s implicit
knowledge domain (of individuals and societies)
become the starting point for a powerful civil actor
in all branches of research and research funding?
And what then will be the rebound effects on civil
society?
4.2 S
ocial cohesion and individual identity
in the knowledge society
Since its origins (and nowadays still) civil society
has been closely associated with ethical and valuerelated aspects of science, technology and research
policy, and at the same time with the fact of trust
deficits in (public) policy actions and institutions.
Values, cultures and ethics also play an increasing
role in the science and research debate, reflected
by the recent analyses of the history of science and
knowledge sociology. Broadening the perspective
towards a wider range of knowledge production
areas like education, innovation, arts or practical
experience, these ‘soft’ dimensions play a relevant
6.Today ‘knowledge trading’ is a term restricted to the sphere of private
business companies and questions of property rights, but the phenomenon
is a rapidly emerging one as the less visible dimension of local as
international transactions in markets, networks or other social structures
of exchange. Interestingly the organisation of ‘stock markets for knowledge
(Wissenbörse)’ are up to date only defined in the sphere of civil society,
as local platforms to supply individual informations about personal skills,
interests, hobbies and other resources for non-profit (often initiated by local
church communities, hosting a website).
With increasing individualisation, globalisation,
mobility and ubiquitous ambient technical
infrastructures, trust and subjective safety will be
of more and more relevance in private, professional
and public life, in the sphere of politics as in the
economy and science. Overregulation on the one
hand, or social disintegration on the other, will
be challenging trends, if trust is not ubiquitous
in society. To illustrate this: the critical comments
made by social groups about green biotechnology
provokes a rigid regulation which is not the case
with red biotechnology. The public obviously trusts
medical doctors more than lab-researchers from
agricultural companies.
Ethics and values
Interlinked with the trust factor are the shaping
factors of ethics and values. This is the case for
society as a whole and specifically for the future of
civil society and knowledge as areas of actors and
activities that are very sensitive to ethical dynamics
and differences. With science and technology
approaching the ‘complete manipulation’ of the
human being and the natural environment (genetic
engineering, ambient intelligence, etc.) ethical
discussions will perhaps reach a new level of conflict.
Will they have low or high impacts on political,
technological and economic decisions? Who will take
up this questions: civil society, consumers, specific
economic sectors or less-developed countries?
Cultural diversity as a European factor
The specific cultural diversity not only creates the
strength, dynamics and variety of civil society in
Europe but also acts as a ‘unique selling point’ for
Europe’s knowledge production and research sector,
as compared to other global players in this field.
The shape and substance of trust, values, ethical
reasoning and culture will change of course, there
will be no replication of moral and cultural patterns
in the 19th and 20th century. The further differentiation
of ethical frames, lifestyles and spiritual orientations
will happen simultaneously alongside a decline in
the conventional variety of linguistic and traditional
cultures. But who will define these value frames,
and what will they look like in 2020? What impacts
will the growing individual and social meaning of
trust, values and ethics have? What about identity
formation in a knowledge society and the ‘economy
4.3 New governance mix
Hybrid governance patterns and network
society
With the increasing openness and transparency
of policy, another – much wider – development is
associated, known in public administration circles as
the emergence of ‘meta-management’. The reliance
on old institutions continually decreases and the
boundaries between institutions and organisations
become less significant. Michael Gibbons describes
these process as a transformation from ‘weaklylinked systems consisting of discrete components’
to ‘strongly-linked systems of fuzzy components’.
Complex networks increasingly take over the
management of societal change processes. They are
characterised by the equality of actors, flexibility,
creativity and alliance-building as their superior
aim. Encouraging effective alliances, coordinating
different interests, and acting as an intermediary,
are also becoming more and more important tasks
for administrators in both the public and the private
domain. New governance patterns are arising in
many countries today: in Germany the ‘partners for
innovation’ or the national foresight process Futur
both bring together a heterogeneous group of actors
and coordinate a variety of thematic and conceptual
policy processes.7
The combination of different governance
mechanisms will be necessary to get the complex
future challenges managed – hierarchical, market,
value-oriented and network-based steering patterns
will be arranged in hybrid forms of institutional
settings. Public organisations, private business,
intermediaries, individuals, time-limited movements
and more static associations are interlinked for
governance tasks, with different power potentials,
knowledge resources, values and strategies. Nongovernmental and market-driven governance
patterns merge with the classical sphere of
governmental policy, fundamentally challenging
the third-sector role of civil society in its ideal-type
position beyond state and market.
Development of funding sources
The culture of donors and funding, the mechanisms
of financing and funding sources, will change along
7.The Netherlands, Denmark or UK can also provide relevant examples for
new governance modes.
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Trust matters
of attention’, where information and perception
are the predominant basis for social inclusion and
cohesion?
W o rk i ng
role and will have an increasingly explicit (and
visible) impact.
The Future of Key Research Actors in the European Research Area
with economic, cultural and political developments.
This has a high impact on the quantity and quality
of research and knowledge production. Churches or
NGOs may increasingly finance their own research.
Pure public funding will decline and will be shaped
along new governance objectives. But what will be
the role of industrial, non-governmental or individual
funding? What could a hybrid financing scheme
mean beyond today’s public-private partnerships,
especially as regards new knowledge-production
areas and structures that will attract money in the
future?
Mobilisation of interests
20
Civil society organisations are becoming increasingly
important actors in innovation by enhancing their
use of new technologies to go beyond their existing
roles as safety nets and as safety valves. In the long
run, civil society organisations could function as
social entrepreneurs that explore new organisational
forms, and thus as sources of societal innovation.
However, this transformation also means that
civil society organisations are caught increasingly
between the business value system (efficiency,
market needs) and their social mission (adherence
to principles, ideological agendas). An example
might be the steady growth of associations for
organic food initiated and sometimes managed by
consumers. The motivation originally was to support
the change towards sustainable agriculture and to
eat healthy food. Over time these approaches have
grown to very successful business models driven by
farmers and/or consumers. The farmers earn more
money since they provide people with innovative
– i.e. healthy, sustainable, regional, tasty, morally
rich – products.
5. Scenarios
5.1 Scenario I: Citizens for Innovation
or The Role of Civil Society in an
Economically-Governed Europe
Basic developments and drivers:
• Europe is a globally connected economy which
is increasingly competing with Asia and other
players for resources, human capital, markets
and strategic innovations.
• Research activities – whether at the national or
European level, or in industry – are predominantly
application- and service-oriented, 80 per cent of
research funds derive from the private sector.
• Civil society is mostly visible and effective in the
field of markets and production, due to the crucial
role of customer relationships for industries’
economic success. Civil society plays a minor role
in agenda-setting or governance at all political
levels.
• Trust, values and ethical questions play a crucial
role, therefore the prevailing distrust between
the economic-political elite and civil society is
a substantial welfare deficit, despite economic
wealth.
‘On the occasion of its ten years birthday, European
Minister of Innovation, Mr. Henri de Chevier,
compliments the Consumer Platform “Citizens for
Innovation” on its Contribution to European Location
of Innovation’, announces Daily Europe, one of the
biggest European Newspapers in June 2020. ‘Citizens
for Innovation’ is a huge Europe-wide internetconsumer organisation founded in 2010 by some
national consumer organisations in cooperation
with a large food industry concern. Initiated as an
electronic B2C-platform ‘Citizens for Innovation’
has developed into the most influencing knowledge
fabric in Europe, that cooperates with business
companies from diverse branches like automobile
and chemical industry as well as service, food and
electrical industry. Since ‘Citizens for Innovation’
disposes of diverse kinds of knowledge – from
consumer interests and societal needs to practical
and theoretical knowledge – companies involve the
organisation in nearly all affairs including strategic,
conceptual and operational questions about
product development, R&D activities, marketing and
communications.
A recent priority of ‘Citizens for Innovation’ was
the development, design and global marketing of
bionic houses, based on mimetic technologies to
imitate natural constructions, materials, processes
and designs. On several virtual platforms – with
highly sophisticated access rules and mechanisms –
potential demand groups and users developed criteria
for product and production processes. Through
the exchange of culturally-specific knowledge in
building & construction and through diverse local
environmental, social and economic conditions,
these platforms created a ‘data pool on bionic
housing’, concerning, for example, technologies
for the flexibility and adaptability of bionic houses
or house components, nationally and regionally
differentiated potential demand extrapolations, and
‘The organisation has brought the European economy
back to the top of the world. It has strengthened its
competitiveness and sustainability by intelligently
organising and distributing knowledge’, de
Chevier is cited by the newspaper, ‘European
services and goods, especially its knowledge, are
highly demanded, companies register the highest
growth rates and each European country has full
employment – this is to a large extent the merit of
“Citizens of Innovation” and indeed of all European
citizens, since the organisation represents the new
European Citizenship and Culture. Efficiency and
solvency have not only became the core values
but also the driving forces of Europe.’ ‘Citizens
for Innovation’ as an institutional arrangement
originally emerged bottom-up and completely
independent from classical players in the research
and innovation system. But meanwhile this intiative
has found its fixed place in the European governance
system, although neither dominated by political nor
industrial influences. Its characteristic is a Europewide decentralised network structure, steered,
managed and monitored by small panels and in
a mode of explicit, but balanced and transparent
interests. Regional, national and European public
funds as private resources contribute to the
financial basis of CfI, but increasingly rents of
De Chevier’s speech reflects the current situation
in Europe. Indeed, the economic situation is very
satisfying, since the ‘idea of free entrepreneurship’
has became fully accepted in all European countries,
and business companies have taken on more and
more governance-tasks. For instance, the area of
knowledge production and distribution is to a large
extent a business responsibility, as the research
budget compositions highlight: 80 per cent of
national as well as European research spending
derives from the private sector. Companies promote
national research institutions as well as other
national and European research organisations.
In addition to that, they provide external private
research institutions or have their own R&D
departments. Accordingly, and since many influential
businesspeople hold political office (e.g. Mr. De
Chevier), their influence on national and European
research policy agenda-setting is very high. The
European Minister of Innovation is a member of
the executive board of a company specialised in
nanotechnology, and advocates the interests of the
nanotechnology industry in Europe.
Against this nepotism, as critics call the close
connection between policy and economy, as well
as the political situation in Europe in general some
political associations engaging in civil society have
started a public campaign. With the slogan ‘More
Democracy – Citizens for Participation’ they want
to create public awareness about the civil society
situation in Europe, and, as the linguistic similarity
to ‘Citizens for Innovations’ demonstrates, their
criticism also focuses on the consumer organisation.
From their point of view, ‘Citizens for Innovation’ is
forcing the loss of traditional democratic European
values like justice and equality, and changing human
self-perception by cooperating with the economy,
which only promotes applied sciences with a high
economic value. Nearly 80 per cent of the whole
research funding is dedicated to applied research,
for instance for information and communication
technologies or for medicine and pharmaceutical
research. In contrast, the funding for basic research
and for humanities and social science in particular,
has been slashed.
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Civil Society
‘Citizens for Innovation’ is a loose alliance of
organisations,
associations
and
individual
persons, who are interested or engaged in specific
technologies or simply interested in products which
accords to their individual needs. According to
their specific interest, competence and knowledge,
the members form different competence- and
knowledge-networks. In addition to that, each
member can play a part in diverse networks.
European farmers active in the bionic housing
‘sub-platform on organic materials’ are at the
same time engaged in the ‘sub-platform on local/
historical-knowledge in construction’, but also in
other ‘Citizens for Innovations’ networks, e.g. as
field experiment partners of research in the platform
on ‘food production without oil’ and as critical
assessment coaches in the platform of ‘primary
education in shrinking regions’. Each competence
net has its own work- and communication-space on
the internet-platform of ‘Citizens for Innovations’
where companies can get in touch with the experts
they need.
intellectual property rights owned by the platform
and its subordinated bodies and other revenues
from the platform’s knowledge services make up the
budget. Europe’s research-, innovation-, industry-,
service- and consumer-ministries on the supranational, national and regional level work in close
cooperation with ‘Consumers for Innovation’ and
guarantee the legal and administrative framework
for its effective work.
W o rk i ng
socio-culturally adjusted marketing strategies. Out
of this pool, ‘knowledge packages’ were built up to
sell them to the R&D, management and marketing
departments of construction and services industries
in the housing sector.
The Future of Key Research Actors in the European Research Area
22
However, the impact of the campaign will be
low since aside from economically-orientated
organisations like ‘Citizens for Innovation’, civil
society plays a minor role in agenda-setting or
governance at all political levels. In the elitedemocratic organised states of Europe, civil
society is willingly engaged in questions to avert
social conflicts or to create public acceptance for
political decisions, but not included in political
priority-setting. Critics argue that civil society
organisations are only tolerated because of their
socially integrative function. In any case, the
political influence of civil society is to a greater or
lesser extent limited to the local level, and its field
of action is more or less restricted to the social
sphere. Most civil society organisations act, or are
obliged to act, as collecting tanks for the interests
and needs of various groups, e.g. the churches
look after the beliefs and values of their members,
environmental organisations like the 50 yearold organisation Greenpeace still try to bring the
idea of environmental protection onto the political
agenda on behalf of the worldwide environmental
movement, lots of private science-orientated
foundations are funding research in the littlefinanced social sciences and humanities on behalf
of the idea of enlightening, and global political
organisations engage in anti-capitalism or antiglobalisation on behalf of the idea of humanity.
Some European as well as national politicians
agitate for more civil society participation in policy
and governance, since they see the potential of
participation, but these ideas have not yet become
accepted. Most politicians do not trust in the ability
of civil society to make decisions; they fear more
participation would bring forth political blockades.
5.2 Scenario II: The Knowledge Stock
Exchange – Europe’s Civil Society
Melts into the Market
Basic developments and drivers:
• Research-activities – whether at the national or
European level, or in industry – are predominantly
application- and service-oriented. Funds for
research and innovation derive increasingly from
hybrid associations beyond state, industry and
civil society.
• The degree of open access, visibility and tradability
of all different kinds of knowledge is very high, a
new key production factor is the linking of highly
divergent actors along and across the knowledge
production chain.
• Citizens’ capacity for self-organisation is well
developed, the culture of networking in the
predominant knowledge-production sector is
ubiquitous.
Europe’s KNOWLEDGE stock exchange (KSE),
located in Prague’s historical centre, prepares its
fifth anniversary in October 2020. In today’s meeting,
the board of directors discusses the idea of editing
a virtual booklet with a sketch of KSE’s successful
history and the way it works as a dynamo of Europe’s
knowledge economy and society. This booklet could
be distributed around the anniversary date to all
interested citizens and organisations. Through a
few snapshots, the KSE should be made visible
and understandable to readers as a catalyst for the
involvement of societal actors and the European
Research Area. The KSE board has to discuss what
could be said about KSE and how the different
levels, areas, actors, processes and challenges of
knowledge production should be presented.
The board of directors first collects general
aspects to characterise the background of their
organisation. Since the late 20th century, Europe
has been developing towards a real knowledge
society, competing and cooperating globally with
Asia and North America, while struggling hard to
keep its welfare status. To meet the challenges of
global competition and sustainability Europe has
created an intensive and extensive knowledgeproduction sphere, which is inspired by the
philosophy of open innovation. Life-long learning,
professional experience, problem-oriented basic
and applied academic research, creative thinking,
etc., are seen as different but relevant parts of
knowledge production in general and the European
Research Area as a political and economic project
in particular.
European nations, like all other competitors in the
global market, have developed towards extremely
individualistic societies. All associated and social
forms of life and engagement are associations on time
and predominantly driven by interests. Nevertheless
the high degree of individualism does not exclude
the potential to create social knowledge resources
– Europe even demonstrates that this individualistic
orientation can even foster common interests and
social cohesion. The belief in knowledge as a private
good is seen as the prerequisite for sharing it, with
profit for oneself and welfare effects for others. It
is therefore necessary to continuously search for
institutional arrangements at all levels of governance
and in all areas of economic, social, political and
cultural life.
In particular, the consumers and users of individual
and collective goods organise themselves in groups
to influence, fund and perform research. They appear
on the knowledge market as owners of innovation
knowledge for business, for political reforms, for
other interest and consumer groups. Besides that,
knowledge often does not appear on the market
without social and political support. In consequence,
it is not available for society.
To organise this knowledge market and to minimise
market failures, people and organisations in Europe
therefore needed a broad forum for knowledge
formation and trading, supported by appropriate
legal and political conditions, economic, technical
and social infrastructures and a mix of governance
forms which fit to the complexity and diversity of
knowledge production. Besides new businesses,
strategic alliances, advocacy mechanisms and
reformed political institutions from the local up to
the EU level in 2015, the idea of a Europe-wide stock
exchange for knowledge – the KSE – became a reality,
where knowledge is traded in nearly all its different
forms. It was taken as the symbol for Europe as a
social market with equal chances for everybody to be
included in economic and social life. Of course since
KSE’s start in 2015, the assessments concerning the
quantity and quality of weaknesses and strengths,
risks and potentials, deficits and perspectives,
‘Is this still an open question?’ asked the board
member from the ‘Individual Inventors association’.
‘I am not sure, but the coincidence between our
pragmatic institution’s origin and the fundamental
discussion is still an interesting phenomenon’,
answered the representative from the ‘European
Association of Consumer Innovators Groups’. ‘Lets
arrange some snapshot news in the brochure about
these weeks of our fifth birthday which shed a light
on this big question. Perhaps this is more innovative
than repeating again what we do, and how we
work, things you can easily find on our well-made
homepage’, the business research representative in
the board proposed. ‘I think an illustrative example
is when the emerging community of DNA-computer
users began to trade at the KSE. They create
crucial knowledge in the IT business which has led
to substantial innovations concerning efficiency,
resource and energy sustainability and security. Also
the social acceptance of DNA computers has grown
rapidly since the community of DNA-computer users
gained influence through their knowledge input to
industry, and they have even become economically
successful by trading their knowledge.’
‘This is indeed a typical KSE-case’, the EUResearch representative joined in. ‘But also in the
more classical research, the time was ripe for the
permanent blurring of frontiers. The virtual research
centre for DNA-IT-Studies (RCD), for example,
equally financed by EU and seven national usercommunities, is also celebrating its fifth anniversary
in 2015. Nowadays it’s a profit-making institutional
arrangement, selling its results to European ITcompetence industry networks. Nearly the same
figures have been reached by the Intelligent Design
Research Centre (IDRC), a joint venture of several
Mediterranean spiritual movements, the European
Animal Protection League and some transatlantic
entertainment companies. IDRC is a relevant
intermediary player between different business
sectors and consumers with a high affinity for
conservative religious values.’
‘Well, civil society really entered science and
education’, added a member. ‘Now we are at the
crossroads of civil society, or is it the public sector
which is in self-transformation? As you all know,
the tradition of Friends of the Earth professorships
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Civil Society
Pure public financing, managing and marketing
of research have decreased in relation to the
engagement of business, consumers, network
alliances and foundations. But shorter product
and production cycles, in combination with the
need for other types of innovation knowledge
besides pure academic research, led to a variety of
outsourcing strategies on the business side, raising
‘innovation research activities’ and its funding by
consumers, stakeholder groups and others. ‘Think
tanks’ in the late 20th century sense do not exist
any more, as knowledge production takes place in
very different locations – and not in single ‘tanks’
anymore. Knowledge production is organised as a
mix of different types of knowledge far beyond pure
academic ‘thinking’.
did not differ substantially. In this context several
politicians, scientists, media representatives and
other voices asked whether October 2015 could not
be seen as the end of the concept and phenomenon
of civil society as a distinct player in knowledge
production and society as a whole.
W o rk i ng
Public and private actors are both involved in the
knowledge economy as a core production area, at
an individual, local, regional, national and European
level. All the different kinds of social actors try
to be part of knowledge production as the main
source of economic, social and political inclusion,
of individual and cultural identity. As a consequence
the knowledge economy produces and depends on a
hybrid governance structure to manage this system.
The Future of Key Research Actors in the European Research Area
at European universities with more than 10 000
students will be picked up by ‘Demographic Turn’,
the umbrella foundation of all European Youth and
Seniors movements and institutions. The budget
to finance around 70 teacher positions (including
doctoral fellowships, innovation transfer centres,
etc.) will be sourced from knowledge rents which the
members of Demographic Turn gain at the market.
They sell their knowledge, for example as senior
consumers to companies which produce avatars and
robots in private households and hospitals.’
24
‘Referring to the European administrative level,
I would rather put it as the challenge of radical
self-reflection than the accomplished fact of selftransformation’, responded the EU delegate. ‘The EU
knowledge commissioner team, with its five present
members, welcomed in their last EU citizen newsemail the contribution of civil institutions, groups,
movements and individuals to research, innovation
and human-capital building. They mentioned that
the European Innovation and Research Council will
drop the internal distribution of the 27 seats (one
third science, one third policy, one third civil society
representatives), seeing as all actual and potential
members are active in civil engagement and political
or scientific engagement. The commissioners
criticised the trend that sees a growing majority of
the council having close relationships with huge
foundation trusts like the ‘Demographic Turn’.
‘The virtual anniversary booklet seems to be
complete’, the boards chairman tried to conclude
after this brainstorming. ‘Let me only add a news
link between the market and the governance
spots you mentioned: just two days ago, the ITpolicy panel of Eastern/South-Eastern Europe
questions, in its guideline on the IT future, the DNAIT strategy in the European knowledge roadmap
which the EU Commission has to sign next week.
The panel members underlined in their TV spot on
the European Innovation Channel that the siliciummix technology path fits much better with normal
users interests in most European countries, as well
as the emerging eastern markets for new hardwaredesigns outside China and India, than DNA-based
technologies. Within the panels, members of the
eastern consumer community of business and
private computer users announced they would
stop all knowledge transfer activities related to
industries, in order to put the Council, Commission
and EU Parliament under pressure. Implicit
knowledge, like safety expectations and treatment
by users, adaptability to existing old pure siliciumbased hardware configurations, and consumers’
information and communications culture in Soviet
and post-Soviet markets is crucial in order to
compete with Chinese suppliers. As a consequence
the stock exchange rates of important IT suppliers
went down immediately at fairly significant rates.’
5.3 Scenario III:
Politically-powerful civil society
Basic developments and drivers:
• Civil society is highly influential on the political
sector, including the research agenda, with highly
elaborated programmes for public involvement in
place.
• Different areas of knowledge production are
sometimes cooperating, but often they are not
integrated, and they sometimes even turn into
controversy.
• Trust, values and ethical questions play a crucial
role, therefore the prevailing distrust between
the economic-political elite and civil society is a
substantial obstacle for innovation and wealth.
The basis for today’s political work was laid at
the turn of the century: The thorough discussion
about the role of civil society participation in EU
research policymaking has had concrete results. In
spring 2020, key representative of civil society and
policymakers celebrated the ten-year anniversary
of the ‘Potsdam Convention on civil society
participation in research policymaking’. In recent
years no European policy decision was made without
discussing it with the civil society. More than that:
ethics and values have became crucial and widely
accepted resources of the knowledge economy. The
research agenda is thus set primarily by civil society.
The first European citizen conferences in 2006
marked the beginning of this development, whose
starting point was the insight of the relevance of
diverse knowledge. Decision makers as well as
knowledge producers have clearly seen the potential
of cultural and societal diversity for agenda setting
in research policy, for the research work itself as
well as for the implementation of research results.
The experience has shown that diversity pushes the
generation of new innovative ideas as well as open
new perspectives.
Beyond this another aspect has strengthen the role
of civil society: the crisis of confidence of the EU and
science at the end of the 20th and beginning of the 21st
centuries. Against this background, the conclusion
was reached that both the European process and
scientific development can only succeed if fully
There are highly elaborated programmes for
public involvement in place: policy panels consult
parliamentary fora and single members of parliament,
online platforms are a major source of public
opinion building and consultation. People generally
feel that politics has become more informed, that
the process of decision-making has become more
transparent and – as one major newspaper put it –
‘simply more just and sustainable’. Conversely, the
self-conception or self-image of citizens strongly
depends on the degree of participation in decisionmaking and agenda-setting. especially in the area
of knowledge production. In these cases, people
see their function or their role of participation at
least as a consulting one if not as a deciding one.
Most European people are engaged in different civil
society groups and use the various possibilities of
participation: from Citizen Committees, Juries and
Conferences via Knowledge Mappings and Commons
Café, which all have a consulting or contributing role,
up to Mediation and Referendums with a planning,
or arbitrating and deciding, function.
Recently, after a mediation process about a two-year
research project on brain enhancing medicine, the
research field has been banned from the EU. The
process brought forward interesting and complex
questions about the changing human self-image
and personal identity. But as a spokesperson from
Despite clear successes that show the ‘European
culture’ has become a positive USP in research as
responsible and sustainable research, the public
still questions the politicians: ‘why is it that industry
still does the kind of research we don’t want?’. The
special challenge for civil society is to mobilise
various interests since political engagement is still
a complimentary work. But compared with other
regions of the earth, Europe lives in great stability:
People by and large see their interests respected
and every person can indicate in a concrete way, he
has his own voice in the political discourse. Other
societies are often on the brink of a ‘revolution’
against the scientists who challenge the traditional
certainties about who we as human beings are.
Some researchers in the history of science have
indicated a deep change in the concept of ‘truth’.
No longer is this purely a question about a scientific
system. Society itself defines in many cases what
is true. Thus, some risks, that scientist would not
have accepted as being relevant according to their
scientific system, today are among the reasons to
take issues off the agenda. Protagonists judge this
as an important step toward the most competitive
knowledge society: nowhere else is ‘knowledge’
understood and used in such a broad sense.
Knowledge is scientific knowledge but also the
day-to-day knowledge of the average ‘pizza-shopmanager’ next door. Apart from the economic point
of view, people appreciate this attitude, because
Europe shows how the ‘battle against Google’ as
the only major source of orientation in the global
knowledge society can be won.
The approaching ten-year Potsdam anniversary has
sparked a discussion among press commentators.
They raise critical questions about the future stability
of the system: will it be possible to keep a system of
parallel research worlds – i.e. the European and the
Japanese – running over a long period of time? Or
will they eventually end up in a destructive conflict
based on their very different value bases? And
25
Paper 1
Civil Society
Looking back, it is that which has changed: Decisions
in the elected parliaments and the EU Commission
are just the very final step in the processes of policymaking. Administrative bodies and parliaments
discuss the issues at stake intensively with civil
society before reaching a decision. This has been
called the process of qualification of policy-making.
Very unlike the early forms of participation, today
the civil society protagonists are highly professional
spokespersons who are obliged to follow a clear set
of standards and rules (‘code of conduct’). This has
also promoted a high professional standard in society
regarding the ways and means of participation. This
is without discussion a major success factor of a
European knowledge society.
industry commented, ‘from the economic point
of view, this is very unfortunate for the European
research landscape. Research will be done in Japan.
But ironically the products will be mainly sold in
Europe.’ Clearly enough, Europe has lost in research
areas such as these, but in others – there have been
major successes in water-technologies – Europe is
a worldwide leader. In 2020 the research budgets
are predominantly driven by the EU. The national
budgets are marginal. However, only one fifth of the
total R&D budget is public. It is the private economy
that sets and drives the research agenda.
W o rk i ng
accepted by European citizens. And this acceptance
– according to mainstream opinion – could only
be created by a higher degree of participation. For
sure, not all politicians are happy about the fact that
trusts, foundations, churches or NGOs’ – many of
which are lobby groups of very specific interests –
in some cases have more influence on the research
agenda than elected bodies. But nobody would
contradict the relevance of diverse knowledge forms
and the new production of knowledge.
The Future of Key Research Actors in the European Research Area
another issue: will people accept that, despite the
fact that they participate politically, the majority of
research follows the rules and objectives of private
companies – with no societal participation at all?
Will people accept this only because they hope that
in the long run the European research-USP will be
the better and more successful one?
6. Impact analysis of
scenarios on ERA
and the European
Knowledge Society
• cohesion vs. fragmentation of the European
geopolitical space (regional cohesion);
The fading away of civil society in the knowledge
market of scenario II goes with a strong, but purely
economic basis for regional cohesion. To use this
potential, the degree of economic, technical and
social self organisation of the European societies
is decisive. There is a broad scope for incentives
and opportunities for transactions with cohesive
effects, but this economic kind of cohesion has to
be characterised as temporary, highly flexible, and
often varying. Scenario I is close to scenario II, but
the non-economic aspects of civil societies’ role in
research policy and knowledge production also
implies impacts which have been formulated for
scenario III above.
• cohesion vs. fragmentation of the European social
space (social cohesion);
Cohesion vs. fragmentation of the European
social space (social cohesion)
• global competitiveness of Europe in research,
innovation and economy; and
The general remark on the degree of cohesive
impacts of research and innovation policy is valid
not only for the regional and political dimension,
but also for social cohesion (seen as the quality of
relationships between social actor groups, classes,
individuals or other socially-defined elements of
society). A second general remark has to state that
the knowledge-production sector is the core of
individual and collective wealth, but a certain part of
society bears the risk of being excluded from it due
to the specific intellectual and social requirements
needed to access knowledge work.
This final chapter looks back at the scenarios from a
policy goals’ perspective and gives a first assessment
of the possible impact of each of the three scenarios.
Attention will be paid to the effects of the different
scenarios regarding:
26
and innovation policy is not likely to have significant
effects on regional cohesion compared to other
policy fields. Common concerns or expectations
across nations referring to specific research issues,
even if they have substantial effects on European
research strategies, will most probably have no
bigger regional cohesive effects in the political,
social and economic dimension. On the other hand,
the increasing scope and influence of participation in
Europe on the local, regional, national and European
level could lead to cohesive effects despite physical
distances and political differences.
• investments in R&D and their impact.
Cohesion vs. fragmentation of the European
geopolitical space (regional cohesion)
Generally the influence of civil societies’ role in
research on regional cohesion among the member
states and regions is rather little. The historicallyand functionally-caused differences in the innovation
and research systems, and in their quantitative
and qualitative dimensions, remain a challenge
to all cohesion efforts within the EU. But with the
increasing importance of knowledge production,
innovation and research in each of the member
states and the EU, the potential for cohesive effects
of this policy field is growing (see also chapter 4).
The relatively strong role of civil society in
scenario III is based on and oriented towards the
political sphere. In the context of the intrinsic
regional and national differences of political values
and structures, civil societies’ strong role in research
Nevertheless the extensive and intensive integration
of social actors into innovation processes in scenario I
and also scenario II have a high potential for social
cohesive effects. The risk of social polarisation and
conflict on the other hand is likely to be greater
in scenario II with its clear dominance of market
mechanisms in all sectors of knowledge production.
The multiple roles which knowledge actors can take
over at the stock exchange, for example, do produce
lots of new relationships, but they also produce
tensions. Whether social cohesion is realised
depends on successful mechanisms of political
Both scenarios I and II open the window for a
competitive Europe not only within Europe but also in
the world. This depends of course on social, political
and technological developments within Europe and
worldwide which support the envisioned knowledge
production system and its environment. The security
problem for example is one of the crucial challenges
for open knowledge societies as they are described
in scenario I and II – in its social, economic, legal
and technical dimensions as well as on a local and
on an international level. A strong global framework
of sustainability and democracy would for example
help to build a system and development path of
knowledge production as described in scenario III
with global leadership in several fields of innovation,
technology and economy. This global leadership
would be based on a societal and political system
which derives its stability from a well-working
interaction with civil society.
The scenarios also give a picture of the effectiveness
of policymaking procedures. The situation described
in scenario I would allow quick procedures.
However, these would be restricted in outreach, in
the possible spectrum of issues that could really
be dealt with: Many topics are under the ‘control’
of large companies. Politics or civil society would
not be allowed to take up these issues. Similarly,
scenario II would allow for effective policymaking.
But again, the general political discourse and
politics may not be able to address issues outside
the mainstream economic agenda. In this case
however, there would not be much frustration
about this, since civil society is very much part of a
new system of knowledge production and benefits
clearly from this system. This positive feeling would
also be true for scenario III. This scenario would
allow for very effective policy procedures in terms
of implementation, since the commitment of voters
is high. However, politics needs time to come up
with decisions based on sound deliberative and
Investments in R&D and their impact
Generally in all three scenarios the boundaries of
budgetary concepts like ‘R&D-Investment’ are blurred
– the definitions of ‘research’ and ‘development’ are
broadening as ‘knowledge’ generally encompasses a
huge variety of new dimensions. As a consequence,
‘investments’ in knowledge production lose their
distinct meaning and statistically clear-cut shape.
Human resources, in a broad sense, and social
capital components have to be integrated into the
notion of ‘R&D-investments’, if capital growth is to
be estimated.
In scenario I, several actors will promote several new
strategies to invest in knowledge capital stock with
the consequence of increasing (reformulated) R&D
investment figures. But several players like private
households will have problems with accumulating
knowledge capital in a significant and economically
sustainable way. But even relatively small
investments in this sector concerning knowledge
production in specific open innovation settings could
be very efficient and effective. And due to learningby-doing effects, the decentralised, diversified and
innovative forms of those investments may produce
high-impact synergies impact in the long run. The
idea of an efficient allocation and accumulation of
knowledge capital for all members in society shapes
the institutional setting of scenario II – assuming free
access to the market, well-functioning intellectual
property mechanisms and a high degree of market
competence and entrepreneurship in society. With
the wide range of opportunities to capitalise on
knowledge in nearly all its forms, this could lead to
tremendous investments in R&D which again have
highly productive effects. But market failures could
also diminish the effectiveness and sustainability
of the unique dynamic and diversity of knowledge
investments in scenario II. In contrast, scenario III
implies that the number and outreach of consensual
research and innovation paths is clearly restricted
by a strong civil society. On the other hand these
investments may be relatively efficient ones, due to
the fact that their social and political implementation
is guaranteed.
27
Paper 1
Civil Society
Global competitiveness of Europe in research,
innovation and economy
participative procedures (although these may not
take much longer than traditional policy-making
does today).
W o rk i ng
integration besides the economic ones. Scenario III
implies significant social capital investments on the
local, regional, national and European level through
appropriate, holistic and powerful participative
structures. But with the strong political framework
of this future world of research and knowledge
production conflicts will increasingly appear – due
to different values, cultures and systems within civil
society and due to the partially antagonistic interests
of civil society, on the one side, and of researchers,
innovators and industry on the other.
The Future of Key Research Actors in the European Research Area
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36
2
W o r k in g
Paper
Researchers (Part 1)
Andrea Bonaccorsi, University of Pisa
T
his document discusses the future of the
research community – the supply side of the
European Research Area.
The discussion does not extensively cover all
issues related to the governance and activity of
researchers, but focuses on a few urgent problems.
The selection has been driven by a sense of urgency
in Member States and EU policy making, faced with
increased competition at the world level in science
and technology, and the difficulties of meeting the
Lisbon objectives.
We will focus on the following issues:
• preparing for the future: the international mobility
of undergraduate students;
• the competition for talent: doctoral education – a
global perspective;
• the exploration machinery: post-doc positions
and the dynamics of science;
• the ageing of researchers;
• a radical interpretation and a proposal.
2. Preparing for
the future: the
international mobility of
undergraduate students
The internationalisation of higher education and
postgraduate studies is key to their quality and
dynamism. The future of researchers in the ERA is
rooted in the current situation of undergraduate and
postgraduate students on a global basis.
Indeed, the key point to consider is the evolution
of the research capabilities of the European Area
within the scenario of increased competition from
Asian countries.
Let us review the evidence,
undergraduate students.
starting
with
An increasing number of students worldwide choose
to undertake their university studies abroad. The
analysis of these flows is revealing.
It appears that the total number of foreign students
attending universities is larger in Europe than in the
US. However, the composition in terms of countries
of origin is profoundly different (DG Research, Key
figures 2003-2004).
Table 1
Foreign students in selected countries and
most common countries of origin. Year 2001
Country or
region
EU-15
Total number of Top ten countries or regions of
foreign students origin
795 436
Greece, France, Germany, Italy,
Spain, Portugal, Ireland, UK,
Austria, Bulgaria
US
582 996
India, China, Korea, Japan, Taiwan,
Canada, Mexico, Turkey, Indonesia,
Thailand
UK
225 722
Asia, Greece, North America,
Africa, Germany, France, Ireland,
USA, China, Malaysia
Germany
199 132
Asia, Turkey, Africa, Portugal,
China, Greece, Italy, Russia,
Austria, France
France
147 402
Africa, Marocco, Asia, Algeria,
Niger, Germany, North America,
Somalia, South America, Spain
Japan
63 637
Asia, China, Korea, Europe,
Malaysia, North America,
Indonesia, Thailand, USA, South
America
Source: DG Research.
Data: Eurostat NewCronos Database; USA: Institute for International
Education (IIE).
Most of the international mobility in Europe is,
in fact, intra-European mobility or post-colonial
mobility. In fact, the most important countries
of origin are, on one hand, Greece, France,
Germany and Italy, and on the other hand those
countries with links to the country of destination
stemming from a common colonial history. The
37
Wo rki ng Paper 2
Researchers (Part 1)
1. Introduction
The Future of Key Research Actors in the European Research Area
inflow of foreign students in France comes mainly
from Maghrebin countries (Morocco, Algeria,
other African countries), in the United Kingdom
from Commonwealth countries (India), in the
Netherlands from Caribbean Islands, and in Spain
from South American countries (DG Research, Key
figures 2003-2004).
Quite the contrary is true for the US system, which
mainly attracts students from Asian countries:
more than 60 000 from India and China each,
around 50 000 from Korea and Japan, 30 000 from
Taiwan, and more than 10 000 from Thailand,
Indonesia and Turkey.
While there is something natural in this pattern of
immigration, there are also elements that require
careful discussion.
38
Models of migration are based on the notion of a
balance between pull and push factors. Pull factors
refer to the attractiveness of the foreign country
in terms of expected income, work conditions
and cultural differences with respect to the home
country. Push factors describe the pressure from
the home country in terms of low income, high
unemployment, lack of protection of human rights,
etc. Individuals decide to migrate when the expected
costs of moving to a foreign country and living in an
unknown environment are offset by the improvement
in income and other valued items. Among other
factors, the existence of a common language or
common cultural heritage may reinforce the decision
to migrate.
We suggest that similar elements determine the
decisions of students and their families to study
abroad. Although this is not necessarily a permanent
migration, push and pull factors clearly are at stake.
whose languages do not have such global diffusion,
such as Germany and Italy. In these countries the
proportion of foreign students is very limited.
Furthermore, European universities are missing out
on the group of foreign students with the highest
rate of growth, i.e. those from the Far East. In
countries such as South Korea, China, or India the
number of students deciding to attend universities
abroad has been increasing steadily in the last 15
years. Unfortunately, most of it is directed towards
US universities, not European.
It is important to pay attention to the sociological
and cultural context of this migration of Asian
students to US universities. The level of motivation
of these students is impressive. The sacrifices that
their families are prepared to make for the education
of their children are huge, and the traditional
Western attitude towards schooling and education
is nothing in comparison to this level of financial and
emotional investment. An extract from a magazine
article (Box 1) illustrates this idea. These elements
are important, because they are an indicator of the
expected outcome that these families hope to draw
from the investment.
According to UNESCO the number of Korean
students studying abroad rose from 110 000 in 1999
to 174 000 in 2002.
Students attend high school in the US in order to
learn English and have a better chance of being
admitted to US universities.
Chung Gi Sup is a 45 year old professor, living alone
in Seoul because his wife and two daughters are
in New Jersey to attend high school. The mother
works hard in order to pay for the school and to
save money for university. The father sends almost
80 per cent of his USD 40 000 salary to New Jersey.
Chung is part of a fast-growing group: men who
accept to live in isolation in order to enable their
children to be educated in an English speaking
country.
Now, the fact that a significant part of Europe’s
attractiveness to foreign students is related to the
benefits coming from its colonial past is noteworthy.
What would the attractiveness of European
universities be if the colonial past were not at stake?
How attractive would they be if foreign students
had to learn a new language, instead of enjoying
the same language of the host European countries,
taking into account the fact that French is taught
in schools in North African countries, Spanish
is the official language of many South American
countries, and English is the second language of all
Commonwealth countries?
Therefore the future for European researchers is one
in which they will have to compete with younger
colleagues, well prepared, highly internationalised,
and tremendously motivated to succeed.
Some comparisons can be made by looking at
countries that do not have a strong colonial past and
European junior researchers have to decide whether
to start their career early or later, stay at home or
These men are called father geese, after the birds
devoted to raising children.
Adapted from Newsweek, September 15, 2003
There are several factors that make research careers
attractive: the prestige of science, the expected
income, and the intrinsic satisfaction in doing
research.
We now draw attention to the single-most important
factor in our opinion: the level of competition,
or the transparency and fluidity through which
research positions are offered and allocated in
the institutional system. We propose that the
attractiveness of European science and the ability
to transform the large doctoral education stock into
effective careers firmly depends on the credibility
of the long term prospects offered by national
governments and the EU, for which transparent
criteria and a system based exclusively on scientific
merit are essential.
If this does not materialise, then the best European
talents will be attracted to other countries (in the
past up to the present day, mainly to the US, and
in the future increasingly to Asian countries) and
the best Asian talents will not flow to Europe
but will continue to contribute their tremendous
intellectual and motivational energy to the
American system.
3. The competition
for talent: doctoral
education – a global
perspective
The problem of the so called brain drain has
repeatedly been discussed in European countries
and at the EU level in recent years. This is not a new
issue, but it is made more salient by the need to
employ a large number of researchers following the
Lisbon strategy.
Let us summarise the key elements of this problem.
The performance of Europe in terms of the number
of PhD students is satisfactory (DG Research, Key
figures 2003-2004).
The EU-15 had 0.55 new PhDs in S&E per 1 000
population aged 25-34 in 2001, compared with 0.41
in the US and 0.27 in Japan.
The most active European countries are Sweden
(1.37), Switzerland (1.11), Finland (1.01) and Germany
(0.80). The average for the EU-25 is only slightly less
at 0.49, as some accession countries perform better
than some European countries (for example, Slovenia
has 0.45 PhDs in S&E per 1 000 population, Czech
Republic has 0.35 and Slovakia has 0.30, significantly
better than Spain, Portugal, Greece and Italy).
In terms of dynamics, a steady increase in the number
of PhDs in all fields took place between the mid-1980s
and the mid-1990s in the largest OECD countries
(National Science Foundation, S&E Indicators, 2004).
In general, this massive growth has been followed by
a period of slow growth or even decrease.
The largest European countries have a different
pattern. In the UK, the period of maximum growth
was between 1995 and 2004, in France there was
a steady increase in the 1986-1994 period, while in
Germany the growth has been more linear over the
last 30 years. In terms of annual production of PhDs,
Europe is in a leading position. Some European
countries, such as the UK, Finland and Sweden,
have a greater number of PhD students than United
States, with respect to the population.
This should enable a steady flow of researchers to
both private industry and public sector research. In
practice, however, this does not work so smoothly.
In order to understand why let us review the relevant
issues, starting with international mobility of PhDs.
Table 2
Production of PhD students in selected OECD
countries
Country
PhD graduates
Per million inhabitants
Switzerland
2 733
380
Finland
1 891
365
Sweden
3 049
344
Austria
1790
221
United Kingdom
11 568
194
Australia
3 687
191
EU-15
70 175
185
United States
44 808
163
Portugal
1 586
158
Spain
6 007
150
Norway
658
147
OECD
147 575
131
South Korea
6 143
131
Canada
3 978
129
Belgium
1 147
112
Czech Republic
895
87
Italy
3 557
62
Source: OECD Education Statistics; OECD MSTI Database, 2002.
Number
39
Wo rki ng Paper 2
Researchers (Part 1)
spend long periods abroad, and make an investment
both in terms of time and motivation. Of course, their
choice is the choice of Member State governments
and the EU. In the long term the motivation of
junior people to undertake a career in research is
fundamental.
The Future of Key Research Actors in the European Research Area
For these students the quality of the receiving
universities is the crucial factor in the decision to
study abroad. Linguistic similarities should not play
a decisive role, if foreign languages are taught at the
university.
only 20.8 per cent in France, 9.3 per cent in Germany,
and lower still in Spain and Italy. In addition, French
doctoral students come mainly from Africa (40 per
cent in 1999), with Algeria, Morocco and Tunisia at
25 per cent.
Existing data suggest that the level of attractiveness
of European universities at the doctoral level is
disappointingly low.
It is clear that the linguistic advantage of the UK
can explain part of the difference. But this is not
the whole story. Continental Europe is not attractive
enough to offset linguistic differences.
Table 3
Share of foreign PhD students
40
Percentage of foreign PhD
students
Switzerland
37
Belgium
36
United Kingdom
34
US
27
Australia
21
Canada
17
Norway
15
OECD
15
Sweden
14
Austria
14
Spain
12
EU-15
11
Finland
6
Portugal
6
Czech Republic
6
Italy
1
South Korea
1
Source: OECD Education Statistics; OECD MSTI Database, 2002.
Apart from two small countries (Switzerland and
Belgium) and a large colonial country (UK), most
European countries do not perform very well in
attracting PhD students.
A breakdown of data for the largest countries is
available in Table 4, based on the compilation by
Moguèrou (2005).
Table 4
Doctoral Science & Engineering degrees
earned by foreign students in 2001 (%)
Area
Natural sciences
Mathematics and
computer science
Engineering
Social sciences
Total S&E
France (*)
16.5
Germany
8.6
UK
25.6
US
34.2
28.7
9.3
43.5
49.1
22.0
23.3
20.8
10.7
4.8
9.3
51.2
48.0
36.9
55.8
20.9
36.3
Source: selected harmonised data from Science & Engineering Indicators
2004, in Moguèrou (2005).
(*) Data refer to 1999.
Natural sciences: physical, biological, earth, atmospheric, ocean sciences.
It appears that only the UK has a university system
that systematically attracts students from abroad.
While in the UK more than one third of doctoral
degrees are earned by foreign students, the figure is
If the Lisbon Strategy includes making Europe the
most attractive area for the knowledge economy,
there is still an extremely long way to go.
In the US the number of doctoral degrees earned
by foreign students increased by 7.8 per cent each
year in the period 1986-1996, while the number
of domestic degrees increased by only 2 per cent
(National Science Board, 2000; 2002). Again, Asian
countries are the most common countries of origin
of foreign students earning doctoral degrees in the
US. Between 1985-2000, China sent 27 000 doctoral
students to US universities, Taiwan 15 000, India
13 000 and South Korea 13 000. In total, students
from Asian countries earned 69 000 US doctorates,
compared to 16 000 EU and Eastern European
countries doctorates (National Science Board,
2004).
The exploration machinery: post-doc positions and
the dynamics of science
Another attractive aspect of the US system is its
large post-doc market. According to the careful
reconstruction of Moguérou (2005), the total number
of post-doc positions in the US was more than
50 000 in 2001. It is impressive to observe that the
proportion of post-doc positions occupied by foreign
PhD students has steadily increased. According to
the detailed data of the National Science Foundation
(WebCASPAR Database System), the number of postdoc positions was less than 20 000 in 1977, of which
13 000 were assigned to US citizens and permanent
residents, and around 6 000 to foreign temporary
residents. In the period 1977-2001 the number of
American post-docs increased up to 19 000, but the
number of foreign post-docs peaked at 25 000 in
2001. This impressive growth is mostly concentrated
in life sciences. In 2001 the NSF recorded 17 072
positions in life sciences for foreign people (74 per
cent of the total) and just 13 579 for US citizens.
Interestingly, a good proportion of foreign postdoc positions are held by European PhD students.
In Germany 66.3 per cent of post-doctorates are
These migration flows have two important
characteristics. Firstly, once European PhD students
have experienced the US system, they often do not
plan to return. According to an EU source ‘about 75
per cent of EU-born US doctorate recipients who
graduated between 1991 and 2000 had no specific
plans to return to the EU, and more and more are
choosing to stay in the United States’ (EC Press
Release, Ref.IP/03/1594, dated November 25,
2003). Surveys conducted in several countries
underline that the main motivation for staying
abroad is not relative income, but the quality of the
research environment, the availability of research
infrastructure and the absence of nepotism in career
decisions. Secondly, there is preliminary evidence
that PhD students who go to the US have better
productivity than those who stay at home (Moguèrou
2004; Commander et al., 2003).
4. The ageing of
researchers
The problem of age is becoming critical in science
policy given the alarming evidence of the increasing
average age of researchers in most European
countries. For example, in Italy the proportion of
professors and researchers aged 24-44 was 60 per
cent in 1984 and only 29 per cent in 2001. Those
that entered the academic system who were aged
between 24-34 were 19 per cent of the total in 1984
and only 5 per cent in 2001 (Avveduto, 2002).
The age composition of the population of
researchers is a critical indicator. Average age
increases for natural reasons and in proportion to
the demography of the population. The turnover
ratio measures the intensity of change in the
population, placing the sum of entry and exit in one
year in comparison to the stock at the beginning
of the year. If we observe an ageing population, it
may simply be the effect of time. Each time an old
researcher retires, resigns, or dies, the average age
shall decrease, and each time a junior researcher
is hired, the average age again decreases. The only
way for the population of researchers to keep the
average age under control is to maintain a steady
and smooth turnover over the years.
The ageing of researcher population is a source of
concern for several reasons.
First, the theory of the scientist life-cycle posits that
scientific productivity follows a life-cycle pattern,
and eventually declines at the end of the scientific
career. This life-cycle effect was found by Levin and
Stephan (1991) to be true for most scientific areas
with the exception of particle physics (see also
Stephan, 1996).
The decline of scientific productivity with age may
depend on a variety of factors.
Firstly, as time goes by the initial differences among
scientists in individual productivity get larger. Most
theories of scientific productivity postulate a stochastic
and cumulative mechanism (Simon, 1957) or a
Matthew effect (Merton, 1968), whereby those that
gain recognition initially in their careers receive reward
and resources, which will be used to carry out further
research. If this is true, initial differences in individual
productivity will tend to become larger over time.
Allison and Stewart (1974) found that the Gini index for
publications and citations of scientists monotonically
increases over time in a series of cohorts from the
date of the PhD, with the exception of biologists. This
evidence is interpreted as strongly supporting the
notion of reinforcement or positive feedback.
Another way of looking at the problem of age is to
model productivity as the outcome of a number of
features that interact multiplicatively, rather than
additively. For example a model may assume that
several elements or mental factors play a role (e.g.
technical ability, finding important problems, and
persistence). As occurs in any multiplicative model,
the distribution of productivity is more skewed
than the distribution of any of its determinants. As
a result, a cohort of scientists starting with a given
distribution will end up with a more dispersed
distribution and the variance will increase over time.
In addition, it is plausible that scientists work on
research not only for the sake of intrinsic pleasure of
scientific puzzle solving, but also in the expectation
of receiving future income. If this investment
motivation is correct, it is inevitable, as in any
theory of human capital accumulation with finite
horizon, that the level of investment will decrease as
scientists approach the date of retirement. Models
of human capital are central to the life cycle of
scientists theory.
This theory has been empirically validated in most
disciplines, perhaps with the exception of particle
41
Wo rki ng Paper 2
Researchers (Part 1)
located in the US (Enders and Mugubushaka, 2004),
while in France around 30 per cent of individuals
undertaking post-doctorate study have chosen to
cross the Atlantic (Moguèrou, 2004).
The Future of Key Research Actors in the European Research Area
physics. This theory applies to individual scientists,
while nothing is said with respect to the age
composition of institutions.
Secondly, we have found that institutions
characterised by higher average age are less
productive (Bonaccorsi and Daraio, 2003; Hall,
Mairesse and Turner, 2005). Institutions of this kind
are not attractive for talented junior researchers.
The old age of the researchers is a signal of bad
quality, either because it means that few junior
people entered the institution recently, or because
it inevitably leads to a management style oriented
towards experience rather than creativity. It is
interesting to note that the large and successful
national European scientific institutions in high
energy physics have never endorsed a policy of
‘seniority’ in their top management positions, and
have instead systematically involved talented junior
researchers in their 30s at the board and decisionmaking level. This is important to create incentives
for junior people and to establish a culture of quality,
merit and competition.
42
Thirdly, an aged population of researchers is also
less mobile. This may lead to missing opportunities
in the world competition.
Finally, the consolidation of an old population of
researchers is a big policy issue because it inevitably
leads to large programmes for the recruitment of
researchers in a concentrated period. Faced with this
problem, there are suggestions that a massive effort
should be made by hiring waves of new researchers
in a concentrated period of time, in order to
drastically reduce the average age. The difficulties
associated with the Lisbon Agenda have something
to do with this issue.
But, while by definition the problem of ageing
worsens over time in the absence of hiring many
young researchers, it is not at all clear what the
schedule for hiring should be. As we have seen with
respect to the Italian CNR (Bonaccorsi and Daraio,
2003), when recruitment of researchers is waveform,
the structure of incentives is completely distorted.
Irregular and unpredictable waves of recruitment
create a queue of junior researchers that work under
short term contract conditions. It is likely that the
best junior researchers will be attracted by external
offers and do not have the patience to stay at home
waiting for a position. By the same token, it is
likely that those that stay in queue are not the best
available. In fact, when recruitment is performed
on a large scale and concentrated in a few years,
the rate of hiring may be larger than the rate of
supply of talented people, so that the recruitment
of people ranked low in terms of research quality
occurs. If high quality people did not ‘queue up’ but
decided to leave research, low quality people have
better opportunities to enter. Uncertainty over the
timing and volume of hiring may induce biases in the
planned investment in human capital.
There is another problem, however. Irregular waves of
recruitment always create situations of rent seeking.
Those that are close to political power and may have
influence on budget decisions will also try to gain
power in the recruitment process, either directly
or indirectly. Since there is no certainty on future
opportunities, when there are positions available
those that may exert power will try to promote
their students or research partners much before
their scientific maturity, or even without scientific
merits. The pressure of the institutional corruption
is such that personal integrity of scientists is not a
sufficient resistance. The carpe diem attitude will
inevitably prevail. And since agents try to anticipate
the behaviour of other agents, this system creates a
classical prisoner dilemma situation, with all agents
trying to take part in the game in order to safeguard
their position.
The only way to reduce this corruption is to build up
a steady and smooth demand for research positions,
on a long term basis, matching individual capabilities
with scientific opportunities.
5. A radical interpretation
and a proposal
How can the available evidence be interpreted? We
suggest a radical interpretation, based on an abstract
characterisation of higher education and research
systems as institutions (Bonaccorsi, 2005b).
Comparative institutional analysis of HE&R systems
is based on the way in which these systems perform
their general functions. In turn, functions are defined
not in static terms, but in a dynamic framework. In this
line, HE&R systems must have mechanisms for variety
generation, selection, and retention. The former
include the architecture of the research system and
the relations between higher education and research,
the higher education process, and doctoral education.
Mechanisms of selection include strategic planning,
project selection, project funding, career planning,
compensation, and the design of researchers’ jobs
and responsibilities. Retention mechanisms include
evaluation and monitoring, and quality signalling.
In Bonaccorsi (2005b) we provide a characterisation
of most national systems based on:
• the number of hierarchical levels in the
institutional architecture and the potential for
corruption and influence strategies;
We propose that this system enters into difficulties
when the rate of growth of scientific production
suddenly increases, and moreover when the number
of different, often incompatible, research directions
is such that senior scientists cannot control the
whole evolution of science. This is exactly what
occurred with the new leading sciences, or search
regimes characterised by rapid growth, divergent
search dynamics, and new forms of complementarity
(Bonaccorsi, 2005a).
• the degree of competition;
Based on these elements, we propose that most
systems in continental Europe are characterised by
a large potential for political influence, low levels of
competition and extremely low levels of diversity.
The empirical counterpart of this characterisation is
formed by continental Europe, i.e. Germany, France,
Italy and Spain among the largest countries. Despite
important differences between these systems we
propose that they share a few elements:
• there is a significant political role in resource
allocation at the level of Ministry of Research or
Education (as opposed to systems of professional
and peer-review based allocation of resources,
such as ESRC in the UK and Scandinavian
countries, or NSF and NIH in the US);
• rules for the cooptation of junior researchers are
scarcely competitive, being largely based on the
affiliation of students and PhD students to groups
or clans of academics;
• rules for career promotions allow significant room
for manoeuver;
• the funding structure is not based on a variety
of sources in a multi-layered system, but on a
limited range of alternatives;
• the extent of cooperation with the private sector
is limited.
At an abstract level, then, we may think of cooptative
rather than competitive systems. Continental
European systems have been tremendously
successful when the rate of change of scientific
knowledge was kept under control by senior
scientists. A hierarchical promotion system,
associated with high barriers to entry, can still be
scientifically productive if senior scientists can
anticipate the direction of research and allocate the
efforts of junior researchers accordingly.
Life sciences are the paradigm of this dramatic
change. Following the molecular biology revolution
and the invention of powerful experimental and
observational techniques (recombinant DNA,
polymerase chain reaction), the number of different
research directions exploded during the 1980s, and
still maintains a divergent and rapid dynamic. In
most fields, such as cancer, Alzheimer, Parkinson,
or HIV, the combination of molecular biology
explanations of causal mechanisms with the need
to explore several possible specific mechanisms of
the disease at protein and cellular level has led to a
massive proliferation of research programmes.
These characteristics are shared by other new
scientific fields, such as computer science, materials
science and nanotechnology.
We propose that the doctoral and post-doc systems
must be conceived of as powerful exploration machines
at low cost. Doctoral students learn the frontiers of the
discipline during their courses and master experimental
techniques through laboratory practice. They learn how
to do research and are pushed to produce creative and
original ideas for their thesis.
In a competitive system, students submit their
ideas to potential supervisors and fight each other
to capture the attention of the best academics.
In a cooptative system, very often professors
suggest ideas for a thesis to students, and become
entrenched in the research process so that they lose
their critical perspective.
Conversely, the doctoral period in competitive
systems maximises variety and risk-taking,
enhancing the exploration capability of the whole
system. The role of post-doc is fundamental here.
During their PhD students have learned how to do
research, but working in projects of others. In the
post-doc period they must demonstrate their ability
to run an experiment, organise junior research
assistants and students and apply for funding. The
post-doc is the first opportunity to test not only the
research capabilities, but also the organisational
43
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Researchers (Part 1)
• the level of diversity and variety.
The Future of Key Research Actors in the European Research Area
capabilities of junior people. Again, having a large
population of post-doc researchers allows the
possibility to explore a large variety of hypotheses
and sub-hypotheses, at reasonably low cost.
In the US system the autonomy of the post-doc, the
institutionally embedded rule that stresses the ability
to apply for funds at NIH and NSF, and the transparent
policy of federal agencies towards junior researchers,
are all elements that support exploration.
Why are competitive systems superior?
44
We propose that superiority is not absolute, but
contingent to the nature of the search regime. In
old sciences (physics, chemistry, mathematics)
European science was excellent, creating schools
based on affiliation but also on strong intellectual
challenge (think for example to the Copenhagen
school in physics). In areas characterised by strong
complementarities (e.g. high energy physics, space
sciences, nuclear research) European countries were
able to design dedicated institutions at national
and supra-national level that reduced the number
of levels of hierarchical decisions and facilitated
long term planning of investment into facilities and
specialised human capital.
But this picture does not hold any longer in
new leading sciences. In these fields cooptative
systems are inferior. The continuous generation
of hypotheses, under conditions of rapid growth
of knowledge and strong complementarities,
requires competition and decentralised funding.
A competitive system better matches exploration
opportunities with existing capabilities.
In essence, we believe that the problem of the
European higher education and research system is,
fundamentally, the lack of adequate competition.
Consider how the US doctoral system is described in
a recent informed account.
Doctoral education, particularly in the sciences, is perhaps
the most efficient competitive market in higher education.
Each winter a limited number of students with the requisite
qualifications apply to those science and engineering
departments that they would most like to attend and
that would be most likely to accept them. The applicants
are well informed about the training they seek, and they
are highly mobile as well. Each department is a small,
autonomous producer, and the departments in each
subject area collectively form a national market. Except for
pricing, doctoral education approaches the requirements
for perfect competition (Geiger, 2004, p. 163).
The virtue of competition is fundamentally rooted
in its cognitive power. Under conditions of radical
uncertainty, decentralised research is more effective
than central planning. The efforts of many, well
informed, agents, are more productive than a
coordinated and centralised research plan.
The existence of a clear ranking of institutions
helps the process of matching between students’
capabilities and supervisor attitudes.
The key feature of this market is that both applicants
and departments vary in quality in ways that are
fully understood by both parties: applicants and
departments can therefore be ranked according to
desirability. Thus, a dual competition takes placedepartments seek to attract the most preferred students
and students seek places at the most preferred
departments in their field. This situation produces a
queuing process of allocation. Top departments choose,
and are chosen by, the best students; departments in
the next tier do the same with the remaining students;
and so on down the list. However, this market is
highly competitive and the terms of competition fairly
delimited (ib. p. 163-4).
Finally, the same competitive mechanism is in place
in the funding of research. Competitive rules are
deeply internalised in the behaviour of all actors and
there is no latitude for trying to change them.
In this market, university scientists are the sellers of
research; outside funders are the purchasers. The
service for sale – research – is literally priced at cost.
The research market is beautifully efficient. It is
nationally integrated, with various units of the federal
government independently purchasing 60 per cent of
research. At the same time it is highly decentralised,
with no unit selling more than 2 per cent of the total.
There are few informational asymmetries. Buyers and
sellers know one another extremely well, exchanging
visits, attending the same meetings and cooperating
in evaluations. (...) Each of these arrangements
represents a different combination of buyer interests
and seller interests. By mutual adjustment these
complementary goals are fulfilled. At the end of the
day (the fiscal year) the market clears. The highest
quality and most apposite academic research is
supported by the funds available for these purposes
(ib. p. 164-5).
In European systems there is no such integration.
Funding is concentrated at national level, with few
alternative sources. The market for research funding
is not large, but national and small.
6. A proposal for a panEuropean market for
PhDs and post-doc
positions
The goal of a European Research Area is firmly rooted
in the recent history of the European Union. After this
notion was developed by the Research Commissioner
Antonio Ruberti in the 1980s, it became an official
strategic goal more than a decade later. It is currently
at the core of the of the EU’s strategy, as formulated
in the Lisbon document and the communications that
made this strategy operational. At the same time,
the idea of a European Research Area inspires the 6th
Framework Programme and the recent proposal for a
European Research Council.
Such a goal requires a huge effort from Member
States, however.
The unification of the research environment
cannot be pursued by way of harmonisation or
regulation. The issues at stake go directly into the
national historical tradition in terms of regulation
of personal rights, the work contractual framework,
social welfare, and the relation between public
officials and the State. Changing these aspects will
require decades, not years. We cannot afford this
perspective.
We need a complementary approach, one that is feasible
in a few years. It must be compatible with current legal
framework, but at the same time it must anticipate
future trends. It must be bottom up, and put pressure
on Member States to speed up the institutional changes
and legal reforms needed to build the ERA.
We propose to start an experiment of marketcreation at European level. Under the auspices
of the EC and with the support of large European
companies, a large job market for PhDs should
be organised annually, in a large European town.
Large companies would attend the job fair with
their recruitment staff and would run interviews
for candidates and examine CVs. Universities might
want to attend in order to identify candidates for
their post-doc positions. Governments and public
administrations might be interested in young
talented people.
What is the benefit of such a job market? First,
size matters. In large markets the supply profile
of candidates better matches with the demand
requirements. The expected income from a large
post-graduate job market will be higher than in a
small market. Specialists in niche disciplines or PhD
students that have pursued an original research
project might find potential partners and employers
more easily.
Second, young people would receive a clear, strong
and lasting message from European institutions that
they will visibly invest in their futures. This would
have an effect on the morale of students and would
encourage new candidates.
Third, the goal of European mobility of talent would
be greatly enhanced by such a large market. PhD
graduates would learn how great the opportunities are
in a unified market, and would consider the possibility
of working abroad as a normal career avenue. Beginning
to work abroad during the early stages of a career is a
powerful stimulus to mobility in the long term.
A pan-European job market would not require, in
its infant stage, any modification in Member States
regulatory framework. PhD graduates would receive
full information on the different contractual and
legal schemes available in different countries, as
well as social security and pension schemes, but
they would have to rely on existing norms.
In due time, however, a few normative
modifications might help to create a dense market
and to align the incentives of students, universities
and companies alike.
Member States should design a fiscal policy that
is favourable to employers when they hire a PhD
student, possibly with an incentive proportional to
the duration of the contract, for a limited period.
They might also introduce the notion of portability of
fiscal treatment across countries. When a company
hires a PhD benefits in its own country of a favourable
fiscal treatment, irrespective of the nationality of
the employee. This treatment is extended to all new
employers in all countries. Member States should
agree on compensating possible distortions that
may arise.
45
Wo rki ng Paper 2
Researchers (Part 1)
We now suggest a practical proposal, one that is
feasible in the short term and might give a clear signal
on the intention of the European Commission (EC) to
accelerate the pace towards the knowledge society.
The Future of Key Research Actors in the European Research Area
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The Future of Key Research Actors in the European Research Area
52
3
W o r k in g
Paper
Researchers (Part 2)
Andrea Bonaccorsi, University of Pisa
I
n considering the role of actors and the driving
forces for change we take a systemic view,
identifying the overall functions carried out by
the actors in the social system (Figure 1). We define
functions in abstract terms, as recurrent patterns
of behavior of a sub-system within the broader
social system. The functions of researchers in this
perspective are (a) to produce; (b) to circulate new
and valid knowledge. The implementation of these
functions requires that the political sub-system
provides researchers with legitimation and funding.
In turn, both the institutional/political system
and the researchers depend on social demand for
accountability and for relevance.
Each of these broad functions can be articulated in
several layers of sub-functions, increasing the level
of specification. In the following, we articulate these
functions in detail.
In doing this exercise we capitalise on several
scientific traditions in social science, namely
the institutionalist theory in general, and the
sociology of science and new economics of science
in particular.
We are aware that the notion of function may be
criticised on grounds of excessive determinism.
According to this criticism, actors cannot be
defined in terms of the functions they carry out
in society, following a principle of instrumental
reason, but rather are based on the capacity
to influence the goals of society by means of
expressive or generative rationality. We do not
exclude this possibility. A number of general
trends we have identified arise from the reflexive
activity of actors (sometimes a small minority of
them) that succeed in shaping social expectations
and changing the agenda. In our language, this
amounts to say that actors can generate new
functions for the social system. This is certainly
possible and is extremely important.
But this is also uncommon. Most of the activity
of social actors takes place within structural
constraints that limit strongly the degrees of
freedom. Institutionalisation always implies the
fulfillment of a number of socially defined functions,
first of all through the internalisation of professional
rules of conduct.
We propose that by focusing on structural
constraints and recurring patterns of activity
we are in a better position to identify and
interpret driving forces for change. One of the
main criticisms to the notion of function is that
it is inevitably conservative: each change in
society takes place only if it is functional to
some high level societal goal, which does not
change at all. We propose an opposite view,
which we may define as dynamic functionalism.
Functions are not static, but evolve over time
following an internal complex dynamics. New
functions are created within existing constraints,
and constraints are modified and overcome as
the result of reflexive activity. The dynamics of
functions is a structural one, because functions
must solve for higher level functions within
structural constraints. Thus focusing on abstract
functions of sub-systems in a society does not
mean to qualify for their inertia and stability,
but rather to identify the potential for structural
change. Dynamic functionalism may be a useful
conceptual tool for change.
Another possible criticism is that functions are
loosely defined. This is possibly true, but it reflects
the relative distrust in this perspective in social
sciences in the last 30 years or so, with the possible
53
Wo rki ng Paper 3
Researchers (Part 2)
1. The role of actors in the
knowledge production
and research system:
some methodological
remarks
The Future of Key Research Actors in the European Research Area
exception of Niklas Luhmann. In other scientific
fields, for example, this notion is currently reemerging, because it helps to explain the behavior
of complex systems, such as living systems in
evolutionary biology and development biology,
complex technical systems in engineering and
artificial intelligence, or the ontological nature of
artificial objects in applied ontology in philosophy.
Let us set aside these conceptual issues and
instead let us concentrate on key trends and drivers
for change in each function and sub-function.
• the Observatory on European University, a joint
researcher-practitioners exercise to develop new
indicators of research activity at the university
level;
• the AQUAMETH project, a project aimed at
integrating secondary micro-data at the level
of individual universities, already available for
six countries (Switzerland, Spain, Portugal,
Norway, Italy and the UK) and in progress for
the Netherlands, Hungary, France and (partially)
Germany;
Figure 1
A dynamic functional model of the changing
role of researchers in the social system
Institutional
system
Society
• the ENIP structural action (European Network
of Indicator Producers), which has produced a
number of country reports on the structure of
funding of research;
• a project carried out for the JRC IPTS (Seville) on
changes in the income structure of a sample of
universities in 10 European countries (CHINC).
Legitimation
Relevance
Funding
Accountability
Selection
54
Production of new
knowledge
Circulation of valid
knowledge
Researchers
2. Recent key trends
In a companion paper we presented some evidence
on key trends, focusing mainly on brain circulation
and the relative loss of attractiveness of the
European research environment.
We merge the analysis of recent key trends with the
discussion of each of the points below.
In developing this discussion we rely on a number of
recent reports from DG Research, various supporting
bodies, and the US National Academies of Sciences.
We also rely on a number of unpublished or
forthcoming results from various projects carried out
under the PRIME Network of Excellence, or under
various EU contracts. We refer in particular to:
3. Driving forces for
change and future
trends
3.1 Production of new knowledge
The first general function of researchers is to
produce new knowledge. This broad social
function creates a tension between internal
rules of knowledge production and the demand
for relevance and accountability. Knowledge
production follows an internal, severe and highly
demanding dynamic, due to methodological rules
and inter-subjective control (Ziman, 1997; 2002).
What accounts for scientific progress is not defined
by the investigator or by society, but only by a
community of other investigators (Rescher, 2000).
The reference point for these internal dynamics
is then the state-of-the-art, or the collective
knowledge held at any given point in time by the
scientific community. This collective knowledge
is valid insofar as it is in accordance with most of
the evidence available- this is a workable notion
of scientific truth. Given this proposition, the
production of knowledge cannot follow external
or societal demands beyond a certain point. The
ultimate court for the production of knowledge
is not social acceptance, but acceptance by an
independent and critical scientific community.
It is interesting to investigate the internal
properties of knowledge production at an abstract
level. In recent years, two models have attracted
the attention of scholars and policy makers: the
Mode 1 and Mode 2 model, and the Triple Helix
model. The former proposes that knowledge
production is increasingly based on multi- or interdisciplinary teams, breaking down disciplinary
boundaries, and moving from investigatordriven research questions to application-driven
questions. While this model captures important
elements, it gives a simplistic representation of
the internal dynamics of knowledge. In particular,
disciplinary boundaries are broken when new
concepts are created at a deep explanatory
level, not for purposes of application. Molecular
biology becomes increasingly dependent on
bioinformatics not because there is an application
out there (this may be a reason for industrial
investment), but because the explanation of
protein synthesis on a molecular basis requires
the comparison of millions of sequenced genes. At
this deeper level the notion of inter-disciplinarity
is a problematic one and does not capture the
essence of phenomena.
The Triple Helix model offers a useful framework
for understanding the tension between the
internal logic of science and the application
side, driven by the interaction between academia
industry and governments. It does not aim,
however, to enter deeply into the analysis of
knowledge production.
More recently, some useful notions have been
developed that might be useful to illuminate
the dynamics of knowledge production and
the driving forces for change. The first one is
the so called ‘Pasteur quadrant’, that offers a
taxonomy of knowledge dynamics in terms of two
variables: quest for fundamental understanding
and consideration of use (Stokes, 1997). Pure
fundamental research addresses issue of
understanding nature, without any consideration
of use (Bohr’s quadrant), while pure applied
research is motivated by use and is not seeking
understanding (Edison’s quadrant). However,
there is also a particular kind of research that is
strongly interested in use, but realises progress
only insofar as it gains deeper understanding of
nature (Pasteur’s quadrant).
This idea has been developed in a recent
document by a High Level Expert Group at the DG
Research (European Commission, 2005), under
the labeling of ‘frontier research’. According to
this document, there is an increasing share of new
knowledge that is, at the same time, potentially
useful and motivated by use, but requires deep
understanding of nature. It is useful to quote this
document fully (Box 1).
In the notion of frontier research the foundations
for multi-disciplinarity are laid down to the
epistemological foundations.
I have recently proposed a notion that might be
useful for our discussion here, namely the idea of
search regimes (Bonaccorsi, 2005). According to
this notion, we can interpret the internal, intrinsic
dynamics of knowledge in science by observing
a few stylised variables, that taken together
define rather precisely several patterns. We have
proposed to observe:
(a)the rate of growth in the production of
knowledge;
55
(b)the degree of diversity in directions of research;
(c)the level and nature of complementarities in the
production of knowledge.
It proposes that most scientific fields which
originated in the last 30 years differ from
twentieth century sciences (mainly physics and
chemistry) in several respects. In particular, fields
such as information technology, life sciences
and biotechnology, materials sciences, and more
recently nanotechnology, although internally
articulated, share these features: (a) accelerated
(sometimes exponential) pattern of growth
after the birth; (b) high diversity of directions of
research (divergence, or proliferation dynamics);
(c) new forms of complementarity, not based on
physical facilities but on institutional and human
complementarity.
With respect to frontier research, we hypothesise
that the trend will continue and reinforce. The
internal dynamics of life sciences (from strong
reductionism in molecular biology to a systemic
view, see for example functional genomics,
proteomics and transcriptomics), information
technology, and materials sciences (smart
materials, manipulation at the atomic level) all
point to exciting new discoveries and potential
applications.
Wo rki ng Paper 3
Researchers (Part 2)
It is important that this achievement of modern
Western scientific organisation is not diminished
by confusing discussion about science as a social
construction.
The Future of Key Research Actors in the European Research Area
Box 1
The notion of frontier research
Frontier research stands at the forefront of creating
new knowledge and developing new understanding.
Those involved are responsible for fundamental
discoveries and advances in theoretical and empirical
understanding, and even achieving the occasional
revolutionary breakthrough that completely changes
our knowledge of the world.
Frontier research is an intrinsically risky endeavour.
In the new and most exciting research areas, the
approach or trajectory that may prove most fruitful
for developing the field is often not clear. Researchers
must be bold and take risks. Indeed, only researchers1
are generally in a position to identify the opportunities
which offer the greatest promise. The task of
funding agencies is confined to supporting the best
researchers with the most exciting ideas, rather than
trying to identify priorities.
56
The traditional distinction between ‘basic’ and
‘applied’ research implies that research can be either
one or the other but not both. With frontier research2
researchers may well be concerned with both new
knowledge about the world and with generating
potentially useful knowledge at the same time.3
There is therefore a much closer and more intimate
connection between the resulting science and
technology, with few of the barriers that arise when
basic research and applied research are carried out
separately.
Frontier research pursues questions irrespective
of established disciplinary boundaries. It may
well involve multi-, inter- or trans-disciplinary
research4 that brings together researchers from
different disciplinary backgrounds, with different
theoretical and conceptual approaches, techniques,
methodologies and instrumentation, perhaps even
different goals and motivations.
Source: European Commission – DG Research (2005) Frontier research. The European
challenge. High level expert group, April.
1. This includes (frontier) researchers working in industry as well as those in
universities and public research organisations. (There have been several
examples of Nobel Prizes awarded to researchers employed in company
research laboratories.)
2. As with the concept of ‘Pasteur’s quadrant’ developed by Donald Stokes
(Stokes, 1997).
3. This is not, however, to imply that the ERC should fund large volumes of
(solely) applied research; only research that meets the other criteria for
‘frontier research’ (in particular, research that promises a fundamental
advance in knowledge or understanding) would be eligible for ERC
support.
4. In what follows, we normally use the single term ‘multidisciplinary
research’ rather than the cumbersome (but more precise) ‘multi-, inter- or
trans-disciplinary research’.
With respect to growth of knowledge, the new
leading sciences and frontier research all point to
sustained growth in the early stages. Indeed, a test
on selected keywords in these fields showed almost
exponential growth. Studying nanotechnology,
Zurby and Dacker (2002) also find exponential
growth. The critical issue is whether these new
leading sciences will enter into a maturity stage,
where the rate of growth will diminish. It is
difficult to anticipate. Most recent accounts of
scientific frontiers, even in the popular literature
(see e.g. Amato, 2002; Maddox, 1998) foresee a
continued proliferation of fields, opened by radical
discoveries. For example, the discovery of gene
sequences responsible for genetic diseases is only
at the beginning. Smart materials are just starting
to be developed. We therefore propose a scenario
where leading sciences reach a maturity stage for
their old fields (those born in the 1970s and 1980s),
still grow rapidly for recently opened fields, and
generate a continuous stream of radically new
fields that grow exponentially.
Diversity is the result of intrinsic dynamics of
knowledge. To take an example, the number of
different places in which to search for antecedents
of any single genetic disease is in the order of
thousands. Each of these places will require a
dedicated team, which will be based on the same
theoretical understanding (no paradigmatic change)
but will take a different direction, partly competing
with other teams. The same underlying proliferation
dynamics can be found in most areas of biomedical
sciences, such as cancer, Alzheimer’s, HIV, or
Parkinson’s. We anticipate this divergent pattern will
continue in the future.
New leading sciences and frontier research are not
based on large physical facilities (big science) but on:
• decentralised facilities (e.g. genomic databases,
networks of molecular biology laboratories,
shared access to synchrotrons);
• institutional complementarity (e.g. between
hospitals, medical schools and laboratories;
between software developers, electronic
designers, and communities of users);
• human
resource
complementarity
multidisciplinary teams).
(e.g.
Here the scenarios are more complex. On one
hand, it is possible that the institutional system
is not reactive. A second possibility is that it takes
a central planning orientation, i.e. to assume that
these new scientific fields are similar to old sciences
and can be controlled directly from the centre. In this
scenario governments identify ‘strategic areas’ and
allocate central resources. Let us label this scenario
‘Colbertist’, although this notion is mainly linked to
industrial, not science policy.
Table 1
Production of new knowledge
Variable
Frontier research
Rate of growth
Degree of diversity
Complementarity
Driving force
for change
Emergence of new
scientific areas:
- highly risky
- demanding (talent)
- oriented to use
- requiring fundamental
understanding
Accelerated/
exponential growth in
the early stage
Future trends
Strong development of
frontier research.
Science policy more
inclined to absorb the
notion.
New fields continue to
be generated within
leading science/
frontier research
Diversity increases.
Intrinsic dynamics of
proliferation of research
hypotheses
New leading sciences A. institutional inertia.
and frontier research
Lack of new centres
are not base on large
and new curricula.
physical facilities (big
Disciplinary
science) but on:
boundaries strong.
- decentralised facilities
No institutional
- institutional
complementarity
complementarity
B. dirigistic policy
- human resource
C. institutional
complementarity
flexibility in building
up complementarity
3.2 Circulation of valid knowledge
Another fundamental function of researchers in
society is to actively disseminate knowledge,
making sure that it meets a standard of validity. This
will require the institutionalisation of legitimation
mechanisms (see below).
The rules for the circulation of knowledge have
been dictated, in modern science, by the norms
of open science (Merton, 1957). These norms will
also be valid in our scenarios. What will likely
change, rather, is the context of the circulation of
knowledge. In particular, we consider the problems
raised by the global circulation of information over
the Internet. This new phenomenon has created
new challenges.
Open scientific publishing
The possibility to publish scientific articles
in web-based journals, as opposed to paper
editions, has considerably lowered the cost of
scientific circulation. Electronic journals are
easier to establish and maintain at low cost.
This may enlarge the audience and the speed of
circulation.
Knowledge sharing
The easiness and cheapness of information
circulation over the Internet has made the goal
of knowledge sharing more realistic. Sharing of
knowledge is much more demanding than just
circulation of information, but is nonetheless greatly
enhanced by Internet communication.
Other emerging trends regard the acceleration of
sequential innovation, in which each step strictly
depends on the availability of knowledge developed
by others.
Knowledge sharing may take several forms:
• several scientific communities maintain their
website, in which all pre-prints are recorded,
discussed and refereed either formally or
informally, and then edited for final publication
on the web and in paper journals as well;
• a classical model is the production of Open
Source software;
• related experiments are the production of
Wikipedia, a freely available on-line encyclopedia
written by voluntary experts worldwide;
• a number of scientific projects recruit nonprofessional volunteers for large scale
exploration (e.g. submarine exploration),
train them for research, and carry out the
investigation activity;
• Creative Commons is a new model of copyright
protection aimed at ensuring the large circulation
of various types of texts;
• in the field of Intellectual Property Rights (IPR),
various forms of patent pooling and patent
agreements are emerging (see for example
Menière and Joly, 2005).
These developments have led to the formulation
of the notion of collective innovation (von Hippel,
2005), as an integration of the more traditional
collective invention.
A summary of trends is summarised in Box 2.
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Finally, it is still possible that the European
system is flexible enough to understand that
the new developments require adaptation in the
institutional rules. This will require sophisticated
government policies, mixing bottom up and top
down approaches. It will require the maximisation
of mobility, both horizontal (international, across
institutions) and vertical (career). It will require
the creation of new institutions (doctoral schools,
new laboratories, joint industry-academia
facilities) at a rapid pace.
The Future of Key Research Actors in the European Research Area
Box 2
Table 2
Institutional backing for Open Access.
Selected examples
Circulation of knowledge
Major science organisations, funding agencies and
university associations
Scientific publishing
Variable
Knowledge sharing
Budapest
(http://www.soros.org/openaccess/view.cfm)
Berlin
(http://www.zim.mpg.de/openaccess-berlin/
signatories.html)
National Institute of health, the US
Open Access Journal Platform
The Public Library of Science (34 000 signatories).
Grant of USD9m. Sponsors: Genentech and Merck
(www.plos.org).
Biomed Central (120 journals, Faculty of 1 000).
Processing charge USD500-1 500; accelerated peer
review in 8 weeks (www.biomedcentral.com).
Pre- and Post-Print Repositories
www.arXiv.org – 300 000 papers in physics and related
disciplines
58
www.ssrn.com – 60 000 papers, 250 000 download per
month, top author with 175 000 downloads
www.jstor.org – 457 journals, moving wall of 3 to 5
years, USD25 000 p.a. subscription fee for a large HE
institution
Knowledge Exchange
www.livingreviews.org- solicited online-only refereed
review articles; to record progress in the research
field and to guide readers to the relevant literature;
updated regularly; International Advisory Board.
Source: Anderson (2005).
We anticipate an increase in the specialised field
of scientific publishing over the Internet, but also
of various forms of knowledge sharing. In the first
scenario we consider the possible creation of new
institutions (new types of licensing schemes and
copyrights, clearing houses, new contracts) and
a flexible and permissive legal environment. The
idea of a global digital archive will materialise when
the technological problems associated with the
conservation of magnetic support are solved.
Driving force for
Future trends
change
Lowering cost of
Increase
scientific journals
Internet communication A. Overall increase.
New institutions
Sequential innovation
created to manage
more diffuse
knowledge sharing /
pooling
B. Monopolist reaction
3.3 Legitimation
In order to implement the social functions of
producing and circulating new and valid knowledge,
researchers need other functions to be fulfilled by
society. In particular, the political system at various
levels has three main functions: legitimation,
selection, and funding.
A fundamental function of researchers in society
is to produce valid knowledge, i.e. to produce
knowledge that has been subject to a process of
inter-subjective validation and control, and can be
considered reliable from non-experts.
The validity of knowledge relies on the adoption of a set
of procedures whose application is usually unobserved
by external users of the knowledge itself. Science
is therefore subject to a fundamental information
asymmetry (Dasgupta and David, 1995; 1997). To correct
for this asymmetry, it is necessary that the scientific
community adopts a rule of priority that emphasises the
ability to control the adoption of correct procedures by
scientists. Since the rule of priority gives high visibility to
the scientist who makes a discovery, this creates strong
incentives to carefully follow methodological rules that
qualify a piece of knowledge as valid. If a scientist is
found to be unprofessional in following methodological
rules, their reputation is damaged.
What happens in contemporary societies is that,
increasingly, knowledge is produced outside
the perimeter of conventional academic activity.
Examples are:
• think tanks;
• private research organisations;
In the second scenario, on the contrary, it is possible
that a counter-reaction is activated by monopolistic
owners of knowledge (e.g. publishers, majors, even
universities). Digital reproduction of information
will be severely restricted. Even free circulation
environments, such as academia, might be subject
to strong enforcement.
• non-profit organisations;
• government agencies;
• consultancy companies and market research
organisations;
• environmental pressure groups;
• trade associations or interest groups.
All these actors put significant efforts into producing
knowledge, very often original knowledge, on various
subjects of interest. They produce this knowledge
for their own use, as in the case of government
agencies, or for selling, as in the case of consulting
companies or private research organisations, or for
advocacy, as in the case of pressure groups, nonprofit, or interest groups. Each of these motivations
is socially valuable and must be protected.
The impact of these new actors in the production
of new knowledge is made even more important
by the advent of the Internet, which replicates and
magnifies the extent of communication. The creation
of reputation over the Internet follows the same
criteria as for scientific knowledge (i.e. citations),
but the entire process is not governed by scientific
authority. Paradoxically, it may well be that the result
of reputation creating processes on the Internet
diverges from the same processes mediated by the
‘physical’ community of scientists.
At the same time, these actors lack the interest
for following the fundamental criteria of academic
research, that is, peer review. It is the fact that
pieces of scientific knowledge have been subject to
the comment and ultimate acceptance of colleagues
in the discipline that qualifies this knowledge as
valid. As is well known, even peer review is subject
to many limitations, but it is still considered the best
method for inter-subjective validation. What about
these different forms of research?
We consider possible scenarios. In the former
scenario non-academic sources of knowledge are
considered fully legitimate by society. This is done
through codes of self-regulation, ethical standards,
and communication protocols. Society trusts these
sources of knowledge as reliable. Producers of
knowledge submit themselves to inspection or other
forms of inter-subjective control, in order to increase
the public’s commitment. Strong reputations are
created. Academic research progressively loses the
power to validate other forms of knowledge.
In the second scenario new sources of knowledge are
accepted in society but only if validated by traditional
academic sources. We may think of this as the cooptation of new actors by established sources of
legitimate knowledge. A case in point is the creation
of new universities, particularly private universities,
in several European countries. Sometimes these
new actors rely on a few established authorities to
affirm their credibility as producers of research and
reliable knowledge.
More generally, there may be processes of
accreditation and certification by the public authority,
in order to increase public trust. For example, new
universities may open large on-line curricula, which
may be less controllable than conventional teaching
in terms of the accreditation of teachers. Distance
learning and Internet-based curricula may create
similar problems. In order to preserve the authority
of scientific knowledge, governments may establish
certification processes.
Finally, in the third scenario there is a clear separation
between established, credible knowledge production
by research organisations and universities, and
other sources which enjoy a lower status.
Table 3
Legitimation of researchers
Variable
Legitimation
Driving force
for change
Creation of several
new actors that carry
out research and
produce valuable new
knowledge for society
Future trends
A. Spontaneous selfregulation of new
actors and creation
of reputation
B. Accreditation
and certification
by established
authorities
C. Separation and
hierarchical
organisation
3.4 Selection
The institutional system has the fundamental
function of selecting researchers and research
projects. This function is allocated to the institutional
system because there is no market selection that
can make this effectively. Non-market selection
and coordination mechanisms require one form or
another of political decision making.
Selection applies at several levels:
• long term strategic goals (‘technology strategy’,
‘scientific and technological priorities’ and the
like);
• research areas, broadly defined;
• individual research projects;
• rules for the selection of researchers.
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• patient organisations;
The Future of Key Research Actors in the European Research Area
Given the focus of the scenario building on actors/
researchers, we focus only on the latter point, by
examining changes in careers of researchers.
We consider the following dimensions of change:
• the size of the market for researchers;
• the selection criteria for careers;
• relative pay;
• the shortage of S&T researchers.
Size of the market
60
We begin with a variable which is rarely considered
in ST&I policy, that is the size of the labour market
for research. In the companion paper of this chapter
we have demonstrated that the attractiveness of
the European environment is decreasing, starting at
undergraduate level and continuing to PhD students
and post-docs. The proportion of foreign students or
researchers in Europe decreases monotonically. We
interpret this evidence by saying that the opportunity
cost of staying in Europe, rather than going to the
US or Asia, is large for junior researchers that have
an international potential.
We have also shown how large the threat is posed
by the massive investment into tertiary education,
postgraduate studies, and research by China and
India combined. It must be said that the awareness
of this threat is much greater in the US system
which, paradoxically, is less exposed to negative
consequences. In the recent report Rising above
the gathering storm, the National Academies
of Science of the US clearly puts the problem in
perspective: there is not an immediate threat of loss
of competitiveness of the American S&T system, but
in the long term (say, 2020) the presence of China
and India in scientific frontiers and high technology
areas will be substantial.
In other words, we suggest that junior researchers
rank their preferred locations for research worldwide
and try to match their profile with these locations.
If their profile matches the location, they will be
offered a curriculum or post-doc position, and they
will move. This ranking is increasingly international,
meaning that researchers perceive the cost of
staying at home as potentially high. The literature on
‘brain circulation’ has made clear the determinants
of mobility of researchers, and has stressed that the
so-called brain drain should be viewed in a long term
perspective.
If potential mobility is increasing, small markets, or
markets in which the best positions are institutionally
allocated to domestic students, will inevitably
become less competitive. Underlying this claim
there is a statistical argument: if the distribution
of potential talent of researchers is skewed, labour
markets that sample from a larger base will be much
better able to identify those over-performing. Small
markets will be saturated easily with domestic
candidates, but then the best performance will be
that of the best within a small sample of potential
talents. Small labour markets will not have the
possibility to spot bright researchers outside.
We consider three scenarios. The first scenario is
the continuation of having small national markets,
as they are now. The role of researchers is to
teach in national languages. Public applications
systematically prefer national candidates, or de
facto prefer them.
The second scenario adds some voluntary, EU-initiated
or bottom-up initiated initiatives for integration.
Examples of this kind are the European Science
Foundation fellowships. A prestigious (and successful)
example of this policy has been the European Molecular
Biology Laboratory that has systematically attracted
researchers from various countries, without any
national quota, and nurtured an authentic European
scientific community of practice. These initiatives may
offer temporary, or sometimes tenure-track positions
to researchers outside the national environment. An
interesting scenario would see the share of foreign
researchers in national institutions steadily increasing,
although slowly.
Finally, we consider a third scenario, called ‘SmithYoung-Stigler scenario’. According to the famous
Smith theorem, further developed by Young and
Stigler, the division of labour is limited by the size
of the market. Suppose the division of labour in
research increases the quality of research: this
may be a questionable assumption in some cases,
but it is normally true. It is better to become an
internationally recognised scholar of a small field,
than be an average expert on many issues, that
however are of interest only to a domestic audience.
In scientific disciplines, in which research requires
extended training and painful trial and error, the
effects of division of labour are greatest. The limits
of professional division of labour may be overcome
through departmental organisation.
We apply this argument by analogy. In a small
research market, due to the limited division of
labour, the quality of researchers may depend on
the average performance in different scientific
areas. In a large market, for each area there will be
an international ranking and the quality will depend
uniquely on this ranking. Individuals that are good at
the domestic level will find themselves well behind in
an international ranking, and there will no longer the
possibility to compensate with other fields, because
at the international level there will be separate
rankings. To give an example, in a small domestic
market an economist knowing something about
labour economics, industrial economics, finance,
and organisational theory might be appreciated. But
at international level he will have to compete with
specialists in each of these fields, and his reputation
will invariably diminish. Larger markets put more
pressure on individual performance. There is no
pentathlon in the international scientific competition
(apart from real geniuses, of course).
Box 3
Our third scenario is based on the assumption
of a strong, European Union-backed initiative to
enlarge the market for researchers immediately and
rapidly. The idea might be to start with a massive
internationalisation of PhD careers, by opening a
large pan-European job market for PhD graduates
and for post-docs (see the attached paper). The idea
would be to involve large European companies and
to directly address universities, by-passing national
governments. A few European universities routinely
recruit researchers on an international basis, but
so far this practice is restricted to some UK and
Swiss universities, with some experience also
in Scandinavian countries. The bulk of European
universities still recruit their researchers nationally.
European Science Foundation
A. The New Instruments and the integration of
research via the EU
More than 50 per cent of the funds within the first
call of FP 6 have been allocated to New Instruments
(Marimon et al., 2004).
3 000 participants in Networks of Excellence
6 000 participants in Integrated projects
Average number of participants: 32.
Open Method of Coordination (OMC)
ERA-NET
B. Integration outside the institutional framework of
the EU
EUROCORES program, a research scheme
combining national and European financial
resources to support European scientists in
addressing major research challenges
European Heads of Research Councils (EUROHORCs)
European Young Investigator Awards (EURYI), a
scheme to attract outstanding young researchers
from anywhere in the world to work in Europe and
lead their own team
Strategic partnership
CNRS, FhG, CNRS/Max Planck-Gesellschaft (MPG),
Netherlands Organisation for Applied Scientific
Research (TNO)/Joanneum Research
Nordic Council of Ministers for Education and Research
NordForsk, Nordic Research Board
CNRS
Laboratoires Européens Associés (LEA)
Source : Edler and Kuhlmann, 2005.
Faced with this challenge, European governments
and European scientific institutions have responded
with timid, small scale integration policies. These
efforts are interesting and valid, but in our opinion
stay below the threshold for structural impact. Box
3 summarises the main developments taking place.
Edler and Kuhlmann (2005) document a real increase
in the extent of formal and informal integration at EU
level.
In the language of Bonaccorsi (2005b), however,
the problem is not one of better policies, but one
of better institutions. Policies aimed at integration
should address the institutional constraints that
limit de facto the potential for integration.
Selection criteria
One distinguished feature of most European
institutional systems is the lack or weakness of
purely competitive selection criteria. There are several
variations on this theme: the internal career of most
German PhD students, who take a position in the
same department and with the same supervisor; the
recruitment system in France and Italy, with elective
mechanisms that may favour strategic maneuvering;
and other national systems. In general, the degree of
autonomy of universities in hiring people is limited,
because the candidates are decided internally by the
local scientific community, within a bargaining game
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This scenario would require an effort similar to
those that have led to the Bologna Conference and
the Bologna process on university curricula. We now
need a major reform in markets for research, based
on a substantial enlargement of their size.
Integration within the EU system.
Selected examples
The Future of Key Research Actors in the European Research Area
with the national scientific community of the same
type. A system of this type extends from the entry
level (research assistant or equivalent) to higher
levels. A critical element lacking in these systems is
the loss of reputation that is generally associated
with protecting a weak candidate in competitive
systems. The penalty for supporting poor candidates
is immediate and devastating. As a result, each layer
of quality of researchers is self-reinforcing, because
researchers do not accept to support lower-level
individuals, but can get no access to support from
higher-level colleagues. These mechanisms are
institutionalised by universities that have policies of
recruitment that clearly target given layers of quality.
62
In addition, few European countries have a system
of tenure-track, i.e. a system that promises a
tenured position after a pre-specified period, under
conditions that an individual satisfies a number of
performance criteria. Tenure-track positions establish
a distinction between layers of academic quality,
and strongly align individual incentives. In addition,
tenure-track positions are the only possibility for
universities to plan their strategy. Since the full cost,
long term position will be awarded at the end of the
period, universities have time to allocate resources
and to evaluate candidates, offering the positions to
the best available candidate.
Now it must be considered that competitive
selection criteria are increasingly preferred by junior
researchers. Surveys of PhD students, post-docs
and researchers migrating to the US have invariably
indicated that what these people appreciate greatly
is the competition in quality and the freedom in
organising research. There is tremendous pressure
on results, but complete autonomy in organisation.
In most European universities the opposite is
true: relaxation on results, but excess control and
bureaucracy on the organisation of research.
We consider two scenarios. In the former the status quo
is dominant. Despite institutional adaptations (e.g. the
French rule of alternation of selection committees, or
the recent Italian call for a national board), individual
incentives will not be changed greatly or lastingly.
Selection criteria will stay opaque.
In the latter scenario there will be limited
experimentation, mainly through:
• autonomous initiatives of European researchoriented universities;
• off-shore
initiatives
experimentation.
or
institutional
Autonomous initiatives may involve a number
of well respected research-oriented European
universities and institutions that adopting codes
of conduct based purely on competitive criteria.
In some sense, they would recognise that the
institutional system allows the recruitment
of under-performing individuals, but these
institutions would credibly self-restrain from
these strategies. If they want to be credible
(in the Schelling sense), they should make an
irreversible commitment to transparency and
responsiveness.
Other initiatives may come from so-called offshore institutions, or from new emerging models.
For example, the Ecole Polytechnique Fèderale de
Lausanne (EPFL) has adopted a tenure-track model
with a purely competitive, international selection
of candidates. In Spain, the two economic and
business schools of Pompeu Fabre and Carlos
III have been established with an international
recruitment model. In Italy, the Italian Institute
of Technology (IIT) has been created greenfield
by the government, with a purely competitive
recruitment model. It must be clear that we are not
advocating these models as such. There are many
political, institutional and organisational problems
behind these experiments. The important thing is
that these new institutions enlarge the variety of
institutional mechanisms within countries, and
allow greater experimentation and comparison
of results. Is it more effective than a patronage
system, in which senior researchers co-opt junior
researchers which they have known for years,
since their degree, or than a purely competitive
international model, in which researchers at
each stage compete in large markets, without
any guarantee? There may be pros and cons in
each of these models, but there is no possibility
to compare these relative merits in European
institutional systems.
Relative pay
Another factor that may change the attractiveness
of research careers is the level of salary. There is
paucity of research on these issues. On one hand,
it is largely believed that research is one of the few
professions in which intrinsic reward is at stake
(Stern, 2000). Public researchers accept lower
salaries than researchers in the industry because
they value the intrinsic satisfaction of autonomy,
intellectual freedom, and lack of stringent
organisation. There is a large body of literature on
the notion of intrinsic reward (see a brief survey in
Bonaccorsi and Rossi, 2005).
In addition, there is the prospect of Lisbon 2010
and beyond Lisbon, say 2020. How could we attract
700 000 more researchers to Europe? One way is,
as discussed above, to rely on foreign researchers
and massively and rapidly open our labour markets
to junior researchers from abroad, mainly from
Asia. Another way would be to increase the level
of salaries. Some universities across Europe are
working the other way round- lowering costs for
students in scientific and engineering faculties,
reducing admission fees and allocating grants. There
is not much coordinated effort across European
countries.
One obvious problem is that it is impossible to
increase the salary of S&T researchers alone, without
increasing that of, say, accountants. The social cost
of attracting junior researchers to the profession
may be too high.
We consider two possible scenarios. One is
stationary relative pay. Another is a massive increase,
motivated by the need to attract researchers.
Shortage of S&T researchers
The issue is well known. A shortage of S&T
researchers is anticipated due to the decrease, in
most OECD countries, of students in science and
engineering.
We consider two possible scenarios: one of inertial
continuation of the current trend, down to a
minimum level of recruitment. Another is an active
policy orientation, starting from high schools, to
nurture the vocational orientation of young people to
these disciplines. In this respect, the ‘ten thousand
teachers for ten million minds’ initiative proposed
by the recent report of the National Academies of
Science in the US is far reaching (NAS, 2005).
Another strategic direction would be to open
scientific careers to foreign researchers on a
substantial basis, by limiting public funding of
doctoral programs to those schools able to teach
in English and allocating resources to international
cooperation.
Table 4
Selection- rules for researcher careers
Variable
Size of the market
Criteria for selection
Relative pay
S&T researchers
Driving force
Future trends
for change
International mobility A. Size of labour
of talents (‘brain
markets stay small.
circulation’)
Mainly domestic
Competition from Asian B. Bottom-up initiatives
countries
to enlarge the labour
market
C. Massive and
rapid initiative to
internationalise the
labour market for
research, starting
from PhD and postdoc level
Preference of junior
A. Criteria selection
researchers for
does not
transparent competitive
substantially change.
selection rules
Remains opaque
Possibility to attract
B. I ncrease of
researchers from other
institutional variety
countries
through autonomous
self-restriction
of established
universities and/
or new institutions
promoting
competitive rules
Need to attract new
A. Relative pay do not
researchers in the
change
profession
B. I ncrease in relative
pay in order
to attract new
researchers
Skill shortage
A. Inertia
B. Active policy
3.5 Funding
A critical feature of research is that it cannot be
financed by borrowing money. The main reason for
this is that research deals with forms of uncertainty
that exceed the notion of risk. Research requires a
long term supporting institution, such as religious
institutions as was the case in the Middle Ages, or
national states in the modern era (Wiener, 1957).
Market forces can provide capital for risky activities,
but only if the risk can be quantified through
measures of probability and the discounted expected
rate of return can be computed. Or, alternatively,
they can provide capital for a pool of projects, acting
as if it were an insurance activity. Neither solution
can provide adequate funding.
Public funding is a requisite for private funding.
According to the economic analysis of science, the
role of public funding is to reduce the fundamental
uncertainty down to the point where the risk can be
computed and private investment can flow (David,
Mowery and Steinmuller, 1992; Evenson and Kislev,
1977).
A recent survey of funding structures of public
research in several European countries has been
carried out by the ENIP project (see the website).
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At the same time, the level of pay relative to other
professions should create an incentive to the
protracted investment in human capital, which
is typical of a career research. Junior researchers
start to earn significant amounts of money quite
late in their life cycle, so that the relative income
they receive in their career should compensate for
this loss.
The Future of Key Research Actors in the European Research Area
The driving forces for change here can be summarised
as follows:
Emergence of different layers of public
funding
• the proportion of public funding of research out
of the total;
The emergence of regional governments as key actors
in ST&I policies has already been examined in recent
years (Cooke, 1997; Sanz and Cruz, 2005). Regions
increasingly enter this field with strategic plans and
funding, with a view to reinforcing the linkages between
research, innovation and local/regional growth.
Varieties of these policies include agglomeration
policies (clusters, technological districts, technopoles),
policies for seed capital and venture capital, incubation
and infrastructures for new firm creation, all of which
may have an indirect effect on researchers.
• the emergence of different layers of public
funding;
• the share of research funding that is allocated on
a contract basis;
• the amount of industrial funding;
• student fees;
• the variety of funding sources.
Public funding of research
64
By and large we consider that this trend will continue,
bringing new financial resources to researchers,
while government resources may steadily or slightly
diminish.
Sometimes in the policy debate the notion of
‘privatising science’ is proposed. A few proponents
support the view that reducing the share of public
funding may be the only way for stimulating the
research system to look for private funding. Most
scholars argue that the economic rationale for public
funding is still very strong and that public funding is
a necessary condition for collecting private funding.
The US observed a sharp decline in Federal support,
but this was more than compensated by the rise of
State support and private/ industrial funding.
Contract research
As a matter of fact, we don’t see a strong decrease of
public support to the research system in Europe.
Further research has shown that, in fact, the share
of contract research is stable (see for example the
ENIP Reports). There is not a sharp increase. This
is most probably the effect of opposite pressures:
governments may want more contracting, whereas
scientific communities stress that only free research
is useful and creative in the long term.
Rather, we see a majority of countries in which
public support is stable, and a few countries (mainly
Scandinavian) in which it is significantly increased.
With regards to future trends, we consider it most
likely that the aggregate level of public funding will
remain stable, but with a change in the composition
between government and regional funding.
Alternatively, a possible scenario might be one of
a sharp decrease in public funding, decided by the
government in order to put pressure on researchers
to seek funding either at the European level or from
industry (‘The Economist’ scenario).
Finally, another scenario is the one currently being
tested out in Scandinavian countries, where the level of
public funding has steadily increased, but institutions
have been reformed or created ex novo following a
competitive model. The combination of public funding
and meritocratic/ competitive rules may constitute an
interesting alternative worth exploring.
A few years ago, several authors (e.g. Geuna) drew
attention to the increasing proportion of public
research funds allocated through contracts, rather
than given freely. Contracts are sometimes preferred
by governments and intermediary agencies because
they are more controllable and there is apparently
more accountability. Contracts are also standard
practice at the EU framework program level and
others in general.
We consider that a steady level of contract research
is more likely. No alternative scenarios on this
variable are considered.
Industrial and private funding of public
research
The existing evidence shows a steady but slow
increase in the extent of industrial funding to
public research. Notwithstanding the fact that the
prevailing evidence shows that industrial funding
and scientific quality are positive complements,
not substitutes, the level of funding is still small
(Etzkowitz et al., 2005; Bruno and Orsenigo, 2003;
Bonaccorsi, Daraio and Simar, 2006; Balconi and
Laboranti, 2006; Calderini and Franzoni, 2005).
In the first we see a continuation of the existing
trend, with industrial funding accounting for a
few percentage points of the average university
budget, say, from 1-3 per cent to 7-9 per cent in
the period. This would be the result of pressures
on industry to make more effort towards the public
research system, but without structural changes and
incentives.
In the second scenario the private funding from
industry and other private sources to the public
research system becomes significant (say, up to 20 per
cent). Part of it will come from industry contracting,
part from private donations, either by corporate donors
or by wealthy individuals. We call this scenario ‘AlesinaGlaeser’ because in their latest book these authours
show a structural difference in social preferences and
institutional arrangements between Europe (with the
possible exception of the UK) and the US (Alesina and
Glaeser, 2004). In Europe the level of taxation is high
and the level of private donation is very low, while
the opposite is true in the US. In Europe the social
perception is that individual success is largely due
to luck and that individual poverty is not the result of
personal responsibility, while in the US people believe
success is ultimately due to individual merits and
poor people are responsible for their status. These
social differences extend not only, as is obvious, to the
design of the welfare system (insurance against the
volatility of personal chances), but also to the design
of the education system (investment in the future of
personal chances). If people strongly believe that the
ultimate reason for success is personal effort, and
also consider that this belief is shared in society so
that there is a high probability that their merits will be
recognised, then they will be willing to invest heavily in
education from their private income. When they have
achieved their economic success, they will be more
likely to make donations to universities, because they
will recognise them as the source of their own success.
If on the contrary people firmly believe that success
is largely due to social mechanisms, and that luck
and social position play a greater role than individual
effort, then they will be more likely to call for social
sharing of costs of education. Once they have
received higher education, they will perceive it as an
obligation of society, because the cost of it has been
included in the heavy taxation. As a consequence,
they will feel less obliged to donate to universities
or private foundations.
The flow of income from private donors and
companies to universities requires a favorable fiscal
environment. In the latter scenario, governments
encourage private/industry flows through fiscal
incentives. We do not posit that there is equivalence
between private funding and contract research, apart
from industrial funding. A large part of private funding
takes the form of grants and long term allocations, in
which research is mainly investigator-driven.
Student fees
In European universities, student fees are
traditionally low and account for a small share of
university budgets (see the evidence from CHINC
and AQUAMETH).
The proposal to raise student fees is based on the
notion that students and their families will become
more able to calculate the rate of return of education
and will place many more demands on universities,
raising the levels of service and the demand for
quality. In turn, this will increase the competition
between universities in hiring the best professors
and teachers, based solely on their research and/or
educational performance.
On the other hand, critics say that poor families
will not be able to raise enough money to fund
the university fees and the cost of living. This will
preclude tertiary education to lower class students,
producing inequality and ultimately restricting the
pool of talent. These critics argue that European
financial markets are not as efficient at lending
money to families on the grounds of the expectation
of future income from students.
The evidence shows that the returns from university
education in Europe are substantial (Brunello et al.,
2005; Walker and Zhu, 2005, Brezis and Crouzet,
2004). At the same time, there are strong reasons to
expect that financial markets are not able to effectively
discount the future income differential of educated
people, so that rationing effects are likely to occur.
We consider a status quo scenario, a moderate increase
scenario, and finally a full pan-European implementation
of ‘The Economist scenario’, where student fees are
raised substantially, up to €5 000 per year.
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This raises an interesting question about future
scenarios for European researchers. Is this due to the
traditional separation between the university activity
and industrial needs? Is this due to the desire of
researchers for independence and autonomy, while
industrial funding always requires the adoption
of severe milestones, industrial reporting style,
and time consciousness? While these issues are at
the core of a large literature, here we develop two
alternative scenarios for this variable.
The Future of Key Research Actors in the European Research Area
Table 5
Funding
Driving force for
Future trends
change
Role of public funding Pressure on
A. No considerable
of research
government budget
aggregate change
Public opinion support
foreseen in
to public research
continental European
countries:
• stability/ slight
reduction in
government
support
• increase in regional
support
B. Sharp decrease in
public funding (‘The
Economist’ scenario)
C. Scandinavian
scenario: countries
at steady state on a
high level of public
support
Emergence of different Constitutionalisation
Strong emergence of
layers of public funding of the role of regional regional governments
governments in
as key players in ST&I
policies of research and policies
innovation
Multi-actor, multi-layer
policies – increasing
complexity
Contract research
Government need
Steady level of contract
for control and
research
accountability
Countervailing effect
of the request of the
scientific community for
blue-sky funding
Industrial funding
Pressure on universities A. Moderate increase
to look for private/
in the level of private/
industrial funding
industrial funding
Fiscal incentives
B. Strong increase in
Strategic long term
the level of private/
view of companies for industrial funding with
nurturing innovation
the support of fiscal
capabilities
incentives (‘AlesinaGlaeser scenario’)
Student fees
Competition between
A. Status quo (typically
universities
€1 000)
Lack of funding
B. Moderate increase
(€2 000-3 000)
C. Substantial increase
(€5 000)
Variety of funding
Rise of heterogeneous A. Still limited variety
sources
funding institutions
B. Strong increase
(private foundations,
in the funding
donor funds, corporate
from foundations
donations, private
(corporate, bank,
angels)
local)
Variety of criteria for
selection and time
horizon of research
Variable
66
the variety of funding institutions implies a variety of
selection criteria, based on:
• level of risk/uncertainty;
• time horizon;
• applied vs blue sky.
We consider two alternative scenarios. In the first
the variety of funding institutions remains limited.
Government sources play the largest role, while
foundations occupy a small niche.
In the second, on the contrary, we anticipate a larger
role for private foundations, non-profit organisations
and community associations in funding research. The
amount of resources that can be mobilised this way may
be significant, if an appropriate environment is created.
3.6 Accountability
The constitutional covenant that links scientists with
the public system and with society is currently under
stress. Increasingly, civil society demands more
information and more justification for the investment
of public money and for scientists’ selection of the
research agenda.
This overall trend has led to the creation of several
new mechanisms through which researchers ‘give
an account’ of what they are doing, and public
opinion may directly or indirectly control. Initially
these efforts took the form of ‘public understanding
of science’, in which researchers were somewhat
the object of public scrutiny, while recently a more
proactive role has become evident.
These solutions include:
• forums;
• science kiosks;
Variety of funding sources
• science festivals;
The European landscape is characterised by a low
variety of funding mechanisms. Traditionally, research
is funded directly by the government (Ministry
of Research) and indirectly (intermediaries such
as research councils or large agencies). Regional
governments only recently entered the game. Industry
funding is still limited. Private foundations are still
scarce, with the exception of the UK.
• science weeks;
This is a severe weakness of the European
institutional system (Bonaccorsi, 2005b), because
• the involvement of patient associations or interest
groups in committees;
• the publication of Corporate Social Responsibility
documents by universities or research centres.
Another core channel of activities focuses on the
role of ethics and ethical committees in sensitive
issues, such as stem cells or human cloning, and
Box 4 gives some information on Science & Society
initiatives.
Box 4
Science and Society initiatives. Selected
examples
Human Genome Project
Ethical, Legal and Social Issues program (ELSI)
Allocation of funds: National Institute of Health 5 per
cent of budget; – Department of Energy 3 per cent.
NASA Education: 1 per cent of budget 2004.
EU Framework Program 5: RPAST program, €18 million
EU Framework Program 6: Science & Society, €88
million (less than 0.5 per cent total)
EU Framework Program 7: Science in Society, €558
million
Through these means researchers try to increase the
consensus of the public opinion and to leverage this
support vis-à-vis policy-makers. Researchers also try
to maintain autonomy in fixing the research agenda.
One possible scenario is that researchers are
increasingly involved and active in these activities,
receiving support and visibility and enhancing the
prospect for public funding.
3.7 Relevance
By relevance we mean the societal demand for the
adaptation of knowledge produced by researchers.
Society understands the value of knowledge per
se, but is also confronted with a number of difficult
problems (environment, energy, social congestion,
security, immigration etc.) and asks the research
system to make an effort to adapt and transform
knowledge, so that it can be used for solving
problems. This pressure can be considered the
demand for new public goods (Laredo, 2005).
In a similar vein, the economic system puts pressure
on researchers to transform and adapt knowledge
so that it can be used for industrial and commercial
purposes. This amounts to a demand for new collective
goods, i.e. goods produced by public research that
can be exploited by external actors, such as firms.
Both demands require strong adaptation capabilities
from researchers, because they are in addition to the
two traditional missions of teaching and research.
These activities, collectively identified as the third
mission, include the production of new public goods
in the form of consultancy to governments, advice,
public opinion making, public understanding of
science, advocacy, and the production of collective
or quasi-private goods such as patents, spin-off
companies, technology transfer and industryacademia relations.
Another scenario, however, extends to the possibility
that stakeholders block some research activities,
for ideological or political reasons. We do not refer
to legal limitations to research (e.g. reproductive
cloning) based on formal procedures of dialogue
with the scientific community and the building of
consensus, but to the activity of pressure groups
that may gain the power to influence public opinion
and politicians.
Table 7
Table 6
Production of new
collective goods
Accountability
Variable
Accountability
Driving force
Future trends
for change
Larger diffusion of
A. Steady increase of
scientific culture across
initiatives to support
the population
the accountability
Pressure of taxpayers
of scientists, with
for accountability of
positive reaction
government decisions
from society
Pressure of public
B. Pressure groups
opinion and
able to block the
interest groups for
development of
accountability of
science
scientists in their
decisions about the
research agenda
Relevance
Variable
Production of new
public goods
Driving force for
change
Pressure from public
opinion
Pressure from
companies and
governments for
opportunities for
growth
Future trends
A. Systematic
involvement of
researchers in
production of new
public goods
B. Negative reaction.
Cultural defense
against new
activities
A. Increase in third
mission activities
by researchers.
Diffusion of TTO, ILO,
incubators and other
tools across the
system. Circulation
of best experiences
B. Counter-reaction in
defense of public
nature of knowledge
A large body of literature deals with these issues (for
recent surveys see Etzkovitz et al., 2005; Lissoni and
Breschi, 2005; Slepeerslater, 2005). By and large
this literature shows that, up to a certain point, the
involvement of universities in quasi-commercial activities
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Researchers (Part 2)
more generally on ethical and social implications of
science and technology.
The Future of Key Research Actors in the European Research Area
and technology transfer is positive, bringing new
resources, opportunities for job placement and stimuli
for original research (Calderini and Franzoni, 2005;
Bonaccorsi, Daraio and Simar, 2006). However, beyond
a certain threshold, there is the risk of short-termism
and distortion of incentives. In short, there is an inverted
U-shaped curve between the level of involvement into
third mission activities and quality of research. The big
issue for each institution is to correctly understand in
which region of this relation they lie.
We consider two possible scenarios for each
issue. In the first scenario, researchers accept the
enlargement of their social function and allocate part
of their time (collectively) to the production of public
goods and to the transformation of knowledge for
social purposes.
In the second scenario, however, there are strong
counter-arguments from researchers, wishing to
defend their traditional mission. This may lead to
conflicts and institutional failures.
68
4. Impact analysis of
scenarios on the ERA
and the European
knowledge society
The combination of possible trends in these different
variables related to the functions of the sub-systems
generates many alternative scenarios. Efforts have
been made to ensure that there is consistency
between variables within the same scenario and
sufficient diversity across scenarios.
The result is four scenarios for researchers as actors
in the ERA. As usual, we label them with reference
to the main aspects of the internal consistency of
variables and to the thrust of change.
• the ‘researcher as civil servant’ scenario;
• the ‘return of national policies’ scenario;
• the ‘knowledge as private good’ scenario;
• the ‘European competitive ecology’ scenario.
In the first scenario (‘researcher as civil servant’)
the traditional definition of researchers as public
officials, entirely devoted to public service, is
reaffirmed. Researchers resist the extension of
their mission towards new societal demand (public
and/or commercial). The level of public funding to
research remains stable or increases slightly, while
private funding stagnates and student fees are kept
at minimum.
Research careers are rigidly public. Competition is
mainly at national level, with careers planned from
the centre. Institutional experimentation is severely
limited. The variety of funding sources is minimal
and there is no strong role for private foundations.
The number of new researchers grows slowly
due to restrictions in government budgets. Junior
researchers are selected following internal rules
of recruitment. No massive immigration of foreign
researchers takes place, because the status of civil
servant is less attractive to highly mobile people.
New actors in the production of knowledge are not
considered seriously by public researchers. European
policy is considered only as an additional source
of funding, with no implications for competition
between researchers and for the careers of junior
researchers.
In the second scenario (‘the return of national
policies’) governments take a proactive role and
adopt a number of new policies. However, they do not
change their institutions. The rules for the selection
and recruitment of researchers stay national and
collusive, the size of the market is small, and the
funding mix is substantially oriented towards the
public sector. However, governments adopt policies
to encourage researchers to engage in third mission
activities, to raise private funding and to contribute
to societal discussion. Active policies of public
understanding of science are adopted. Governments
strictly regulate the production of knowledge from
non-academic actors, emanating rules and directives
for certification and accreditation.
In some cases governments adopt long term plans
for strategic scientific and technological areas, and
researchers have the incentive to move to targeted
research.
European initiatives are encouraged, but only as
complementary to national policies. Some limited
effort is done in the direction of integration of
policies. Governments lobby the EU to impose or
negotiate their national priorities and to leverage
funds. No major structural reforms in the labour
market, or in the competition between universities,
is introduced.
In the third scenario (‘knowledge as a private
good’) a radical shift is produced with respect to
the policy orientation and the role of researchers.
This scenario is not policy-driven, but institutional
reform-driven. Due to the financial collapse of some
public universities, a shift towards private models
is promoted. The labour contract is made private
and negotiated on a personal basis. Universities
are granted the greatest financial autonomy by
governments but there is also a sharp decrease
in resource transfer. They raise student fees
significantly and increase private funding massively.
This makes the profession attractive, because
relative pay increases and foreign researchers
flow into the system. Strong competition between
universities raises the average level of service. The
management of universities is hired from the private
sector. The undertaking of third mission activities, in
this scenario, is entirely tilted towards the production
of quasi-private goods such as technology transfer,
IPR and spin-off companies, while the social mission
is neglected.
In the fourth scenario (‘European competitive
ecology’) major changes are introduced in the
institutional texture of European systems, without
disruption. A series of new institutions are
created, mainly Graduate Schools following purely
competitive recruitment models on an international
basis. A number of purely teaching universities
(college universities) are created, with the goal of
satisfying educational needs that do not require
research. The competition between universities is
strong.
Large inflows of foreign students and researchers
enlarge the market. An integrated job market is
created at the level of PhD graduates and postdocs, with large companies and many universities
voluntarily convening to the selection conferences
to hire junior people and to promote competition.
Private funding increases, not only in the form of
industrial contract research, but also in long term
support for exploratory research and education via
private foundations. The variety of funding sources
therefore increases greatly. These new sources
invariably adopt competitive rules for project
selection and for recruitment.
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At the European level, this scenario implies the
direct involvement of researchers into large research
networks, mainly promoted by private companies
and multinational companies (MNCs), which provide
the bulk of funds to universities.
The Future of Key Research Actors in the European Research Area
Table 8
Four scenarios
Functions and
Researcher as civil servant
operationalisation variables
Production of new knowledge
Frontier research
Strong disciplinary
boundaries limit frontier
research
Rate of growth
Public funding limits rapid
growth in emergent areas
Degree of diversity
Limited
Complementarity
Limited
Circulation of valid knowledge
Scientific publishing
Diffused but only within
public researchers
Other sources excluded
Knowledge sharing
Legitimation
Legitimation
70
Selection
Size of the market
Criteria for selection
The return of
national policies
Knowledge as a
private good
Government strategic
decisions
European
competitive ecology
Massive inflow of private
investment into highachieving universities
Government try to spot
Highly selective dynamics:
emerging areas and fund
some areas thrive, others
them centrally
stagnate
Governments try to follow
Diversity is nurtured only in
many directions, usually with areas close to commercial
no success
applications (e.g. life
sciences)
Large physical facilities
Large strategic programs with
centralised governance
Public and private
collaboration and
competition
Institutions position
themselves at different rates
of growth
Diversity is systematically
enhanced by different types
of institutions
Diffused
Diffused
Ethos of disinterested public Less important
circulation of knowledge
No application considered
Diffused but with strict
implementation of
Intellectual Property Rights
(IPRs)
Strong restrictions from
patents and copyrights
Different regimes of IPR
protection depending on
the field
Private-public cooperation for
knowledge sharing
Strong enforcement of public Non-academic producers
certification criteria
legitimated according to
strategic priorities
Market reputation only
Market reputation with
regulatory framework
National
International
International
Pure competition
Mainly competitive
High
Variable according to the
institution
Relative pay
Public
Bureaucratic
Collusive
Low
S&T researchers
Limited attraction
National with limited
European integration
Limited competition in
strategic programs
Collusive elsewhere
Low in academic system
Incentive pay in strategic
programs
Attraction in strategic
programs with careers and
working conditions beyond
the norm
Funding
Role of public funding of
research
Strong attraction due to the Strong attraction due to
possibility to do training and the quality of research, but
move to the private sector
problems with disparity
of treatment in various
institutions
Very strong
Normal in academia
Government commitment but Extraordinary for strategic
limited budget
priorities with special funding
schemes
Emergence of different layers Limited
Limited
of public funding
Mostly public
Mostly public with some
involvement of large private
companies
Diminishing
Variable according to types of
institutions
Extremely diversified layers
Strong role of private money
and competition for student
fees
Contract research
Very high
Extremely diversified layers
Strong role of private
foundations, donations, and
alumni
Quality attracts international
funding
Moderate
Industrial funding
Student fees
Variety of funding sources
Accountability
Accountability
Relevance
Production of new public
goods
Limited
Mostly free research
Limited
Very high
Low
Low
Very important in priority
Fundamental
areas
Low
Very high
Low except special programs High
Important in some cases, not
in general
Variable
Very high
No need to demonstrate
anything to public opinion
and pressure groups
Mainly to the business
community and to funding
agencies/ governments
Extended accountability to
public opinion and advocacy
groups, business community,
governments, private donors
Intrinsic to the mission
No proactive policy
Neglected, apart from
Strongly neglected
environmental and energy
issues
Strongly encouraged through On a purely commercial basis
proactive policies
Production of new collective Excluded
goods
Strong negative reaction
Cultural resistance
Extended accountability to
students and their families,
governments, business
community
Taken on board by particular
institutions
Important for all institutions
but division of labour takes
place among institutions
Some specialise in third
mission activities
4
W o r k in g
SMEs
Paper
Bart Clarysse, Ghent University and Vlerick Leuven Gent Management School
The result was an increasing lack of consensus
among academics about the growth potential of
these companies. In fact, some academics started
to argue that at least in Europe, research-based
start-ups do not grow at all (Autio and Lumme,
1999). The academic community searched for more
theoretical reasons why so few consistent results
were found among this group of companies and
found that, from a policy perspective, differences
should not only be made based upon the technology
(new technology versus traditional sectors), but also
among the institutional origin of companies and the
growth ambition of the entrepreneur. Subsequently,
scholars started to examine subpopulations such as
the corporate spin-offs. These are companies that
are founded as a spin-off from larger, established
firms. They usually take the knowledge or technology
developed at the parent institute as a core asset to
start from. Because of this existing knowledge, they
seem to have a competitive advantage over other
new technology based firms to overcome the liability
of newness and subsequently exhibit larger growth
rates. Because of their growth potential, policymakers have become interested in the innovative
potential which established firms have and their
willingness towards spin-off corporate ventures.
Not only do research-based start-ups differ in the
nature of their origin, they also differ in the extent
to which they attract external capital at time of
founding. A very particular category of external
investors are the venture capitalists (VCs). Among
other things, they seem to have a specific capability
to pick the potential growers. Hellman and Puri
(2001) performed a distinct and extensive analysis of
this particular group of venture capital backed SMEs.
VCs provide the financial resources to overcome the
liability of newness and they are assumed to help
the companies to realise their growth potential.
Although they are often expected to play a role in
financing the technology developments in small
start-ups, in reality they seldom invest in high-tech
start-ups. About 90 per cent of the European VCs
invest in non-high-tech start-ups or traditional SMEs
that want to realise a turn-around.
Summarising, we observe that SMEs differ according
to the ‘institutional link’ they have with their parent
organisation (i.e. corporate, academic, none),
the financial resources they are able to collect to
overcome the liability of newness (VC-backed or not)
and their history (technology start-up, established in
the 1990s, or generation SME in traditional sectors).
It is important to understand each of these categories
in detail and to analyse potential scenarios. The
remainder of the paper is organised as follows. First,
71
Paper 4
SMEs
I
ncreasingly, SMEs and especially the subpopulation
of research-based start-ups are assumed to play an
important role in today’s knowledge based economy
(Bollinger et al., 1983; Utterback et al., 1988; Acs
& Audretsch, 1990; Kirchhoff, 1994; Paasi, 1999).
However, different economic and societal forces have
an impact on these organisations. Despite this romantic
perception in the mid-1980s, in the mid-1990s very
few of these companies were meeting expectations
and their role in the economic environment was
questioned. Different reasons were put forward as to
why these companies fell short of meeting objectives:
they were too technology push; they were having
difficulties in getting access to international markets;
their technology was too immature...
It is not only the corporate spin-offs which have
become the subject of research and policy interest.
Academic spin-offs, which are ventures that come
from universities or public research institutes, have
also received increasing attention. Academic spinoffs have become an alternative for some universities
to transfer technology and commercialise research
results next to contract research and license
agreements. There are several reasons why they
form a separate group of SMEs: their founding teams
usually lack experience, the technology/IP needs to
be valued in the starting capital of the company etc.
This often forces the parent institutes to bring in
external investors at a very early, pre-seed, stage in
these companies.
Wo rki ng
1. Introduction
The Future of Key Research Actors in the European Research Area
we give a literature review regarding the different
types of companies described above. Second, we
discuss the challenges that these firms are faced
with in the long run. The final part of the paper draws
some scenarios as to how the relative importance of
these different groups of companies will evolve over
time for knowledge production and diffusion.
2. D
ifferent types of
SMEs
Figure 1
History
Different Groups of Actors
Traditional
SME
Ct V ed
No ack
b
e
ck
ba
VC
d
Start-up
Fi
Re nan
so ci
ur al
ce
72
SMEs are not a homogeneous group of organisations.
We can distinguish between ‘SMEs in traditional
sectors’ on the one hand and ‘Research Based StartUps’ on the other. The latter form a mix of companies
including ‘corporate spin-offs’, ‘academic spinoffs’, ‘independent new technology based firms’
and ‘Venture Capital backed firms’. Although the
categories are not exclusive, each of these firms
has been treated as a distinct population in the
literature. We now provide a description of each of
these different groups.
Academic
Spinout
Corporate
Spinout
Institutional
Origin
Independant
NTBF
2.1 SMEs in Traditional Sectors
Today SMEs in traditional industries constitute a
significant force in our economy (Adame-sanchez et
al., 2001). They account for 60 to 70 per cent of all
employment (OECD, 1998a) and command two thirds
of sales volume in the non primary sector. Moreover,
most of the expansion in employment in Europe over
the past decade has been in small firms. Out of the
17 million enterprises in the private and non-primary
sector in Europe in 1993, 93.3 per cent were microfirms (having zero to nine employees), 6.2 per cent
were small (having ten to ninety-nine employees)
and only 0.5 per cent were medium-sized (having
100-499 employees). The European SME sector has
some notable strengths: strong business dynamics,
an increasing level of education of its entrepreneurs,
increasing internationalisation of trade, direct
foreign investment and strategic alliances. The
group of SMEs active in traditional sectors is a very
diverse group of companies. SMEs are most present
in construction, distribution and service sectors, but
are also powerful in some manufacturing industries
(Mulhern, 1995).
Typically, these companies are family controlled.
They have a more closed and controlled structure
compared to corporate and academic spin-offs and
new technology based firms. The management of
these companies is mostly performed by the owner.
They tend to have less venture capital and fewer
external shareholders on board; credits and loans
are still the main source of financing.
There is a growing consensus on the innovative
character of SMEs. Historically, SMEs in traditional
sectors were not perceived to be innovative.
However, today many studies have demonstrated
that smaller size is not necessarily an obstacle to
innovation (Chen and Hambrick, 1995; Julien et
al., 1994). Between 30 and 60 per cent of all SMEs
can be characterised as innovative (Göker, 1998).
Innovativeness in these companies can be found
in the application of new business models, new
services or in the improvement of existing products.
Adame-Sanchez et al. (2001) highlight the capacity
to adapt to change as a main condition for the
survival and growth of SMEs specialising in mature
sectors. More and more SMEs are increasingly aware
about the importance of innovation. Some studies
even conclude that innovative activities are the most
important determinants of success (Baldwin, 1995).
It is striking to see that SMEs in traditional sectors
form a major part of the most rapidly growing
companies. The drivers for this growth are little
known as this is a field of study scarcely researched
to date. Further research also needs to be conducted
into the role of innovation in the growth of these
companies. More remarkably still, growth as such is
less a focus of these companies than for the researchbased start-ups. SMEs tend to have a longer time
focus and initially strive simply for survival. The
knowledge embodied in these companies is often
formed in the long tradition of the founding team
in the sector. This prior knowledge which often
consists of experience and commercial networks is
an advantage over newcomers to the sector. Reduced
communication costs and easy transport make it
easier for SMEs to enter international markets.
The term ‘New Technology-Based Start-ups’ was
first introduced by A.D. Little (1977) and he defined
these firms as ‘independent firms established
within the last 25 years for the purpose of exploiting
an invention or a technological innovation which
implies substantial technological risks’. Although
appealing, researchers argued that this definition
of ‘new technology-based firms’ is difficult to use in
research (e.g. Storey & Tether, 1998). One approach
to solve this is narrowing down the definition,
referring to new independent firms, developing
new industries, only. Other scholars decided to use
a much broader definition which in turn sometimes
resulted in an ambiguous conceptualisation of
NTBF. Rickne (2000) pointed out that this multitude
of definitions and approaches has impeded the
comparison of different studies on NTBFs. To
overcome any conceptual confusion, Heirman and
Clarysse (2004) have introduced the term ‘researchbased start-ups’ (RBSUs), referring to the intrinsic
research intensity and riskier character of NTBFs as
compared to traditional SMEs. RBSUs are defined as
new business start-ups, which develop new products
or services for the purpose of commercialisation.
Using a cluster analysis, Heirman and Clarysse
(2004) identified four types of RBSUs, depending on
the configuration and development of the financial,
human and technological resources during the
life cycle of the company. The first type of RBSUs
are the prospectors, founded by teams with little
management experience and with technology which
is still in an early phase of development. In order to
attract experienced management and to stimulate
the technology development, the prospectors
search for external financing in vain. Conversely,
the venture capital backed RBSUs succeed in
convincing an institutional or corporate investor.
The technology of the VC-backed RBSU is often a
platform technology allowing the development of
a portfolio of applications. The external financial
means allow the VC-backed RBSU to attract
experienced management and to fuel technological
The resources of a firm during its early years of
existence are of crucial importance for RBSUs to
develop and create a competitive advantage (Teece,
1997). In addition, several researchers argue that the
initial resource-base of a start-up play an important
role in the growth path and later performance of the
firm (Stinchcombe, 1965; Boeker, 1988).
Inspired by some visible success stories in the 1980s
and the early 1990s, policy-makers pictured RBSUs
as the vehicle to create economic growth in a region.
This romantic view on the growth of RBSUs has been
argued by several researchers. In contrast to the
overall growth perception of RBSUs, the vast majority
of these companies do not grow at all and remain
small (Autio & Yli-Renko, 1998; Chiesa & Piccaluga,
2000). Focusing on the imprinting effects of the
initial resource-base, Heirman and Clarysse (2005)
show that financial means and human resources at
start-up are important determinants of early growth.
RBSUs that succeed in attracting the necessary
financial means to commercialise their product show
excessive growth, especially in employment. The fact
that the commercial experience of the founding team
has a very strong impact on the growth of the RBSU
is a very important finding from a policy perspective.
Governments traditionally support start-ups in the
technological development of their products. Policy
measures to support the commercialisation of
innovative products on the other hand are scarce. As
a result, policy-makers should not only provide R&D
subsidies but also take initiatives to enhance the
commercial skills of founders.
2.3 Corporate Spin-offs
In today’s innovation–driven world, knowledge and
learning are key factors that foster competitiveness
and growth. Corporate spin-offs (CSOs) are a result
and a driver of change to a knowledge-driven
economy. The specific nature of CSOs makes them
an important and pro-active element within the
knowledge economy. Already existing knowledge
73
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SMEs
2.2 Independent New Technology Based
Firms
developments. A third type of RBSUs are the socalled ‘product start-ups’, founded by inexperienced
teams which have a market-ready product. Expecting
revenues shortly after start-up, the product startup doesn’t look for external financing. Finally, the
transitional start-up is typically founded by former
consultants. This type doesn’t have a concrete
product idea and focuses instead on services. The
shift towards product development is market driven.
During their consulting activities, the transitional
start-up identifies a market opportunity which is
exploited to develop a product.
Wo rki ng
Although only approximately 10 per cent of SMEs
are technology-based (Göker H.A., 1998), these
technology-based companies or research-based
start-ups have received significant attention both
from academics and policy-makers. We have defined
these companies into four categories: independent
New Technology-Based Firms (NTBFs), academic
spin-offs, corporate spin-offs and VC-backed
companies. We discuss each category subsequently.
The Future of Key Research Actors in the European Research Area
and experience is newly shaped and combined
into a new product or process. According to expert
estimations, they make up for around 12.9 per cent
of new firm formation in the EU (Tubke, 2004).
CSOs use active relationships and networking as a
strategic success factor. The CSO process leads to
a shift from internalised to externalised knowledge
and from organisational to individual responsibility.
In addition, CSO processes involve economic,
organisational, and knowledge-related changes at
individual, organisational, local, regional, national,
and pan-national levels. They have been shown to
produce considerable impacts at all stages.
74
New firms spinning off from established ones are
not a new phenomenon, for example, the Volvo car
manufacturer was spun off from the bearing company
SKF as far back as the 1920s. The spinning off of
innovative ideas that fall outside the core business
of the parent organisation can create new business
opportunities that otherwise may not have been
commercialised. Corporate spin-offs are widespread
in industries such as semiconductors, disk drives
and lasers. Fairchild Semiconductor’s many spin-offs
(dubbed ‘Fairchildren’) are a salient example. CSOs
are often an efficient mechanism for the transfer of
knowledge from large established firms. They are an
important group to consider since they combine the
rapid growth of new firms with a considerably lower
failure rate than other types of start-ups (Tubke et
al, 2004).
CSOs are often the result of restructuring or
reorganisations of the parent company. They are
often undertaken for strategic or operational
motives related to the parent company, which might
be a consequence of restructuring or refocusing
activity. Activities that are not within the company’s
core competencies and that do not meet minimum
performance requirements are either closed down
or spun-off. However, the costs involved are crucial
in terms of the decision whether to spin-off or
close down an activity. Moreover, sectors with
high spin-off frequencies are sectors that undergo
a high level of cost-cutting activity. Deregulation
seems to have been one of the driving factors in
encouraging the emergence of CSOs in the energy
and telecommunications sector. CSOs might also
be formed when employees are not able to realise
their ideas in the parent company. These employees
want to exploit an unused potential based on their
key experience acquired within the parent company.
Some of them are frustrated because the parent
firm does not allow them to pursue an opportunity,
so they decide to leave the parent firm. Others spot
opportunities in the external environment and decide
to pursue the opportunity themselves, rather then
sharing it with the parent firm. Scholars have used
different definitions to identify CSOs. We define a
CSO as: ‘a separate legal entity that is concentrated
around activities that were originally developed in a
larger parent firm’.
Several studies have looked at the phenomenon
of corporate spin-offs and found that they create
excess stock return for the parent firm and the
corporate spin-off. For the parent firm, excess share
price improvements of about 3 per cent around the
announcement date of the spin-off have been found
(Daley et al., 1997; Schipper & Smith, 1983). Setting
up a CSO can allow the parent firm to focus its
activities and to reduce information asymmetry that
might exist due to the numerous activities of the
parent firm (Krishnaswami & Subramaniam, 1999).
Daley, Mehrotra, and Sivakumar (1997), and Desai
and Jain (1999) document a significant improvement
in operating performance in the year after the event
for spin-offs that separate divisions that operate
in different industries. Another explanation can be
found in the undoing of earlier unwise acquisitions.
Allen et al. (1995) found that when a spin-off is
preceded by the acquisition of the division the
positive abnormal returns around the spin-off
represent the re-creation of value that was destroyed
at the time of the earlier acquisition.
In the studies mentioned above, the parent is the
initiator to create the CSO. However, a number of CSO
are set up by employees of the parent firm. In this
case, employees want to exploit an unused potential
based on their key experience acquired within the
parent firm. Authors studying this group of employeebased CSOs have focused on the relatedness
between a CSO and its parent firm. These studies
have found mixed support for the hypothesis that a
CSO benefits from ties with its parent. Sapienza et
al. (2004) found that production and technological
knowledge relatedness is related to growth, but
marketing knowledge has no significant relation. On
the other hand, Davis et al. (1992) found that a high
level of marketing relatedness is associated with
high sales growth. Others have reported positive
relationships between technological relatedness
and sales growth (Doutriaux, 1992), between overall
relatedness and profitability (Woo et al., 1992) and
between production relatedness and return on
assets (Davis et al., 1992). Further, some studies
have found no relationship between relatedness and
market share (Sorrentino and Williams, 1995).
Few studies have compared the group of corporate
spin-offs to other groups such as university spin-
Studies report that European research labs,
traditionally closely tied to government and
enshrouded in the cocoon of academia, are
increasingly involved in spinning off ventures.
Moreover, these companies are argued to play an
increasing role in economic development (OECD,
2003). The increased policy interest in generating
commercial gains from publicly funded research
and the growing recognition by academics of the
market opportunities for their inventions has
fuelled the fact that research-based spin-offs
(RBSOs) have become an important aspect of the
technology transfer process (Di Gregorio & Shane,
2003; Wright, Birley & Mosey, 2004). In this context,
universities and research institutes alike have
increasingly developed internal systems for the
commercialisation of their technology. Since a lot
of products and processes currently on the market
could not have been developed without scientific
research (Mansfield, 1998), the OECD has stressed
the importance for research organisations to
develop structures and formal policies to facilitate
the transition from research to the creation of new
spin-offs (OECD, 1998).
This growth in spin-offs has become an international
phenomenon (Clarysse, et al., 2005) and has
stimulated academic and policy debate regarding
whether and how RBSOs create wealth (Lambert,
2003). Beneath the superficial expectation that
all spin-offs will create significant wealth, and
consequent policy reassessment when they do not,
is the growing recognition of the need to understand
the heterogeneity of RBSOs, of their objectives
and of the context in which they occur. Generally,
both NTBFs and RBSOs face similar difficulties in
Traditional pioneering studies of new technology
based ventures have identified typologies but have
not separately identified RBSOs. For example,
Jones-Evans (1995) develops a typology based on
previous ownership backgrounds of entrepreneurs.
Autio (1997) provides a typology based on science
versus engineering based technology ventures in the
context of the linkages with their environment. While
there is growing recognition of the heterogeneity of
high-tech ventures, studies have tended to be unidimensional. Bullock (1983) identified two categories:
‘soft companies’, the technical consultants solving
customised problems, and ‘hard companies’ that
sell standardised products to a general market. In
parallel, Stankiewicz (1994) classifies the NTBFs
according to the way they operate. He identifies
three different operation modes: consultant and
R&D boutique mode, product-oriented mode, and
technological-asset mode. Mangematin et al. (2002),
in turn, consider the heterogeneity of trajectories
of biotechnology ventures in France in terms of
whether their business models involve small, less
research intensive projects targeting market niches
or research intensive projects targeting broader
market types.
Both academics and policy-makers have been
developing a variety of definitions for researchbased spin-offs. A common two-dimensional
definition of an RBSO is a new company that is
formed (1) by a faculty member, staff member or
doctoral student who left university to found the
company or started the company while still affiliated
with the university, and/or (2) a core technology (or
75
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SMEs
2.4 Academic Spin-offs
establishing a market presence and in achieving
sustainable returns. However, RBSOs also face two
fundamentally different problems (Vohora, Wright
& Lockett, 2004). First, emanating from what is
historically a non-commercial environment, RBSOs
face specific obstacles and challenges since the
university environment typically lacks commercial
resources, in particular academic entrepreneurs with
commercial skills to create viable ventures. Second,
the venture’s ability to develop commercially may
be adversely impacted by the conflicting objectives
of central stakeholders such as the university, the
academic entrepreneur, the venture’s management
team and suppliers of finance. For example, Clarysse
et al. (2005) highlight the problems of conflicts
between stakeholder objectives with regard to the
type of ventures they wish to create. RBSOs thus
pose major challenges if they are to realise their
potential to meet the objectives of their founders
and the parent research organisations (PROs) from
which they emerge.
W o r ki ng
offs. A Swedish study compares university spin-offs
with corporate spin-offs and New Technology Based
Firms (Lindholm, 1997). Compared to university
spin-offs, CSOs are reported to be more innovative
firms putting a stronger focus on the exploitation of
their inventions. With respect to similar non-spin-off
companies, CSOs are more innovative and focused
on their customers. They combine existing process
technologies, which are often similar to those of the
parent, with a leaner organisation that permits them
to produce more innovative, tailored products at
lower costs than their competition. At the European
level, corporate spin-offs are estimated to produce
an above average net employment growth of at least
8 per cent (Tubke, 2004). Despite of the diversity,
most studies on CSOs tend to conclude that they are
beneficial for the parent firm and perform well.
The Future of Key Research Actors in the European Research Area
76
idea) that is transferred from the parent organisation
(e.g. Smilor et al., 1990; Steffenson et al., 1999). The
OECD posits that a spin-off is a company that meets
at least one of the following criteria: (1) one of the
founders is an employee of the public research
organisation (PRO), (2) the company licenses a
technology from the PRO, (3) a PRO has equity in
the company or (4) the PRO directly established the
company (Callan, 2002). The latter criterion opens
up the distinction between spin-offs that are set up
with the support of the parent organisation – push or
passive spin-offs – and ventures that are established
without participation or support from the parent
organisation, the so-called ‘pull’ or ‘active’ spinoffs (e.g. Matkin, 2001). Another inclusive, broad
definition has been proposed by UNISPIN, a project
of the 4th Framework Programme of the European
Commission: a spin-off is a new firm that is largely
dependent on knowledge/research from a public
research organisation for its establishment (Callan,
2002). The Association of University Technology
Managers (AUTM)1 suggested making a distinction
between companies established with and without
formal transfer of technology at time of founding.
They refer to the companies as ‘spin-offs’ and ‘startups’ respectively. Spin-offs denote all the companies
or traders as persons engaged in businesses that
were dependent upon licensing or assignment of the
institution’s technology for initiation. Conversely,
start-ups are those companies that were not
dependent upon licensing or assignment of the
institution’s technology for initiation. However, the
business was established based on the research/
knowledge base of the PRO. Although there is no
formalised technology transfer, it is possible that
the PRO holds equity in these companies.
In Europe, researchers have included both spin-offs
and start-ups in their databases, using a variety
of inclusion criteria. This makes the comparison
of European research results very difficult. In fact
we observe that a lot of research-based spin-offs
do not receive a formal transfer of technology, but
in fact are still identified as a spin-off company. In
Flanders, for example, we have identified the total
population of research-based spin-offs based on the
listings from the technology transfer offices (Moray,
2004). From the 93 firms that were set up from 1991
to 2002, 40 are companies that started activities
without a formal transfer of technology. Although we
have no exact figures for other European countries,
researchers in Italy, France and Portugal make
similar observations (PRIME Network of Excellence,
2004).
1.http://www.autm.net
2.5 Venture Capital Backed Firms
According to Heirman and Clarysse (2004), about
10 per cent of all start-ups are backed by venture
capitalists (VC). Similar findings were reported by
Burgel and Murray (1998), who found that 10 per
cent of a sample of NTBFs was VC backed. Venture
capital is defined by the European Venture Capital
Association as professional equity co-invested with
the entrepreneur to fund an early stage or expansion
venture. Given that the venture capitalist takes a
high risk at the moment of the investment, an above
average return on investment is expected.
Venture capitalists operate in environments where
other financing parties, such as banks and business
angels are less likely to invest given the perceived
risk and the cost of problems arising from information
asymmetries. On the one hand, these information
asymmetries may give rise to adverse selection
problems. In this case, the entrepreneur possesses
more information on the potential of a product or
technology and may overstate this potential, which
makes it extremely difficult for the VC to distinguish
between good-quality and bad-quality proposals.
On the other hand, these information asymmetries
may give rise to moral or ethical problems, with the
entrepreneur taking actions that are beneficial to
himself, but not necessarily to the investor. Amit et
al. (1998) state that VCs emerge exactly because
they develop specialised abilities in selecting and
monitoring entrepreneurial projects.
Since the original ‘theory of the growth of the firm’ in
Penrose (1959), several factors have been suggested
as affecting growth. These factors can be internal
to the company, such as financial, organisational,
human and technological factors, and are addressed
by the resource-based theory of the firm. Other
factors are external, and comprise the market forces
and environmental carrying capacity (Aldrich, 1990;
Singh and Lumsden, 1990). There are three main
factors that cause venture capital financing to be
different from other types of financing. First, VCs
carefully scrutinise the founders and their business
concepts (Fried and Hisrich, 1994) and are expected
to select those investments that have high growth
potential.
Second, they are involved in monitoring and valueadding activities (Sapienza et al., 1996; MacMillan
et al., 1988). VCs are mainly involved with valueadding activities in order to improve outcomes of
their investments (Repullo and Suarez, 1990). While
entrepreneurs specialise in the development of
knowledge about combining resources to exploit new
Therefore, venture capitalists invest in environments
where their relative efficiency in selecting and
monitoring investments and providing value-adding
services give them a comparative advantage over
other investors. Therefore, VCs are expected to
be prominent in industries where informational
concerns are important, such as biotech, ICT,
etc. (Amit, 1998). Researchers have found that
other types of financing, such as business angel
financing, bank loans, subsidies, money from the
entrepreneur, 3F(friends, family and fools) are either
insufficient or inappropriate to fully exploit the
rapid growth potential of a new technology (Oakey,
1984; Westhead and Storey, 1995) and to bridge the
liability of newness at a sufficiently high speed.
There is however no consensus on the impact of venture
capital on company performance and growth. Some
researchers have found that VC encourages efficient
capital allocation (Chan, 1983; Sahlman, 1990), whereas
other state that the most promising entrepreneurs will
not seek venture capital financing (Amit et al., 1990).
Also empirical research on differences in performance
between VC-backed and non-VC-backed companies
has produced mixed results. Some studies indicate
that those start-ups that succeed in attracting venture
capital outperform those that do not in terms of time
to market (Hellman and Puri, 2000), innovative activity
and the number of valuable patents (Kortum and Lerner,
2000) and employment and revenue growth (Heirman
and Clarysse, 2005). Other studies have shown that
3. Changes in the
Innovation System
A discussion of which challenges SMEs will
experience in the future and how they might
respond to these challenges should include at least
a view on how innovation is expected to change in
the future. Chesbrough (2003) has been one of the
most influential management gurus and promotes
the idea of an open innovation system. In the past,
companies usually innovated according to a closed,
pipeline kind of system. In such a closed system,
a large company manages the whole process of
innovation, ranging from idea generation to the
launching of products onto the markets. This means
that the company hardly makes use of other actors in
the innovation system to develop its new products.
In his seminal work on open innovation, Chesbrough
identifies a number of factors that have changed the
economic system and that make a closed system
difficult to sustain. These factors are (1) the increased
mobility of researchers, (2) the evolution on the risk
capital market and (3) the professionalisation of
the market for new ideas. We discuss each of these
factors in the next paragraphs.
3.1 The Increased Mobility of Researchers
The number of researchers and scientists has
increased enormously during the last 25 years.
Whereas after the second world war, engineers
and scientists were very scarce and hardly to be
found outside the larger, established companies,
nowadays the stock of engineers has become very
large. This means that the R&D departments of
large companies no longer possess a monopoly
over engineering and scientific talent. Also SMEs
and public research centres have become significant
centres of knowledge. In parallel with this evolution,
the principle of life time employment has lost its
overwhelming importance. Scientists and engineers
tend to flow from one job to another much more
than twenty years ago. This mobility has become a
self-fulfilling prophecy. Because the engineers and
scientists switch much more from one job to the
other, in many places they find a critical mass of
knowledge that is large enough to attract them.
77
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Third, VCs can bring a reputation effect that facilitates
growth (Davila et al., 2003). This reputation effect
may however be highly dependent on the reputation
of the VC that invests. Indeed, Megginson and Weiss
(1991) indicate that the reputation of some longexisting VC companies is second to none, and their
presence in the capital structure sends a strong
positive signal to other investors and stakeholders.
start-ups that receive venture capital need more time
to ship their first product for revenues (Schoonhoven
et al., 1990). A study by Manigart et al. (2002) indicates
that VC-backed companies have a lower probability
of survival and a higher probability of going bankrupt
compared to non-VC-backed ones.
Wo rki ng
opportunities (Kirzner, 1973) and in the day-to-day
development of new business activities (MacMillan et
al., 1989), VCs focus mainly on creating networks to
reduce the cost of acquiring capital, to find customers
and suppliers and to establish the venture’s credibility
(MacMillan et al., 1989; Lam, 1991). This involvement
in value-adding activities is however dependent on
the portfolio company’s characteristics and the VC’s
characteristics. Venture capitalists are for instance
more involved with innovative companies and
companies in an early stage of development (Sapienza
et al., 1994). Knockaert et al. (2005) show that the
level of involvement in value-adding activities is highly
dependent on sources of funds obtained by VCs and
the human capital of their investment managers.
The Future of Key Research Actors in the European Research Area
3.2 The Evolution of the Risk Capital
Market 2
SMEs finance their businesses in different ways.
The traditional SMEs most often use private money
and bank loans to start their activities. According to
Heirman and Clarysse (2004) most research-based
start-ups become established without external
financing. The aforementioned product based startups need external financing however, as they have
to recruit people in order to bring their product to
the market, may outsource production and often
need resources to further develop their product.
They often use suppliers’ credit or have social debts
in order to cover their first financing needs.
78
Since the mid-1990s, the availability of risk capital
has increased enormously (Keil et al., 2004), both
allowing large companies to spread their risks and
collaborate with financial investors and giving rise to
the availability of risk capital for high and medium tech
companies. The classic role of venture capitalism is
the supply of capital to risky new, small and innovative
enterprises that have difficulty raising such capital
from other sources (Bishop, 1996). However, quite
a lot of researchers have indicated that, compared
to the US, European venture capitalists have a bias
against investing in early stage high-tech companies
(Martin et al., 2002; Bottazzi and Da Rin, 2002;
Lockett et al., 2002). European VCs prefer to invest
in later, less risky stages and impose more stringent
selection criteria to technology projects compared
to non high-tech projects (Lockett et al., 2002). So
it seems that the average European VC is not really
taking on the classical role of venture capital when
investing. Venture capital in the US however has had
a much longer tradition than it has had in Europe.
Venture capitalism in Europe – including the UK – got
under way in a significant form only in the late 1980s.
Most of the growth of the industry has occurred since
the mid-1990s, especially at the end of that decade.
The European VC industry obtained its record level
in 2000, raising €48 billion. The UK still represents
by far the largest venture capital market, accounting
for around 44 per cent of the total in 2001 (Martin et
al., 2002), and the most similar with respect to size,
maturity and type of VCs to that in the US (Sapienza et
al., 1996). In comparison, the venture capital market
in the US first developed in the 1950s and 1960s. It
grew slowly in the 1970s, but then began to take off
in the 1980s (Gompers and Lerner, 2001). In recent
years it has expanded dramatically, investing a total of
2.Knockaert, M. (2005) Does Venture Capital Matter for High Tech Start-ups?
An analysis of European Early Stage Investors. Doctoral dissertation,
September 2005.
USD104.3 billion in 2000. It is estimated that between
a third and a half of US venture capital funds have
been invested in high-tech sectors. Venture funds for
MBOs in the US typically account for less than 5 per
cent of total venture investment (Martin et al., 2002),
even though differences between the US and the UK
should be interpreted with caution given that most
US statistics only take into account early stage and
development industry, with the EU data covering the
whole private equity industry. As Murray and Marriott
(1998) indicate, it is the ability of the US venture capital
industry to continue to invest predominantly in young
technology-based ventures which differentiates them
from their major European counterparts.
The proportion that the European industry devotes to
management buy-outs is much larger than that of the
US. In the US, venture capital usually refers to equity
for seed, start-up and expansion activity. Even taking
into account these definition differences, we can say,
as Murray (1999) notes, that the European venture
capital industry is basically a ‘development capital’
industry. This is supported by an analysis of the
EVCA data (EVCA, 2004). Figure 2 shows the amounts
invested per investment stage over the last years.
Figure 2
Amounts invested in Europe per stage
100%
6 663 403
4 183 799
2 930 688
80%
70%
7 796 736
13 916 398
2 139 293
8 533 380
9 202 988
60%
50%
40%
30%
14 405 952
16 920 576
18 423 246
2002
2003
10 944 574
20%
10%
0%
2000
2001
Year
Early phase
Expansion/replacement
Buyout
Source: EVCA (2004).
The industry invested a total of €29 billion in 2003.
Only €2.14 billion (or 7 per cent) went to companies
in their early stage of development, and €6.95
billion (or 24 per cent) was diverted towards hightech investing. About 5.9 per cent of the funds raised
in 2003 were expected to be allocated to early stage
3.3 The Increased Professionalisation of
the Market for New Ideas
Two decades ago, the ideas market was
underdeveloped with knowledge as a source of
innovation strongly embodied in individuals and
single organisations., However, given the increased
capability of other actors in the value added chain,
it is increasingly possible to realise opportunities
for knowledge production and diffusion outside the
parent organisation. Initiatives for innovation come
more and more from other actors in the value chain.
In the Fast Moving Consumer Goods Industry for
example, the suppliers of packaging materials are
the ones stimulating innovation in the sector more so
than the companies producing the consumer goods.
Historically, companies performed most of their
activities independently from each other. Today,
multinationals are much more involved in setting up
Figure 3
Open Innovation
79
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SMEs
Some researchers indicate that, given the
disappointing risk adjusted returns to early stage
high-tech investments, this reluctance towards
early stage high-tech investing may have been quite
rational (Sahlman, 1990; Amit et al., 1990; Lockett et
al., 2002). Based on a study of Venture Economics
and Bannock Consulting (1997), Murray and Marriott
(1998) report pooled IRRs for early stage investments
of 5.7 per cent per year, and 17.6 per cent for MBO
funds. If we compare these reported IRRs to the last
available ones, from a similar study by Thomson
Venture Economics and EVCA (2004) over the year
2003, we find that the situation has deteriorated
due to the Internet and dotcom crisis. Pooled IRRs
per year for early stage investments were 1.9 per
cent compared to 12.2 per cent for MBO funds.
incubators, collaborating with SMEs much earlier
in the development process etc. The increasing
complexity of knowledge and the quicker pace of
knowledge production have led companies to search
for new ways to manage their innovation process. In
practice, this often means that the central R&D lab
is no longer the sole privileged supplier of ideas.
Universities, research institutes, high-tech startups and other companies have increasingly become
important sources of new knowledge to remain
at the forefront of new developments. Second,
companies increasingly look for commercialisation
opportunities outside their traditional product
portfolio or existing markets. Licensing, joint
ventures and establishing spin-off companies have
become logical alternatives. Third, having a firstmover advantage is increasingly seen as a superior
asset over the defensive protection of knowledge
and technology. The open innovation system is
presented in figure 3.
W o r ki ng
high-tech investments. The European high-tech
venture capital industry is cyclical by nature. Due to
the dotcom and internet debacle, investments in and
amounts raised for high-tech investing fell sharply.
For instance, in 2001 funds raised for investment in
early-stage high-tech companies decreased by 35
per cent to €5.6 billion, compared to 6 per cent for
funds directed to non high-tech companies the year
before. The reluctance towards investing in early
stage companies and the fact that the IT crisis has
impacted the VC investment preferences with respect
to stage can clearly be seen in Figure 2. The internet
debacle seems to have affected the entire VC industry
with total amounts invested dropping from €34.9
billion in 2000 to €29 billion in 2003. It seems that
the industry has shifted from investments in early
stage companies and companies in the expansion
phase towards the less risky MBO business.
The most important implication of an open
innovation system is that the detection of
interesting technological and latent market trends
are at least as important as performing the R&D
itself. Companies should establish a capability that
allows the recognition of opportunities as much as
possible. Instruments such as ‘technology watch’
and ‘technology roadmapping’ can support this
process. Also, lead users should be involved in the
problem solving at a very early stage (Allio, 2004).
Using external knowledge to generate ideas is also
an inherent part of the trend towards more open
innovation trend (Linder et al., 2003). Industry
experts are included in internal brainstorming
sessions to come up with ideas about how a
company could innovate in the future. In conclusion,
research that used to be a private matter for the
companies is increasingly subject to a much more
open communication.
The Future of Key Research Actors in the European Research Area
revenues and value added compared to RBSUs (see
Figure 5). Although this may partly be explained by
the lack of growth ambition of the entrepreneurmanager, the SMEs in traditional sectors represent
the largest group, which make them very important
actors in terms of employment and opens up large
possibilities for growth driven by innovation.
4. Challenges for the
different groups of
SMEs
Each of these actors is supposed to play a major
role in the knowledge generation, production and
diffusion for tomorrow’s economy. However, they
also face major challenges to start playing and then
sustaining this role. In this section, we summarise
the challenges faced by each of the organisations.
Figure 5
Growth rate of traditional SMEs as compared
to RBSUs (data for Flanders, companies set up
between 1991-2002)
SMEs in traditional sectors
4.1 Traditional SMEs
80
160
Figure 4
Export of traditional SMEs as compared to
RBSUs (% of total exports) (Data for Flanders,
companies set up between 1991-2002)
Research-Based Start-Ups
80
70
60
50
40
30
20
120
100
80
60
40
20
0
Total Assets
Revenues
Value Added
Full Time
Equivalent
Employees
In order for European SMEs to survive in the new
globalised economy they should focus more on
innovation-driven growth. Although more companies
are becoming aware of the importance of innovation,
still only few of them are explicitly striving towards
innovative activities. Even though some policy
measures have already been taken to further stimulate
innovation in these companies, we believe greater
attention should be paid to this concern in the future.
Another point of concern in the future is the financial
management of SMEs. According to the UEAPME, SMEs
are facing more difficulties in accessing finance due
to restructuring and an ongoing focus on profitability
in the finance sector. This shortage of finance is a
relevant constraint to the potential contribution of
SMEs to growth and employment in the EU. Therefore
strong attention should be paid to the improvement of
the framework conditions for SME finance.
4.2 I ndependent New Technology Based
Firms
10
0
140
Growth ratio
SMEs in traditional sectors are confronted with
two main challenges. First, they are experiencing a
complex mix of opportunities and threats posed by
the globalisation of markets. Increasingly SMEs will
have to cope with the fierce competition of other
SMEs located in less developed countries, which
can benefit from cost advantages over European
SMEs. On the other hand, SMEs should try to take
full advantage of the export market opportunities.
It is alarming to see how most European SMEs
remain highly dependent on their domestic market.
Figure 4 illustrates this for a representative sample
of SMEs and RBSUs in Flanders. Almost 80 per cent
of the SMEs in traditional sectors do not export at
all whereas about 50 per cent of the RBSUs display
export activities representing more than 50 per cent
of their total sales.
SMEs in traditional sectors
Research-Based Start-Ups
0%
1–9%
10–50%
> 50%
Second, traditional SMEs display much lower
growth rates in terms of employees, total assets,
Different technological and structural evolutions
made it easier for SMEs to participate in the
international economy. In particular, the Internet
and its rapid growth blurred the borders between
In contrast to MNEs, which have very large stock
in resources, RBSUs are notoriously resource-poor
(Doutriaux, 1992). Welch and Luostarinen (1988)
show that RBSUs lack the necessary time, capital
and capabilities to adequately penetrate foreign
markets. Several researchers show that RBSUs can
overcome these limitations by creating a network
of partners with complementary resources and
capabilities (e.g. Birly, 1985). By tapping into the
resource and knowledge base of their network,
RBSUs can accelerate their learning process (YliRenko et al, 2001) and leverage their legitimacy and
reputation (Uzzi, 1997).
4.3 Corporate Spin-offs
Parent firms have used CSOs in the past as a way
to downsize business units to avoid problems with
unemployment or bad reputation. In recent years,
CSOs have been set up as a way to commercialise
radical innovation projects. Looking at radical
innovation projects in large established firms, one
could deduct that CSOs might be the ideal way of
commercialising radical innovation projects. On
the one hand, the CSO can take advantage of the
link it has with its parent e.g. sharing of resources:
it can use the technical resources and knowledge
present in the parent firm, it may be backed by
financial resources of the parent firm, or it can
have a competitive advantage by being connected
It is necessary to examine the role a CSO can have
in shaping an industry and keeping its parent
competitive. A CSO could be set up to explore and
commercialise radical innovation projects. Once the
CSO has a viable business model and generates
revenues, the parent firm can spin the CSO back in.
For the parent firm, the spin-in is a safe bet since
the CSO has already proven its value. On the other
hand, since the CSO has already passed the start-up
phase, the chance of surviving in the large parent
firm is much higher. After a few years, the CSO has
been able to validate its business model, attract
its first customers and generate revenues. The CSO
has grown in size and importance which contributes
to its legitimacy as a company and/or business
unit. CSOs might be the solution to successful
commercialisation and survival in industry.
4.4 Academic Spin-offs
During the mid-1990s, this category of SMEs has
increased in numbers as a result of numerous
government initiatives. Universities and public research
institutes had come under pressure to show their role
in society and their positive contribution towards the
commercialisation of research results. Booming stock
markets and isolated, though visible, IPOs of hightech start-ups, had increased the perception among
policy-makers that academic spin-offs could become
engines of regional development and growth. As a
result, many researchers were attracted by the idea
of founding such a start-up. The incentives to do so
were many: universities created technology transfer
agencies (TTOs) to manage the commercialisation
of research activities at universities. These TTOs
often had a clear focus on the support of spin-offs.
Because it was clear that management support was
not enough, pre-seed capital funds were also created.
These funds had the objective of investing in spin-off
activities. The key performance parameters of these
funds tended not to be purely market driven, but often
had the creation of spin-offs as a specific objective. To
help, governments introduced initiatives to support
these funds financially and to stimulate researchers
to create academic spin-offs.
Nowadays, the average European university has
between ten and fifteen spin-offs, created since
the mid-1990s. However, the relative importance
81
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SMEs
Although internationalisation is an appealing avenue
for growth, entering foreign markets involves some
substantial risks. As described by Yli-Renko et al.
(2005), RBSUs entering foreign markets face both
the liability of newness and of foreignness. The
liability of newness (Stinchcombe, 1965) results in
a lack of legitimacy of RBSUs (Aldrich & Fiol, 1994),
which hinders the companies to get a foothold
in a foreign market. The liability of foreignness
(Zaheer, 1995) burdens RBSUs with costs arising
from geographic distance and cultural, political and
economic differences.
to a large parent firm. On the other hand, the CSO
has the freedom to build its own business model
and explore new market opportunities. Since the
CSO is legally independent, it has the freedom to
change its business model according to the market
opportunities and demands.
Wo rki ng
countries and even continents. Furthermore, policymakers facilitated international business by reducing
trade barriers. Several studies show that RBSUs in
general and independent NTBFs in particular enter the
international scene at a very early stage. Contrary to
stage models, which describe the internationalisation
process of a company as a step-by-step process
(Johanson and Valhne, 1977), these firms seem to
leapfrog some stages to accelerate their international
activities. An important factor that steers their
decision to go international from inception is the
limited size of the local market (Zaby, 1998).
The Future of Key Research Actors in the European Research Area
of informal start-ups and formal IP based spin-offs
remains unclear because national databases on
spin-off companies are very hard to compare given
the variety of inclusion criteria.
4.5 Venture Capital Backed Start-ups
82
According to Amit (1998), who built on agency theory,
VCs are expected to be prominent in industries where
informational concerns are important, such as biotech,
ICT, etc. However, within this class of projects, VCs will
select those projects with the lowest chance of giving
rise to costs related to informational asymmetries.
They will therefore prefer to invest in companies that
have realised first sales over pure start-ups. This
phenomenon is giving rise to what we call the equity
gap, or the risk averseness of investors to invest small
amount of money in companies that are in an early
stage of development, typically in a seed or startup phase. There are a number of reasons why this
equity gap exists. First, VCs incur similar costs when
selecting and following up on small and large projects,
and may therefore prefer to invest in larger projects.
Second, banks are extremely risk-averse towards early
stage projects that often cannot provide guarantees,
especially in a high-tech context, where the main
assets of the company are knowledge-based.
As outlined earlier, the European venture capital
industry is different from that of the US. European
VCs prefer to invest in later, less risky stages,
in contrast to the US, where MBO investments
typically account for less than 5 per cent of total
venture investment (Martin et al., 2002). The ICT
bubble in 2000 caused VCs to shift from early stage
investments to MBOs. Whereas the European VC
industry invested €6.7 billion in seed and startup phases in 2000, it invested only €2.1 billion in
the same phases in 2003. Reasons for this are the
disappointing return on investment obtained from
early stage investments, the lack of active stock
markets in Europe and the company owners’ fear of
losing financial independence.
This reluctance however causes a major problem for
early stage companies, and especially for high-tech
companies that need sufficient amounts of financing in
order to bridge the liability of newness. They are faced
with a chicken-and-egg problem, with VCs that are not
willing to invest before first sales have been realised,
a patent has been taken and a complete management
team is in place. Start-ups however often need
financing in order to realise these first sales, to apply
for a patent, or to hire a high-level business developer.
Quite a lot of government initiatives have been put in
place in order to motivate VCs to invest in the early
stages of companies, or governments have set up their
own funds. Public funds however remain small, with
investment managers being less experienced, and
often responsible for a diverse portfolio, ranging from
biotech to ICT to industrial automation. This prevents
them from being able to develop specialised industry
knowledge and build a network, or to be involved in
value-adding activities (Knockaert et al., 2005). Given
the reluctance of private VCs to invest in early stage
projects, which seems to be natural given the low
returns, governments are challenged with making sure
that sufficient venture capital financing is available to
start-ups and even companies in a pre-start-up phase.
They must also ensure that the investment managers
involved in the follow-up of investments have both the
expertise and network to add value to the ventures
invested in. Bottazzi and Da Rin (2002) report of the
wide consensus among economists, business leaders
and policy-makers that a vibrant venture capital
industry is a cornerstone of the US’s leadership in the
commercialisation of technological innovation. They
also conclude that the quality of European venture
capital is a more urgent issue than sheer quantity.
5. Scenarios on the
relative importance of
the different types of
SMEs in knowledge
production and
diffusion
The final section of this paper discusses some
scenarios on how the relative importance of these
different groups of companies for knowledge
production and diffusion will evolve over time.
Since SMEs are not one homogeneous group of
companies, it is not possible to draw exclusive
scenarios for the group as a whole. Based on the
challenges outlined above and the trend towards
open innovation we summarise some scenarios that
may be complementary in nature.
5.1 Scenario 1: 2020 – Academic spin-offs:
from hype to reality
Since the mid-1990s spin-offs have been increasingly
set up as a alternative to licensing. Although growth
or performance measures are difficult to get by
As a response to these developments, governments
in many other European countries have introduced
key performance indicators to encourage public
research institutes and universities to take part
in the entrepreneurial process. We expect that
an increasing focus on the commercialisation of
intellectual property through spin-off companies
does not go hand in hand with establishing an
entrepreneurial culture. This has large implications
as to how much and which type of companies will be
established in the future. PROs with a strategic focus
on commercialising intellectual property put much
less effort in establishing start-ups (Moray, 2005).
Interestingly, it is exactly these companies that are
often the result of entrepreneurial processes which
inherently grow from ‘bottom-up’ instead of being
the result of ‘top down’ approaches.
If the government wants to stimulate the
establishment of research-based SMEs, there
is a need for a well-balanced view of what
academic entrepreneurship entails and it needs
to be integrated in the organisational culture. For
example, both researchers and technology transfer
officers need to be open to the possibility of both
spin-offs and start-ups. Today, spin-offs might
be created as part of the technological valuation
whereas sometimes establishing a small start-up
might be a better idea from a business point of view.
Overall, we expect that fewer IP based spin-offs will
be established in the future, but that established
spin-offs will be the result of highly scrutinised
selection procedures. These technology platform
companies will be incubated or embedded in a
supportive entrepreneurial/business development
network, to raise their chance of success and to
enhance the probability that the winners become
established.
The population of academic spin-offs as a whole is
still too young to draw strong conclusions in terms
of growth. A study by Moray and Clarysse (2005)
suggests that the average return realised on the
portfolio of spin-offs from a top Belgian research
institute was about 11 per cent per year and the total
employment of these companies averaged around
450 employees. Other results, such as the ones
published by Chalmers in Sweden, show similar
findings. These results are quite good, but it remains
questionable whether they are representative for all
universities and research institutes in Europe and
whether it will be sustainable over time.
5.2 Scenario 2: 2020 – An increasing focus
on business model innovation as a
source of competitive advantage
In a world where knowledge and technology
become increasingly complex, the value of an idea
depends greatly upon the business model. There is
no inherent value in an innovation per se. The value
is determined instead by the business model used
to bring it to market. The same innovation taken
to market through two different business models
will yield different amounts of value (Chesbourg,
83
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SMEs
Policy-makers have been increasingly aware that the
results of scientific research, in the form of IP that
can be protected through patents and copyrights,
contribute to technological innovation and economic
growth (OECD, 2003). Similarly, public research
organisations in general, and universities in particular,
increasingly wanted to meet today’s expectation of
being an ‘entrepreneurial university’. So, PROs are
confronted with a two-fold mission: on one hand,
they are expected to commercialise their intellectual
property, on the other hand they are increasingly
expected to stimulate academic entrepreneurship.
The first mission means that the creation of spin-offs is
important, alongside licensing and contract research.
The second mission entails that both spin-offs and
start-ups should be encouraged, boosting the rate of
new venture creation in a particular institutional or
regional setting.
In this respect, the Lambert Review of BusinessUniversity Collaboration (2003) raises concern
that some public research organisations may be
actually setting too high a price on their IP. Further,
employees need to be recruited with a strong
entrepreneurial orientation and commercial interest
to meet the expectation of an entrepreneurial
organisational environment. It is important that the
government takes into account facilitating factors
for stimulating academic entrepreneurship – such
as the financial and human resources – instead of
solely focusing on the amount of ventures to be
generated per year. These observations are in line
with Goldfarb and Henrekson’s (2003) findings,
who argue that a top down approach in stimulating
the commercialisation of technology potentially
impedes the freedom to interact with industry and
new firms, which are in turn an important source of
experienced business people.
Wo rki ng
at the European level, it is a question that needs
to be tackled so as to understand the role of this
particular type of SME in knowledge production and
diffusion. In particular, the degree to which they
contribute or participate in knowledge networks
at the regional level is a hugely interesting, albeit
uninvestigated topic.
The Future of Key Research Actors in the European Research Area
2000). Especially in the context of traditional SMEs
and academic spin-offs, the importance of business
model innovation has been highly underestimated in
the past.
84
The strength and efficiency of the core business and
the innovative capacity of the people leading the
firm (in terms of making way for the development of
new products and processes) have often been at the
forefront of academic interest. However, forcing new
ideas into an existing business model is asking for
innovations to fail. Business model innovation goes
beyond developing new products and processes
and requires a completely new way of offering
products and services. It implies (1) articulating
the value proposition (the value created for users),
(2) identifying distinct market segments (the users
to whom the innovation/technology is useful and
the purpose for which it can be used), (3) defining
the structure of the firm’s value chain required to
create and distribute the offering (to determine the
complementary assets needed to support the firm’s
position in this chain), (4) specifying the revenue
generation mechanisms for the firm, and estimating
the cost structure and target margins of producing
the offering, and (5) formulating the competitive
strategy by which the innovating firm will gain and
hold an advantage over rivals.
Policy-makers should increasingly focus on
developing measures which help SMEs to
continuously question their ongoing business and
support activities aimed at increasing growth and
internationalisation.
5.3 Scenario 3: 2020 – The demise of
locally embedded generation SMEs?
Based on the observation that SMEs in traditional
sectors are mainly local actors and experience
little growth, we expect that these companies
will progressively disappear, unless they pursue
innovation-driven growth.
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Heterogeneity of Trajectories: The Case of Biotechnology in France’, Research Policy 32, pp. 621-638.
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Business Venturing 4, pp. 27-47.
Manigart S., Baeyens K, Van Hyfte W. (2002) ‘The survival of venture capital backed companies’, Venture Capital 4(2), pp. 103-124.
Martin R., Sunley P., Turner D. (2002) ‘Taking risks in regions: the geographical anatomy of Europe’s emerging venture capital market’,
Journal of Economic Geography 2(2), pp. 121-145.
Megginson W.L., Weiss K.A. (1991) ‘Venture Capitalist Certification in Initial Public Offerings’, The Journal of Finance XLVI(3), pp. 879-903.
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Entrepreneurship and SME Research: On its Way to the Next Millennium, pp. 199-216.
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pp. 689-708.
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Venturing 11, pp. 439-469.
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86
5
W o r k in g
Paper
Universities
Attila Havas, Institute of Economics, Hungarian Academy of Sciences, Budapest
T
his paper has been written as part of the activities
of the HLEG on The Future of Key Research
Actors in the European Research Area with the
objective to contribute to research and technological
development and innovation (RTDI) policies shaping
the European Research and Innovation Area (ERIA)
of the European Union (EU).2 It should be stressed,
however, that ERIA is understood throughout this
paper as the set of all relevant actors of RTDI processes
in the EU, as well as their interactions. In other words,
‘ERIA-policies’ of the EU are just one element of ERIA,
as it is composed of all other EU, national and regional
policies affecting RTDI processes and performance,
the activities of firms, various types of R&D units
and institutes, higher education (HE) organisations,
financial intermediaries, as well as a host of
supporting, bridging and service organisations, and
most importantly the systemic features, i.e.
the interactions (competition, communication,
networking, co-operation, etc.) among these actors.
Eight actors have been identified in this project,
namely researchers, research and technology
organisations (RTOs), universities, SMEs, large firms,
regional and national governments, and civil society
– treated by eight individual contributions. This
paper aims at devising some possible future states
of universities in 2020, focusing on their research
activities. In other words, it is not a thorough,
exhaustive academic treatment of the current
situation of universities; rather, it is a prospective
analysis. Another important limitation is that it is
simply not feasible to take into account the wide
variety of universities in a single paper. Even inside
a country, one can observe considerable diversity
in terms of their activities (the balance between
teaching, research, and other activities), orientation
(whether their research agenda is geared to regional,
national, EU or global issues, and which labour
markets is teaching catering for), performance
(economic efficiency, teaching and research
excellence – whatever metrics are used), and their
overall role in their respective neighbourhoods.
Across countries, these differences are even
more striking, given their diverse academic and
administrative traditions, followed for centuries.
Universities – like all the other actors – operate
in broader socio-economic systems, and thus it
is crucial to set the scene. One possibility could
be to treat these systems as given. The EU itself,
however, is still evolving; in part due to a number
of internal factors – e.g. the recently initiated
strategic processes and enlargement as the most
visible ones –, and in part as a reaction to external
factors, such as globalisation, competition among
the Triad regions, etc. This paper, therefore, devises
alternative ‘visions’ for the EU (by considering the
overall rationale of its policies, and its standing
vis-à-vis the Triad regions), as a starting point
for developing futures for universities. It is also
assumed that the European Research and Innovation
Area can evolve in different directions, depending on
the main features of the EU to a significant extent,
but with its own dynamics too.3
The visions developed for universities by 2020 are
largely driven by these broader structures, that is, the
EU and the ERIA. In other words, it is a sort of ‘topdown’ approach, and hence a number of ‘bottom-up’
– or ‘micro-level’ – factors might be missing from
this paper. One has to make a choice, indeed, as
there is a trade-off between a comprehensive, allencompassing report (considering a large number
of factors in an attempt to offer a full coverage of
complex issues) and a reader-friendly one. Moreover,
other contributions to this HLEG are paying more
attention to some of these factors, especially the one
by Andrea Bonaccorsi. As a general rule, it is never
a ‘one-man-job’ to build policy-relevant visions:
1.All figures and datasheets mentioned in this chapter can be found in
Chapter 6 “Statistical annex”.
2.The author is indebted for the comments by the members and co-ordinators
of the HLEG on the earlier drafts of this report. Further suggestions by János
Gács and Annamária Inzelt are also gratefully acknowledged.
3.Several ERA visions have been devised by putting governance issues into
the centre (see e.g. Kuhlmann [2001], Georghiou [2001]), Europolis [2001] –
the ones developed in this paper are based on different key variables.
87
Paper 5
Universities
1
Wo rki ng
1. Introduction
The Future of Key Research Actors in the European Research Area
the very idea behind meaningful, germane ‘futures’
is to bring together different stakeholders with
their diverse background, accumulated knowledge
and experience, as well as distinct viewpoints
and approaches so as to enrich the discussion
and analysis. Visions developed by individuals,
therefore, can only spark lively dialogues, and offer
food for thought, at best.4
The report relies on the ‘innovation systems school’
(or evolutionary economics of innovation), but does
not provide an overview of the main concepts of
this paradigm.5 Following the terms of reference, it
is structured as follows. The current and emerging
roles of universities are analysed as starting points
(Section 2), followed by an account of recent and
future key trends, and the identification of drivers
for changes (Sections 3-4). Then, alternative visions
for the EU, the ERIA and universities by 2020 are
devised, and finally their likely impacts on ERIA are
considered (Sections 5-6).
88
The scope of the policy analyses and
recommendations developed by this paper is clearly
delineated by the legal competence and financial
means that the EU – especially the European
Commission and the European Parliament – has to
influence the developments of ERIA, and in particular
the dynamics of higher education. This includes the
following tools/channels: (i) open method of coordination, workshops, green papers (advocating
policy approaches/paradigms, as well as advocating
the use of certain RTDI policy measures, policymaking tools and methods); (ii) funding (RTD
Framework Programmes, or FPs, Competitiveness
and Innovation FP, EU Research Council, Structural
Funds, etc.).
Current (and the likely future) competence of national
and regional governments in terms of funding and
regulating higher education and research (HE/R)
is also to be taken into account when analysing
current trends, and devising visions in more detail.
These factors are even more important when forming
actual policy decisions. Thus, a caveat should be
repeated: just as nowadays, obviously a huge variety
of universities will be observed in 15 years, too, and
thus it is not possible to reflect this diversity in a
single paper.
4.For other purposes, e.g. academic or consultancy projects, ‘single-authored’
visions might be appropriate ‘end-products’, of course. The point here
is to emphasise the fundamental difference between policy processes/
dialogues, on the one hand, and academic endeavours or consultancy tasks,
on the other.
5.Some of the major contributions can be found among the References,
although most of them are not cited directly.
2. The role of universities
in the research system
Universities have traditionally been key players
– for centuries the only visible ones – in producing
and validating new scientific knowledge.6 They have
focused on two main activities:
• training the future generation of researchers, R&D
managers, and policymakers (among many other
fields, for science, technology and innovation
– STI – policies, too);
• conducting various types of research.7
Other research actors have emerged since the 19th
century, notably firms (often – but not exclusively –
in the form of R&D units), public labs, and more
recently some patient groups and other types of
NGOs, too. The role of users in the innovation process
is also recognised now, and has become much better
understood. (von Hippel [1988], Fagerberg et al. [2005])
These developments are discussed in other papers
produced for this HLEG – except the role of public
labs. (Banthien [2006], Clarysee and Moray [2005],
Leyten [2006], Reger and Mietzner [2005]) Moreover,
the notion of research has been extended and revised
considerably, and the discussion moved on to analyse
broader issues like: knowledge, knowledge production
and use; new players in producing, using and validating
knowledge; learning, and learning capabilities, etc.8
Notwithstanding the abovementioned general
considerations on the principal role of universities
in creating knowledge, one should not overlook the
significant diversity across the EU at least in three
aspects:
6.The role of inventors is not to be discussed here, although they have
advanced technologies to a very significant extent, and several major
inventions have long preceded the ‘proper’ theories of their underpinning
scientific principles, such as the steam engine, the first airplanes,
semiconductors, etc. In other words, the links between science and
technology is far from being (uni-)linear. Contrary to the widespread belief
that technologies are, in essence, applied sciences, a number of scientific
disciplines evolved from the puzzles why certain technologies work as they
do. (Nelson [2004], Rosenberg [1996], [1998]).
7.A number of typologies could be used to define/classify research activities,
e.g. the ones developed by the OECD Frascati Manual, Stokes [1997]
quadrants, or EC [2005a]. For a proper policy dialogue it is crucial to use
appropriate terms, but it would go beyond the scope of this paper to
discuss competing terminologies in detail. Suffice it to say that the still
pre-dominant ‘holy trinity’ of ‘basic and applied research, experimental
development’ is not providing any meaningful policy guidance, and can be
even seriously misleading.
8.It would be practically impossible – or ‘unfair’ – to ‘single out’ just a few
contributions to this debate from the huge body of literature; see some
of the major works form the evolutionary economics of innovation listed
among the references.
• the competence of national vs. regional
governments to regulate and fund universities;
Where research is located:
universities vs. other players
• the outputs (outcomes, impacts) of research
efforts by universities.
There is a rather strong consensus in the literature
on the rationale to spend public money on basic
science: training of future generation of researchers is
understood to have the overriding importance among
the other benefits of basic science, implicitly assumed
to be conducted (almost exclusively) at universities.
(Pavitt [1991], [1998], Salter and Martin [2001]) From a
different angle, this consensus suggests a very close
link between higher education and research. Indeed,
for centuries universities had been elite education
institutes for the elite in two respects: (i) only the elite
of a given age cohort was offered higher education
– the term itself clearly reflects this feature, although
nowadays we tend not to pay attention to this name;
and (ii) the ‘output’ was the next generation of the elite:
higher education meant to reproduce academic staff
and societal leadership. It was important, therefore,
to offer the highest possible level of education, which,
in turn, required high-quality research. To further
strengthen the link between education and research,
when training the next generation of the academic staff
it was a must to teach them how to conduct research,
too, i.e. to involve them in research activities while they
were students. In short, that was the Humboldtian
model of universities: assuming a unity of teaching
and research, based on the idea of higher education
through exposure to, and immersion in, research
activities (Kehm [2006]).
Only the first aspect is treated in some detail below.
As for the second one, suffice it to say that in some
bigger EU countries – e.g. in Germany and the UK –
the regional authorities have competences to devise
policies on higher education, as well as to fund HE
institutes.9
As for the third aspects, the very fact that universities’
research efforts lead to rather diverse outputs
(outcomes, impacts), both in terms of quality and
quantity, prevents any meaningful analysis at the EUlevel. The sheer number of universities, together with
the diversity one can observe in their performance,
means that a thorough, micro-level discussion would
be needed. On that basis a comparative analyses can
be conducted either at the regional/national level,
or across countries, but in the latter case taking only
universities belonging to the same ‘league’, e.g.
those aspiring to world-class research and education.
Further, empirical research does suggest that diversity
prevails even inside universities: the performance
of faculties or individual institutes and departments
varies a lot. No doubt, there are various efforts to
rank universities in spite of these methodological
difficulties, but none of these ‘league tables’ is
generally accepted. On the contrary, they are heavily
criticised, exactly because of their questionable
methodologies – and it is not the subject of this paper
to discuss these issues in more detail.10
Obviously, it would be pertinent to conduct thorough
empirical analyses to compare the performance of
universities among the Triad regions, as well as across
EU countries, by taking into account the ‘quality’
and ‘efficiency’ of their research and education
activities. First, though, a sound methodology should
be developed to establish appropriate metrics
and evaluation criteria. Among other factors, the
universities’ role in global, EU, national, regional and
sectoral research networks and innovation systems
should doubtless be considered in order to establish
their level of ‘competitiveness’. These results
could be used both for deepening our theoretical
9.For a detailed analysis of the overall role of regional governments in STI
policies, see Sanz-Menéndez [2005].
10.On the more general issue of merits and drawbacks of benchmarking,
and the distinction between naïve vs. intelligent benchmarking, see, e.g.
Fagerberg [2003], as well as Lundvall and Tomlinson [2002].
The last few decades, however, have seen a major
change: with 30-40 per cent of the relevant age
cohort attending tertiary education, we cannot speak
of the same ‘higher’ education system. It is neither
exclusively the ‘elite’, who participates in it, and nor
is the only aim to reproduce the academic and social
elite.11 Thus, an increasing number of HE institutes
are mainly – or only – teaching organisations, and
overall we can see, therefore, a growing number
of ‘teaching-only’ positions in the HE sector. In the
meantime, the number of ‘research-only’ positions
is also increasing at certain universities, plus
other research performers do play a major role in
producing knowledge (see below in more detail). In
other words, teaching and research nowadays are
only ‘intertwined’ at a fewer number of universities,
11.‘Today one in three young people go to university [in the UK – AH],
a proportion which is continuing to rise. Where it was once thought
exceptional to win a place at university, was a guaranteed sign of academic
and social advance and a just occasion for celebration, today it merely
marks a stage in life, requiring no special academic merit, signalling in itself
no great likelihood of later worldly success.’ – describes the situation in the
UK in the mid-1990s Smith and Webster [1997].
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Universities
understanding of innovation processes, as well as for
underpinning relevant, efficient policies.
Wo rki ng
• the balance of research activities between
universities and other players;
The Future of Key Research Actors in the European Research Area
and usually only at the post-graduate level. The
Humboldtian model has thus become an exception,
rather than the rule.
90
We also know that countries follow different routes.
Universities do play a leading role in a number of
countries; yet, in other countries public research
institutes can be at least as important players. The
well-known examples are the institutes belonging
to Max Planck Gesellschaft (Germany), CNRS
(Centre National de la Recherche Scientifique,
France), CNR (Consiglio Nazionale delle Ricerche,
Italy), CSIC (Consejo Superior de Investigaciones
Científicas, Spain), and the Academies of Sciences
in a number of new EU member states. There are no
readily available statistics to compare the weight of
universities and these other types of public research
institutes, either in terms of inputs or outputs. Thus,
only some examples are presented in Boxes 1-5
(Statistical annex), clearly showing that the role of
these research organisations should not be ignored
in policy discussions.12 A sort of proxy variable can
be the distribution of public funding for universities
and public labs: these data also suggest the nonnegligible weight of the latter in a number of
countries (Figure 1).
In sum, there seem to be strong reasons to revisit
the aforementioned, widely held, consensus on the
rationale for funding ‘basic’ science by public money:
(i) the very notion of ‘basic’ science is questionable,
(ii) even if we continue using this doubtful term,
higher education and ‘basic’ science are not that
closely interconnected nowadays as they used to
be, partly because of the changing nature of higher
education, partly because the crucial role played by
other research actors in producing knowledge.
Leaving aside the question of whether universities or
other research organisations play a more important
role in pursuing ‘basic’ research activities, it is
worth having a look at the relative weight of various
research-performing sectors.13 First, though, the
scene should be set by recalling the huge variety
among the EU (and OECD) members in terms
12.For a more detailed description of public research centres, especially on
the variety of players in this sector, e.g. in terms of organisational forms
and changing ownership (public, semi-public) profiles, missions, size, and
performance, see EC [2003a], pp. 65-74. The report also signals a similar
warning: ‘Relatively speaking, this sector has received less attention than
the business and higher education sectors. One barrier to understanding
is the wide range of structures existing in Europe, which vary by country,
nature of mission and type of research. Furthermore, this sector is often less
visible in public indicators (such as the number of scientific publications and
patents) because the principal outputs of its scientific and technological
activities are consumed by government itself in terms of advice, or by
private clients for technological consultancy.’ (p. 65).
13.Lack of readily available data across countries on various types of research
is also a major obstacle to pursue this question further. The theoretical
considerations, however, are even more important reasons to conclude that
one should not devote too much effort to this issue.
of their ‘pool’ of researchers, i.e. their absolute
numbers, as well as in terms of ‘research-intensity’
of employment, i.e. the number of researchers per
1 000 labour force (Data sheet 1, and Figure 2, in the
Statistical Annex)
Now to compare the various research-performing
sectors by taking input indicators, employment data
show a great deal of diversity in terms of the share
of HE researchers in the national total. There is no
generally valid pattern in terms of dynamics, either;
that is, the share of universities has increased in
some countries and decreased in others during the
last 25 years (Data sheet 2).
In a few OECD member countries, the weight of
universities is around 50-60 per cent (Australia,
Greece, Poland, Portugal, Slovak Republic, Spain), in
a somewhat larger group this ratio is around 30-40
per cent (Austria, Belgium, Canada, Czech Republic,
Denmark, Finland, France, Hungary, Ireland, Italy,
Japan, The Netherlands, Norway, Sweden), while in
a small group it is between 15-25 per cent (Germany,
Korea, UK, USA). A quick look at the composition of
these groups also reveals that one can find smaller
and larger, less developed and more advanced
countries in each ‘cohort’. As for the dynamics,
major changes, i.e. at least around 8 percentage
points in the last 25 years, have occurred in 10 cases
in downward direction, while noticeable upward
changes can only observed in 2 cases (Hungary and
Slovak Republic), while roughly half of the countries
maintained their shares over this long period.
Firms are major employers of researchers: the
share of this sector in the national total is above 50
per cent in 15 OECD countries (out of the 24 ones
selected for this exercise), and in two other ones are
very close to this level (around 45-47 per cent, Data
sheet 3). It can also be established that practically
all the advanced countries are in this group. The
share of business enterprises is significantly higher
in the USA than the EU average.
For this sector, a clearer pattern of dynamics can be
observed: in most cases there is a strong upward
trend, while in five countries no major changes have
occurred since 1981.14 Only three new EU member
states have shown a noticeable decrease (Hungary,
Poland, and the Slovak Republic).
A third major sector employing researchers is the
government. In most cases, the weight of this sector
14.As for the sixth one, namely the Czech Republic, data are only available
1999 onwards, and in this significantly shorter period the share of business
enterprise researchers was fluctuating between 39-45 per cent.
The business enterprise sector plays a dominant role
in terms of performing gross domestic expenditure on
R&D (GERD, Data sheet 6). In most cases, its share
is around 60-70 per cent, in four additional cases it
is still around 50 per cent, and only in four cohesion
countries is it around 30-40 per cent (Greece, Hungary,
Poland and Portugal).15 The overall trend is either an
increasing weight, or maintaining an already high
share, with only a few exceptions showing a decrease
(Italy, Poland, and the Slovak Republic).
Employment figures are not readily available for the
fourth sector, namely the private non-profit research
organisations. The share of this sector is rather low
in terms of performing GERD in most OECD countries:
below two per cent in 13 countries; around two to
three per cent in four countries; just above four per
cent in the US, and above ten per cent in Portugal – in
the latter case most likely for specific institutional/
historical reasons. (Data sheet 8) Available data do
not show any noticeable change since 1995, except
in the case of the UK and US, where the share of this
sector has increased.
To sum up, the two input indicators considered here
do suggest a great diversity in terms of the ‘weight’
of various research performing sectors, but a clear
finding is that the business enterprise sector is a
dominant one in the majority of OECD (EU) countries,
and all the advanced ones share this feature. From a
different angle: the relative weight of universities, and
especially that of the government sector, is higher in
the less developed (or cohesion) countries.
Output indicators, such as publications, citations,
patents awarded, spin-off firms established are not
readily available by research performing sectors,
and thus their relative weight cannot be compared
this way.
Key inputs for university-based research
Researchers
Usually a small portion of GERD is performed by the
government sector: around – or even below – ten
per cent, with the exception of two big, affluent,
and somewhat centralised states, namely France
and Germany (16-18 per cent, and 13-14 per cent,
respectively, since the late 1990s, Data sheet 7). Less
developed countries tend to have a higher share,
however, the extreme case being Poland (40-45 per
cent in 2002-2003), followed by the Czech Republic,
Greece, Hungary, Italy, Portugal, the Slovak Republic,
and Spain (with a share of roughly 18-30 per cent).
It should be noted again, that a ten per cent share
means a significant research capacity in absolute
numbers in big countries (e.g. the UK and USA),
and/or in the ones with a high GERD (e.g. Finland).
15.The Slovak Republic seems to be an interesting ‘outlier’ with its very high
– albeit declining – share, but individual cases are not to be discussed in
any detail here.
The number of HE researchers has grown significantly
since 1981: from 382 000 to 870 000 (1999) as the
total OECD figure, and from 156 000 to 430 000
(2002) as the total EU employment (Data sheet 9).
It should also be noted that the EU employs the
highest number of researchers in the HE system, and
more than double the number of US researchers,
that is, 186 000 (1999).
Funding16
The funding of university-based research increased
substantially since 1991: Higher education-based
R&D (HERD) grew by 36 per cent in the EU countries
16.The issue of (overall) funding universities is dealt with by Andrea
Bonaccorsi’s contribution in more detail. Figure 3 provides a snapshot on
diversity among EU countries in terms of the share of public and private
funding of HE expenditures, while Figure 4 reports on the dynamics of these
expenditures.
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Paper 5
Universities
Another important input indicator is spending on
R&D activities. Taking this figure, the share of the
university sector is significantly lower compared
to its weight in employment. The diversity among
countries remains easily noticeable, however. (Data
sheet 5) This indicator also shows a mixed long-term
dynamics: in some countries – both in advanced and
less developed ones; e.g. Canada, Greece, Hungary,
Ireland, the UK – the university sector gained a higher
share, while e.g. in Japan and Sweden a significant
loss can be seen (ten and eight percentage points
respectively, in around 25 years).
As for the dynamics, the weight of the government
sectors is diminishing – or remains at a low level –,
practically in all countries. The only ‘outliers’ are
Hungary and Poland.
Wo rki ng
is below 15 per cent, or even 10 per cent (Data
sheet 4). It is only six countries, where the share is
around 20 per cent, and there are two extreme cases
with a figure around 30 per cent (the Czech Republic
and Hungary). Again, it is a quite straightforward
conclusion that the share of this sector is rather
low in advanced countries – but not necessarily the
absolute number of researchers –, while the majority
of less developed countries tend to have a larger
government sector, though often with a low absolute
number of researchers. As for the dynamics, the
overall trend is a decreasing one.
The Future of Key Research Actors in the European Research Area
in 1991-2000 (that is, from USD24.4 billion [constant
1995 prices and PPP] to 33.3 billion), and a further 10.7
per cent in 2000-2003 (from USD38.5 billion [2000
prices] to 42.6 billion). The respective growth rates for
the OECD area are even higher: 40 per cent in 19912000, and 15.2 per cent in 2000-2003. (OECD MSTI,
various issues, author’s calculation). This suggests
an increasing recognition of universities’ contribution
to social and economic objectives. The sources of
funding for research have been diversified in the
meantime. There are a variety of potential funding
sources: national governments, supranational bodies,
regional governments, business enterprises, and the
civil society (foundations). International public sources
(EU schemes, and bilateral agreements) are especially
important in two groups of countries: (a) advanced
ones, co-operating in leading-edge research projects;
and (b) cohesion countries, lacking sufficient domestic
funds. In order to attract new financial sources,
universities need to demonstrate their financial and
social accountability.
92
Despite the variety of funding sources, governments
remain the main financing body for university-based
research. The share of HERD funded by industry is
rather low in most OECD countries (on average 6.1
per cent for the OECD area in 2003, and 6.5 per cent
for the EU25), and it is increasing only in a few ones,
e.g. in Hungary and Turkey (Data sheet 10).
3. Recent key trends
This section lists, rather than discusses in detail,
some of the recent key trends.17 Some of these
trends will be used when building visions in
Section 5. Others that would occur in the same way,
i.e. regardless of the basic features of a given vision,
will not occur in the visions. The order in which these
trends are listed does not necessarily reflect their
significance.
•increasing role in local, regional, sectoral,
national and international production and
innovation systems.
2.An increasing share of the age group of 18-29
years old is registered for university courses. In
a number of countries, there is already a very
high enrolment at HE, leading to a fundamental
transition from elite universities of the previous
centuries to ‘mass production processes’ (as
already discussed in the previous section).18
The impacts of this change can be far-reaching in
terms of:
•the financial and infrastructural requirements
(difficulties in accommodating ever-larger
number of students);
•the number and/or workload of teachers;
•the quality of education/degrees (their ‘prestige’,
acceptance by potential employers);19
•job-seekers’ aspirations, ambitions.
3.The Bologna Process – understood here as its
original Sorbonne declaration and the joint
decisions made at various follow-up conferences
held in Bologna [1999], Prague [2001], Berlin
[2003] and Bergen [2005] – is aimed at having
significant impacts on the EU HE system in many
respects. The specific goals include:
•improving international transparency of
study programmes and the recognition of
degrees via convergence towards a common
framework for degrees and study cycles;
•promoting student mobility in the EU, and the
integration of university graduates in the EU
labour market;
1.Changing roles and responsibilities of
universities: on the one hand, new roles emerge,
on the other hand, the balance of various roles is
changing:
18.As this pressure mainly concerns the educational role of universities,
there is no need to provide a thorough analysis here. Just to illustrate
this otherwise well-known phenomenon, it is satisfactory to mention two
distinct cases; an advanced EU member and a cohesion country: the number
of UK university students have increased by a factor of five between the
early 1960s and the late 1990s (Smith and Webster [1997], p. 18), and in
Hungary by three times in the last 15 years (Semjén [2004]). For a snapshot
on an earlier period (2000/2001), see Figure 8.
19.This issue was already raised some 10 years ago in the country where the
explosion of the number of students occurred first, but it seems to have
a growing relevance in ever more countries since then: ‘The expansion
has been accompanied by squeezing of resources, as is now widely
acknowledged, and this has manifested itself in growing student poverty,
declining academic salaries, falling academic social status, and in an
increasingly shabby fabric of universities themselves. With the growth in
student numbers has come a devaluation in the currency of a degree, with
graduates no longer feeling confident of achieving high salaries and high
status in later life. And alongside this decline have come the charges that
standards are declining and that universities are awarding (…) ‘dummy
degrees’.’ (Smith and Webster [1997], p. 18).
•teaching; academic research; consultancy
and troubleshooting (problem-solving) for
firms and other national/regional/local
players (NGOs, policymakers); other joint
RTDI projects with businesses;
17.Other recent key trends are likely to be continued in the coming decades,
too, and thus they are discussed in Section 4, focusing on future trends.
the
mobility
of
university
•promoting EU-wide co-operation among
universities in quality assurance, evaluation,
and curricula development;
•giving more attention to life-long learning as
a basis for a competitive economy;
•making the EU HE system more attractive;
•achieving easier recognition of degrees and
modules. (Alesi et al. [2005]).
All of these goals are of direct relevance for the
teaching role of universities, i.e. not directly for
their role in the research landscape. However at
the Berlin Conference, held on 18-19 September
2003, the need to incorporate doctoral studies into
the Bologna Process was specifically mentioned.
That dimension is obviously closely interconnected
with the research activities of universities, both
in terms of the present research projects (in which
PhD students are usually participating), and as the
training of the future generation of researchers.
4. Driving forces for
change and future
trends
Some of the driving forces for change are already
present, and thus their impacts are manifested in the
recent key trends, discussed in the previous section.
The most important driving forces are likely to be as
follows:
• Quest for excellence in research (both for
improving academic recognition and raising
funds, either from public or private sources) and
the speedier completion of projects (new results
should be achieved ever faster). This is adding
thrust to the already strong pressure for intense
international collaboration, and in the meantime
creating a fierce competition for talents (PhD
students, researchers, and university staff ).
• Technological changes: more sophisticated and thus
more expensive equipment is needed for conducting
research, putting pressures on university budgets.
• Demographic changes (some already discussed
in Section 3, others to be discussed below): the
number of students is likely to further increase.
• Tensions in government budgets: governments,
both national and regional ones, are under pressure
to cut public expenditures, so as to balance their
budgets, and/or make tax cuts possible.
• Quest for cost-efficiency of research: the combined
effects of technological and demographic changes,
together with the pressure on public funding,
open a gap between rapidly increasing research
and education costs and public budgets allocated
to higher education and research (HE/R). Thus
research projects are more and more closely
scrutinised in terms of their cost-efficiency.
• New societal demands and changing values.
• New methods, approaches, norms to organise,
manage, validate, legitimate and evaluate HE/R.
Policies can either toughen some of these driving
forces, slow down or divert their impacts, or create
new drivers for change by introducing far-reaching
and resolute goals into the HE/R system.
These science and technology (S&T), societal and
economic factors – coupled with various policies and
regulations – may give rise to a number of future trends
(while a number of current ones are likely to persist):
1.Fundamental shifts in the balance of various
roles of universities? New activities and roles to
be performed by 2020 (given social, financial,
organisational, S&T trends/developments/
demand/shocks)?
2.New types of courses/degrees – in terms of their
content, requirements, as well as ‘teaching’
(delivery) and assessment methods – are to be
offered to meet:
•new societal and economic needs;
•short(er), more practical courses for jobseekers;
•regular re-training of middle and toplevel managers and policy-makers, as well
as researchers (as required by life-long
learning);
•a different structure/balance between
learning and working: learning is more
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•facilitating
faculties;
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The Future of Key Research Actors in the European Research Area
evenly spread throughout the career path of
individuals;
94
•courses for self-development;
•flexibility in the timing and delivery of courses,
and/or taking exams in any period of the year);
•courses tailored to students
customisation’ in HE ‘services’);
•more pronounced demands/requirements/
values ‘attached’ to HE/R funds coming from
governments,
businesses,
foundations,
alumni associations, and ‘consumers’
(students and/or their parents).
(‘mass-
3.Intensifying the international mobility of students
and staff; although an important aspect of this trend
is already mentioned as part of the Bologna Process
(in Section 3), namely intra-EU mobility, the global
aspects are so essential that it merits a separate
mention as a future trend. Significant differences
can be observed in this respect inside the EU (by
countries) and inside the ‘winner’ countries (by
universities) – see Figure 6, Data sheet 11, and
Bonaccorsi (2005) on this point for details.
Would these differences further increase or
diminish?
A current trend is that post-graduate courses
offered by US universities are particularly
attractive for foreign students, including
students from the EU. What is worrisome from
the point of view of the future of ERIA is that
nearly 60 per cent of science and engineering
doctoral students coming from EU countries
have firm plans to stay in the US, upon
the completion of their studies, instead of
returning to the EU. This proportion has risen
notably over the past decade: from 44.5 per
cent at the beginning of the 1990s to 57.5 per
cent at the turn of the millennium (see Data
sheet 12 in the Statistical Annex).
Competition for students and staff (intra-EU,
globally) is likely not merely to continue, but to
intensify significantly. In the case of students, both
numbers and talent are likely to be important in
these contests (quality playing a more pronounced
role for post-graduate courses), while in the case
of staff, talent is the overriding consideration.
•Which regions of the Triad are going to be
successful/can benefit the most?
•Which countries inside the EU?
•What type of universities?
4.Ever-stronger international co-operation in
research (and innovation) projects at a global
level and an EU-level, as none of the Triad
regions – let alone individual countries – can be
self-sufficient.
5.Stronger, better articulated needs for multi(trans-; inter-) disciplinary training and research.
6.Demographic trends: the overall trend of an ageing
population persisting in the EU as a whole triggers
a change in the composition of students in terms of
age, that is, the share of ‘mature’ students is likely
to increase. Lifelong learning further reinforces
this trend. Thus new methods and approaches
in HE are likely to emerge; just as new types of
contacts, communications, exchanges between
HE (teachers and other staff) and students on the
one hand, and among students (from different age
group/experience) on the other.20
7.New HE/R ‘service providers’ might evolve, for
example:
•fundamentally re-structured universities,
e.g. financially weak, formerly independent
universities taken over by strong performers
from the HE/R sector, or other businesses,
such as publishing houses, with the ambition
of selling education services, not ‘just books’;
•newly set up ‘branch’ campuses of highly
respected universities, using their ‘parent’
university’s curricula;21
•organisers of studies and degrees operating
without their own academic staff and own
courses;22
20.Some signs can already be felt in the US: ‘Institutions designed and
operated for youthful students have often been traumatised by the
changing composition of the student population. This is especially true
of the faculties who are ill-equipped to deal with the demands of the
three million working adult students who not only want an education but
want it delivered in much the same way the other services they purchase
are delivered: efficiently, conveniently as to time and place, courteously,
and with a consistent structure yielding a uniform quality. Furthermore,
they want an education that, quite apart from what it may do for them as
reflective beings, will improve their performance in the workplace whether it
be in the professions or technical position.’ (Sperling [1999], p. 114).
21.The West Report has devised a number of business models for universities,
among others, this one. (GAL [1997]).
22.This is not mere speculation: Western Governors University is a virtual one,
set up as a private collaborative venture by governors of 18 states in the US
and a number of large companies. It offers distance-learning courses via
its website, alongside ‘brokered’ courses and degrees (provided by ‘real’
education institutes), and also acts as a clearinghouse. (Farbman [1999]).
•NGOs setting up virtual universities;
•‘accreditation’
organisations
granting
certificates, diplomas, even degrees without
offering their own teaching programmes (it
can be a new role for existing universities,
too); it can be based on proved competences,
or more conventional coursework done by the
‘students’ elsewhere, including e-learning;
•currently ‘unthinkable’ players might launch
HE/R services in various ways: using or
modifying current organisational forms and/
or inventing new ones.
8.Lost monopoly of universities (and other
conventional academic players) in terms
of legitimisation, validation of knowledge?
Besides conventional academic researchers,
knowledge is produced by a wide variety of
players, e.g. think tanks, private research
organisations,
non-profit
organisations,
government agencies, consultancy companies,
market research organisations, patients’
groups, various NGOs, trade associations,
interest groups. These pieces of knowledge
are used by the organisations themselves
(government agencies, firms’ labs), sold to
other parties (contract research organisations,
consultancies) or exploited in political/societal
processes for advocating/pursuing certain
views or interests (NGOs, trade associations).
From a different angle, these pieces of
knowledge are also diffused, and thus subjects
to different types of validation procedures
(formal/informal; explicit/implicit). Currently
the rules of validation seem to be in flux, i.e.
the traditional peer-review process seems to
be losing its long-established monopoly. As
the roles of different players, and hence ‘the
rules of the game’ are changing in legitimating
knowledge, Bonaccorsi (2005) considers
3 possible future states: (a) non-academic
sources of knowledge are considered fully
legitimate, i.e. academic research loses its
power to validate knowledge; (b) knowledge
– either from academic or non-academic
sources – is only accepted in society if validated
by conventional academic rules and players;
(c) a clear separation between knowledge
created by credible academic organisations
and non-academic ones, the former enjoying a
higher status.
9.Changing set of evaluation criteria: depending
on the speed and extent of changes envisaged
above (especially 1-5), universities are likely to
be evaluated by using new metrics, besides the
conventional criteria of academic excellence
(notably publications, citations). In particular,
to what extent they fulfil their various societal
roles; what types of courses are offered to
whom, at what level of quality; are they attractive
for foreign staff and students; are they active in
international co-operation; to what extent are
they engaged in multi- (trans-; inter-) disciplinary
training and research; are they using various
resources in an efficient way?23
Various types of universities (e.g. ones focusing
on vocational training as opposed to postgraduate teaching and research; or meeting local
needs vs. acting as a global player; etc.) are likely
to be evaluated by different sets of criteria.
The overall rationale of ERIA, in which universities
operate, is also likely to have an impact on devising
evaluation criteria and methods. (see Section 5 on
different possible rationales for ERIA.)
95
10.The further proliferation of the already existing
diversity of governance and management models,
and the more pronounced professionalisation of
university management: there is already a wide
variety of governance models (different ways
and weights of involving stakeholders: national
and regional policy-makers, businesses, societal
groups, students, academic staff, etc.) as well as
management models (collegial vs. professional,
their different ‘blends’. (Kehm [2006]) The
inherent tension between the interests, values,
and goals of different stakeholders, and the
tensions between the need to monitor and
control the various activities of universities for
managerial purposes and the nature of academic
activities (training, research) would most
likely be resolved in different ways by different
players. The emergence of new players – and new
business models for HE institutions – is likely to
add ‘more colours’ to this picture. The diversity of
governance and management models, therefore,
is likely to further proliferate, even inside the
group of similar HE institutes, let alone among
different types of them.
23.The weight of these measures is a complicated and ‘tricky’ issue; obviously,
it cannot be treated here in a satisfactory manner. The question of efficiency,
alone, is a very complicated one.
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The Future of Key Research Actors in the European Research Area
5. Visions (future states)
for universities
The ideas presented here are aimed at triggering a
debate. In other words, the nature and goal of our
work require an intense dialogue among the members
of this HLEG at least for two reasons: (i) different
approaches/perspective need to be taken into account
when contemplating the future of ERIA; (ii) the links,
communication, interactions, co-operations among the
various players – analysed by different members of our
group in the first stage in ‘isolation’ – are key aspects
of the future shape and performance of ERIA.
We can devise visions on the future of HE/R from the
perspective of the EU as a whole, taking into account
ERIA as a ‘mezzo level’ system, before addressing
the important issues at the level of universities. A
different approach is to develop futures from the
perspective of HE/R (disregarding various driving
forces, factors, structural and policy variables at the
EU and ERIA levels). The former approach is taken in
Chapter 5.1, while the latter in Chapter 5.2.24
96
These visions (‘futures’ or ‘stories of a future
world’) are meant to present a number of different
possible future roles, missions, organisational
forms, strengths and weaknesses for universities.
These visions offer a description of future states in
2020 rather than ‘fully-fledged’ or ‘path scenarios’,
developing detailed causal stories of how
universities might be transformed between now and
then. Furthermore, it is beyond the scope of this
project to enter into a detailed consideration of the
degree of probability of specific visions. The modest
aim is to sketch different visions of coherent systems
of roles and contexts that allow highlighting the role
of policy in making these future systems feasible.
The major underlying assumptions for building visions
for universities should be spelt out before going into the
details, to avoid some potential misunderstanding or
misinterpretation. First, as already stated in Section 4,
policies can influence the existing driving forces for
change, and can also trigger changes themselves.
Secondly, universities – just as other research actors –
cannot operate fully isolated from their socio-economic
environment.26 For these two reasons, various EU
polices under the label of the Lisbon Process, especially
concerning the relative weight of competitiveness and
cohesion objectives, as well as the more specific ones
on the ERIA, should be considered here.27 Third, the
interrelations between competitiveness28 and cohesion
can be thought of in different ways: (i) as mutually
exclusive goals (a ‘zero-sum game’, as these policy
fields are competing for the same set of scarce political,
intellectual, organisational and financial resources); or
(ii) as mutually reinforcing ones (a competitive EU can
set aside resources to promote cohesion regions, while
narrowing the gaps between advanced and laggard
regions would enhance the competitiveness of the EU
as a whole). This paper takes the latter view, and thus
attributes a great significance to innovation processes
in the cohesion regions/countries, as well as to the
wide range of policies required to promote innovation.
Fourth, cohesion is an issue for (a) large, advanced
member states (given the significant differences among
their regions), (b) for the ‘classic’ cohesion countries,
and (c) for the 10 new member states. Thus, it is a
major political and policy issue – and not only because
of the 2004 enlargement, as it has been an issue for
a non-negligible part of the EU15 as well. Moreover
forthcoming enlargement(s) will add more countries
and regions to this ‘list’. Fifth, promoting RTDI efforts
in cohesion regions via joint research projects (funded,
for example, by RTD FP) does not mean that scientific
excellence is compromised (Sharp [1998]). Sixth, a
pronounced policy emphasis on cohesion does – and
should – not preclude competition among universities.
5.1 Visions for HE/R derived from the
perspective of the EU and ERIA
In this logic, the point of departure is a highly selective
set of fundamental features of the EU: (i) its main
strategic intention/orientation in terms of putting the
main emphasis on cohesion (societal issues) vis-àvis competitiveness; and (ii) its overall performance
compared to the other Triad regions (Table 1).25
24.Note that the national – and sub-national regional – level is ‘skipped’ in either
approaches, given the huge diversity of the national (regional) education
systems. Skipping these levels from the current exercise, however, does not
imply that national (regional) factors can be neglected in actual prospective
analyses (e.g. strategic planning or genuine foresight programmes).
25.Emerging countries, e.g. China and India, might also become important
competitors, but a sufficiently flexible interpretation of the Triad regions can
easily include these – or any other relevant – countries.
26.The degree, to which they can or should be ‘protected’ from their broader
context, would in itself be a subject of intense discussion, as different
parties are likely to have rather diverse views on this question. Clearly, even
a superficial treatment of this issue would be way beyond the scope of this
paper.
27.In launching the discussion on the priorities for the new generation of
cohesion policy programmes, on 6 July 2005 the Commission published
draft Community Strategic Guidelines entitled ‘Cohesion Policy in Support
of Growth and Jobs: Community Strategic Guidelines, 2007-2013’. One of the
specific guideline is to improve the knowledge and innovation for growth.
More specific areas of interventions, proposed by the Commission, include:
improving and increasing investment in RTD, facilitating innovation and
promoting entrepreneurship. (EC [2005c]).
28.There is no widely accepted definition of competitiveness; economists have
different views even concerning the ‘appropriate’ level of analysis: products,
firms, value chains (production networks), regions, nations, or even larger
entities. This problem obviously cannot be solved here.
Table 1
Visions for the EU
EU vs. Triad
Internal
strategy
Successful EU
Laggard EU
Cohesion (societal issues)
Competitiveness (‘multi-speed EU’)
B) ‘Successful multi-speed EU’
A number of EU regions that are already successful are heavily
promoted by EU policies (funds) as ‘engines of growth’, making
them even stronger, leading to enhanced competitiveness of the
EU vis-à-vis the Triad regions.
In the meantime, the gap between these successful EU-regions
and the less developed ones widens significantly, even inside
the big, advanced member states.c
D) ‘Failed multi-speed EU’:
C) The EU development strategy is incapable of harmonising
the requirements of competitiveness and cohesion; policies A multi-speed EU strategy – in spite of ignoring cohesion – fails
meant to support the latter are not modernised, and thus take to close the gap with other Triad regions, while it widens the gap
up too many resources, and hamper the processes required between the advanced and less developed EU-regions.
The reasons for this failure can be numerous: e.g. internal
for enhanced competitiveness.
(inappropriate policies and/or poor implementation), external
Ca) ‘Shaky cohesion’: At least temporary achievements in
(improving EU performance, but an even quicker development of
terms of stronger cohesion (at the expense of external
the other Triad regions). In other words, we can regard the former
competitiveness, and thus considered ‘shaky’).
case an ‘absolute’ failure, while the latter one a ‘relative’ failure.
Cb) Double failure: Inappropriate strategies, insufficient coIn any case, it is highly likely that key players of strong EU
ordination of various policies, poor implementation and/
or external factors lead to an overall failure both in terms of regions would act together both at an intra-regional and an
cohesion and performance vis-à-vis the other Triad regions. inter-regional level – probably also with their counterparts
outside of the EU.
A) ‘Double success’:
A carefully balanced development strategy of the EU, keeping
the ‘welfare’ elements, too, at an EU-level – but pursuing these
cohesion/welfare policies in a more flexible way, and using
more appropriate, refined policy toolsa – leads to an ‘externally’
successful and cohesive EU.b
a. The current success of Denmark, Finland and Sweden points to the possibility of a ‘reformed European socio-economic model’. (Aiginger [2004], Aiginger and Guger [2005]).
b. This vision requires an efficient co-ordination of a number of policies, in three ways: horizontally, i.e. across policy fields, vertically, i.e. across governance levels; and along the time dimension,
too, i.e. short-, medium- and long-term policies also need to be harmonised. (Romanainen [2005]) The vision itself, however, makes no assumption if this co-ordination is achieved via heavyhanded top-down mechanisms, or as concerted actions of member states and other key players, without a strong centre. This is the well-known issue of having or not a ‘federal EU’. (see also two
visions of the EUROPOLIS project, coined ‘Federal Europe’, and ‘Roundtable Europe’, respectively; EUROPOLIS [2001]).
c. Two types of EU behaviour can lead to this future state: (i) a conscious strategic choice to use available funds and other policy tools (e.g. regulation) exclusively or excessively for boosting
competitiveness, and thus ignoring cohesion on purpose (as a perceived necessity); (ii) incapability to devise strategies and policies, and/or general inaction, inertia, inefficiency to implement
policies. (In a radical scenario, not to be discussed here, the loss of most/all EU policy-making power to national, regional, and local authorities would also result in widening gaps among
regions. For a largely similar scenario, called ‘Swiss Europe’, see EUROPOLIS (2001).
These different visions for the EU as a whole have
strong implications for the ERIA, too. In principle,
therefore, different types of ERIAs can be derived
from the above five visions.29 In practice, however,
not all five of them are equally relevant from a
policy (strategy) point of view. Moreover, devising
29.As already stressed, ERIA is understood throughout this paper as the set of
all relevant actors of RTDI processes in the EU, as well as their interactions.
Therefore, by making a strong link between the EU structures and strategies
on the one hand, and the ERIA, on the other, does not deny the possibility
that ‘ERIA policies’ of the EU can enjoy some level of independence from
the overall strategy of the EU. Yet, it would go beyond the scope of this
paper to discuss when this potential ‘discrepancy’ (or ‘mismatch’) can be
seen as a ‘healthy, creative’ tension, i.e. ERIA policies take the lead into the
‘right’ direction, and pull other policies, too; and when it is ‘destructive’ by
hampering development and/or leading to a waste of public resources.
What sort of ERIA would be needed to support
an ‘externally’ successful, cohesive EU (‘Double
success’)? What sorts of policies are needed to bring
about that type of ERIA (EU vs. national policies; RTDI
and other policies, their alignment)? What resources
are needed to finance that type of ERIA (RTDI efforts)?
In other words, how to set in motion a virtuous circle
of ‘external’ success (competitiveness) of the EU and
RTDI efforts? What are the interrelations between
cohesion and RTDI efforts? Can we set a virtuous
circle in motion in this respect, too, or should we see
it as a trade-off? The former policy approach is based
on the consideration that Structural Funds used for
promoting improved innovation capabilities can lead
to faster, more efficient cohesion processes, and
eventually enhanced external competitiveness of
the EU as whole; that is part of the ‘Double success’
vision.30 Meanwhile, arguments to use the EU funds
30.A closely related question would be whether the emphasis put on cohesion
goals would convince laggard EU countries/regions to consider RTDI as
an important enabler of more efficient and faster catching-up, and thus to
devote more intellectual and financial resources to it – but this question
cannot be discussed here.
Wo rki ng
10-15 visions for the ERIA (2-3 ERIA visions times
5 EU visions) would introduce an unmanageable
complexity into this exercise. Thus, choices have to
be made in this respect, too (like making strategic
decisions in real life). It is proposed to consider two
cases here: A) ‘Double success’ and B) ‘Successful
multi-speed EU’.
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97
None of the above five visions can be dismissed
on logical grounds, i.e. any of them could occur.
Their likelihood (plausibility) might differ a lot, of
course, but only subjective judgements could be
made concerning the probability of these visions.
In other words, we do not have any sound, reliable
method to ‘predict’ which of these visions is most
likely to materialise. The actual relevance and
use of them is to present stark choices in terms of
strategies, and to project the future repercussions
of the strategic choices made now. In that way,
these visions can inform present-day decisions,
and also show the possibilities to shape our future.
From a different angle, it is both an opportunity
for, and a responsibility of, decision-makers to act
strategically.
The Future of Key Research Actors in the European Research Area
exclusively or excessively for boosting the already
successful EU regions can ‘dry’ Structural Funds, and
that would lead to a ‘Successful multi-speed EU’.
Not all of these questions can be discussed here
as appropriate answers to them would require a
dialogue among the key players, i.e. any individual
effort to come up with relevant replies is bound to
fail almost by definition. The main features of the
types of ERIA ‘fitting’ to the broad visions of ‘Double
success’ and ‘Successful multi-speed EU’ are
presented in Table 2. It is followed by the discussion
of the main characteristics/roles of universities in
these ‘futures’. (Table 3).
Table 2
Features of the ERIA in two EU visions:
‘Double success’ vs. ‘Successful multi-speed EU’
EU
ERIA
Rationale for EU RTDI
policies
Co-ordination of
policies
Location of major
HE/R centres
Research agenda
98
‘Double success’
‘Double-track’: tackle societal challenges, promote cohesion
and enhance competitiveness.
Intense and successful policy co-ordination among regions,
consciously supported by harmonised national and EU-policies,
with a specific aim to enhance competitiveness and advance
cohesion.
Widely distributed across the EU, weaker centres are
strengthened, new ones are set up in laggard regions with a
specific objective to promote cohesion.
An appropriate balance between societal and techno-economic
issues.
‘Successful multi-speed EU’
Excessive emphasis on enhancing competitiveness.
‘Multi-speed’ policy co-ordination: intense and successful
among advanced regions, heavily supported by their national
and EU-policies; ad hoc and weak co-ordination among laggard
regions, between laggard and advanced regions, at best with
half-hearted, reluctant EU efforts.
Concentrated in already strong, successful regions.
Focus on techno-economic issues; some (minimal) research
efforts to tackle social challenges stemming from the widening
gaps between flourishing and laggard EU-regions (extreme
social tensions and severe, immediate environmental problems
are understood as threats to stability and thus competitiveness:
societal issues as topics for R&D are seen through this lens).
Mobility of
‘Two-way traffic’: gaining experience, building contacts in more ‘One-way street’: brain-drain from laggard regions to booming
researchers,
advanced regions across the Triad, and then exploiting these
ones.
university staff and contacts upon return to ‘cohesion’ regions via intense, mutually Policy schemes aim at further strengthening strong regions via
students
beneficial co-operation.
mobility grants.
Mobility grants explicitly aim at both nurturing talents (for
‘Two-way traffic’ with strong Triad countries/regions.
excellence in RTDI and competitiveness) and fostering cohesion.
Integration of RTDI
Widely occurring across the EU and globally. Policies aimed at
Mainly among strong, successful regions across the Triad, driven
activities (across
promoting the integration of RTDI activities also have an explicit by businesses, supported by policies; laggards are left out for
national boundaries) aim of fostering cohesion, among other EU-wide issues.
not having sufficient financial and intellectual resources and
lacking modern infrastructure.
Research
Up-to-date equipment, including joint large and medium-sized Up-to-date equipment and large- and medium-sized RTD
infrastructure
RTD facilities are distributed across regions, equal access
facilities are concentrated in strong regions. Limited access to
to these facilities for all regions. EU funds meant to keep up
these facilities for laggard regions. EU funds meant to keep up
modern infrastructure also have an explicit aim of fostering
modern infrastructure do not consider cohesion objectives.
cohesion.
Innovation systems, Strong, flexible innovation systems in a large number of
Strong, flexible innovation systems in the advanced regions,
co-operation among regions (with their own specific strengths), capable of renewal capable of renewal and adaptation to the ever changing external
key playersa
and adaptation to the ever-changing external environment,
environment, underpinning sustained competitiveness.
underpinning both cohesion and competitiveness.
Intense communication among businesses, academia, and
Intense communication among businesses, academia,
policy-makers to set RTDI priorities relevant for enhancing
policymakers, and civil society to set RTDI priorities relevant for competitiveness; strong academia-industry co-operation,
cohesion and competitiveness; strong academia-industry comutually beneficial, intense links among large firms and SMEs
operation, mutually beneficial, intense links among large firms both inside and across flourishing regions.
and SMEs in a large number of regions (gradually increasing
Ad hoc, weak communication and co-operation among the key
over time).
players in laggard regions; weak RTDI policy constituencies.
Co-ordinated, joint efforts – supported by EU funds –
Insufficient, half-hearted EU-supported efforts – at best – to
to strengthen weaker innovation systems, including
strengthen weaker innovation systems of laggard regions/
communication, networking and co-operation among key
countries.
players inside those regions and across regions.
RTDI services
Widely distributed across the whole EU, working efficiently,
Mainly in the successful EU regions, sharing experience among
(information,
sharing experience across stronger and weaker regions, but
themselves and with partners in the Triad regions, but geared
consultancy,
geared towards specific needs (not attempting to diffuse ‘one
towards specific needs (not pursuing ‘one size fits all’ type
incubation, etc.)
size fits all’ type practices), supported by an appropriate, copractices), supported by an appropriate, co-ordinated mix of
ordinated mix of regional, national and EU policies.
regional, national and EU policies.
Financial
Conscious EU efforts (policies, guidelines, networking, exchange No conscious EU efforts to improve financial infrastructure in the
infrastructure
of experience) to improve financial infrastructure across the EU. laggard regions.
Policy-preparation
Conscious EU efforts (guidelines, networking, exchange of
No conscious EU efforts (guidelines, networking, exchange of
methods, practices
experience) to improve policymaking practices across the EU.
experience) to improve policy-making practices in the laggard
regions.
a. Co-operation with the relevant Triad partners is taken for granted, i.e. not discussed here as a distinguishing feature.
Table 3
Roles and features of universities in two EU visions:
‘Double success’ vs. ‘Successful multi-speed EU’
EU
‘Double success’
Universities
The role/mission of ‘Double-track’ mission of teaching and research at universities:
universities
contribution to tackle societal challenges, promote cohesion
and enhance competitiveness.
New types of activities at universities?
Mobility of
Universities located in advanced and laggard regions of the EU
researchers,
actively co-operate in promoting ‘Two-way traffic’ becomes a
university staff and wide-spread practice: gaining experience, building contacts in
students
more advanced regions, and then exploiting these contacts upon
return to ‘cohesion’ regions via intense, mutually beneficial
co-operation.
Grants offered by universities themselves explicitly aim at both
nurturing talents (for excellence in RTDI and competitiveness)
and fostering cohesion (students from laggard regions are
requested to return to their home regions for a certain period).
A certain degree of diversity among universities is maintained
in terms of attracting foreign staff and students (especially from
advanced Triad regions).
Integration of RTDI
Widely occurs across the EU and globally. Policies aimed at
activities (across
promoting the integration of RTDI activities also have an explicit
national boundaries) aim of fostering cohesion, among other EU-wide issues.
Universities actively participate in these co-operations.
‘Successful multi-speed EU’
Teaching and research at universities put excessive emphasis on
enhancing competitiveness.
‘One-way street’: brain-drain from laggard regions to booming
ones, promoted by grants offered by universities located in the
advanced regions.
Mainly among strong, successful regions across the Triad, driven
by businesses, supported by policies. Laggards are left out for
not having sufficient financial and intellectual resources and for
lacking modern infrastructure.
‘Elite’ universities are active partners in these processes, the
ones located in laggard regions seek partners in the advanced
regions (not paying attention to the cohesion needs of their own
home region).
Table 4
Driving forces and their likely impacts on universities
99
Teaching programmes put more emphasis on meeting
techno-economic (competitiveness) objectives at the expense
of societal challenges (preparing students mainly for jobs
of techno-economic relevance, with that sort of mindsets/
rationales, i.e. students are not trained to understand both
societal and techno-economic challenges).
Life-long learning is a daily practice mainly in the advanced EU
regions; in the laggard ones it is available for, and requested
by, only a tiny share of citizens. Universities located in the
advanced regions are flexible enough to offer the right ‘mix’ of
longer (traditional) and shorter courses, adjusted to the new
structure/balance of learning and working (frequent changes
between being a full- and part-time student or a full- and parttime employee, at the level of university ‘customers’). Most
universities located in the laggard regions are not prepared or
flexible enough to offer these ‘mixes’ of courses.
The Bologna process The Bologna process is also used to facilitate cohesion (by
The Bologna process is mainly advantageous for the advanced
making staff and student exchange programmes smoother,
EU regions (via intense staff and student exchange programmes
given the harmonisation of curricula).
among these regions).
Competition for
A large number of ‘world-class’ universities are located across
There are a fewer number of ‘world-class’ universities in the EU,
talents (students and the EU. They can all attract talents from the Triad because
mainly located in the most advanced regions, and only these
faculty)
there are no major intra-EU regional differences among the
can attract talents from the Triad (as there are major intra-EU
universities in terms of the quality of their teaching and research regional differences among the universities in terms of the
programmes, thanks to conscious efforts aimed at fostering
quality of their teaching and research programmes, given the
cohesion.
lack of cohesion efforts).
The diversity among HE institutes remains, some of them are
The diversity among HE institutes becomes even more
focusing on serving regional/local needs, mainly offering
pronounced, especially across the advanced and laggard
degrees and shorter courses required in the regional/local
EU-regions. A large number of HE institutes – most of them are
labour markets; i.e. these do not pay attention to attract talents located in the laggard regions, some in the advanced ones too
from other countries, not even from the EU.
– are focusing on serving regional/local needs, mainly offering
degrees required in the regional/local labour markets; i.e. these
do not pay attention to attract talents from other countries, not
even from within the EU.
Multidisciplinary
Multidisciplinary education becomes a widely used practice
Multidisciplinary education is offered in a limited sense: mainly
education/training
across the EU. It is particularly relevant to make students
integrating disciplines relevant for tackling techno-economic
understand the close relationships between societal and
(competitiveness) issues (i.e. somewhat neglecting societal
techno-economic issues/challenges.
issues).
Paper 5
Universities
‘Successful multi-speed EU’
Wo rki ng
EU visions
Trends,
‘Double success’
outcomes of
driving forces
New types of
Teaching programmes are balanced in terms of meeting societal
courses/degrees
and techno-economic (competitiveness) objectives (training
students to understand both societal and techno-economic
challenges, and the relationships between these issues;
developing relevant theoretical and practical skills; etc.).
Life-long learning becomes a reality (not just a slogan). Most
universities across the EU are flexible enough to offer the right
‘mix’ of longer (traditional) and shorter courses, adjusted to
the new structure/balance of learning and working (frequent
changes between being a full- and part-time student or a
full- and part-time employee, at the level of ‘customers’ of
universities).
The Future of Key Research Actors in the European Research Area
Multidisciplinary
research
Demographic trends
Evaluation criteria
Multidisciplinary research becomes a widely used practice
Multidisciplinary research is pursued in a limited sense: mainly
at universities across the EU. It is particularly relevant for
integrating disciplines relevant for tackling techno-economic
universities to play their important societal role by better
(competitiveness) issues (i.e. somewhat neglecting societal
understanding themselves the close relationships between
issues).
societal and techno-economic issues/challenges, as well as by
offering these new types of insights for other actors.
An ageing population is likely to lead to a different composition of students in terms of their age structure: the share of ‘mature’
students is likely to increase substantially. Thus, new methods and approaches are going to be used in HE to teach these
students. Furthermore, new types of contacts emerge between teachers (and other staff of HE institutes) and students, as well as
among students (coming from different age groups with different experiences).
Universities are evaluated by using a complex set of criteria,
Universities are mainly evaluated by using a limited set of
to assess how successful they are in tackling both societal and criteria, with a focus on assessing how successful they are in
techno-economic challenges/issues in their research activities; tackling techno-economic challenges/issues in their research
how well balanced their teaching programmes are in this
activities; and how well designed their teaching programmes in
respect; and how active they are in performing their societal
this respect.
roles.
An important trend – as a potential development,
i.e. not a ‘prediction’, – is the possibility of losing
the current monopoly of universities in terms of
legitimisation and validation of knowledge. This
trend can occur regardless of the ‘structure’ used
here (the alternative futures of the EU in the forms
of ‘Double success’ and ‘Successful multi-speed
EU’). Likewise, new methods, approaches, norms
to organise and manage universities are also
expected to emerge regardless of the alternative
futures devised here, and thus all these factors are
discussed in Table 7.
100
5.2 Visions from the perspective of
universities
We can devise visions from the perspective of
universities, too, assuming that EU ERIA ‘structures’
and main characteristics are ‘fixed’. Taking into
account the trends and drivers identified in Sections 3
and 4, three visions can be elaborated, as suggested
at the first meeting of this HLEG (6 July 2005):
• Universities
remain
largely
unchanged,
performing the same functions in roughly the
same organisational attributes (allowing for
efficiency improvements);
• Universities reform themselves – or are reformed –
radically by transforming their main functions
and/or organisational attributes;
• Universities disappear and their functions are
assumed/diffused in a completely different way,
e.g. by firms’ labs and universities, contract
research organisations (CROs), NGOs, etc.
Discussing a largely unchanged university system
only makes sense if we assume major changes in
the environment: when fundamental changes are
identified in the external conditions, extrapolating
the behaviour of an actor that is unwilling/unable to
change might be a powerful tool to warn key players
in that (sub-)system that they need to change their
attitudes, behaviour, and strategies. Thus, the
following sections use the above alternative visions
for the EU and ERIA – that is ‘Double success’ and
‘Successful multi-speed EU’, respectively – to
characterise/identify major changes in the external
environment of universities, and assess what are the
likely features of unchanged, radically reformed or
disappearing universities under those conditions
(Tables 5 and 6).
As already pointed out in Section 5.1., there are
important driving factors, which can occur regardless
of the ‘structure’ used here (the alternative futures
of the EU in the forms of ‘Double success’ and
‘Successful multi-speed EU’), and thus these are
discussed separately in Table 7.
Universities are, of course, diverse entities in terms
of their roles (the composition of various roles
they play), attitudes, norms and strategies, as well
as in their performance, as already pointed out
several times throughout this paper. Thus, a sort
of ‘average’ university is assumed in the following
sub-sections,
when
discussing
‘unchanged
universities’: not an extremely inward-looking,
inflexible, ‘sclerotic’ one, further characterised by
inertia and poor performance, and not a particularly
active one in various networks, a flexible, dynamic,
highly successful university, either – although we
can find such universities at each extreme. Radically
reformed universities, by contrast, are highly
flexible, and thus adapt their courses, teaching and
research approaches, as well as their organisational
structures, managerial practices and other internal
processes to the ever changing external environment,
expressed by the needs of their ‘clients’: students,
the wider research community, businesses, policymakers and the civil society. They possess excellent
‘navigation’ skills to find their way in this complex
world, often characterised by the conflicting
requirements of various stakeholders.
Table 5
Driving forces and their likely impacts on universities in the ‘Double success’ case
Only a few ‘world-class’ EU universities
can attract talents (students and staff )
from advanced Triad regions, and they are
also under increasing pressure from their
Triad-competitors.
Universities do not understand or assume
their role in addressing societal issues,
among them cohesion. Thus, inside the
EU, mobility is mainly a ‘one-way street’:
brain-drain prevails from laggard regions
to booming ones, promoted by grants
offered by universities located in the
advanced regions.
Integration of RTDI
Only a few’ world-class’ EU universities
activities (across
can join global networks at the forefront
national boundaries) of RTDI activities.
Inside the EU, some universities actively
participate in cross-border RTDI activities,
also aimed at promoting cohesion (via
enhanced competitiveness of laggard
regions), while the majority of universities
are only interested in so-called basic
research projects (conducted in the
logic of ‘pure science’, i.e. isolated from
innovation processes).
Courses/degrees
Mainly ‘traditional’ (BA, BSc, MA, MSc,
PhD) courses/degrees are offered,
following a ‘pure science’ rationale; i.e.
societal needs and competitiveness
issues are largely neglected.
Shorter, more practical courses – geared
towards the needs of job-seekers and
potential employers – are missing or
exceptional.
Life-long learning is perceived as a
challenge to centuries-long traditions,
and is neither understood nor taken as a
great opportunity.
Universities disappear
A new balance of the main activities
(teaching; academic research;
consultancy, trouble-shooting, and other
joint projects with businesses) and a new
way to conduct these activities in the
frame of intense interactions with other
players in various innovation systems
(regional, national, sectoral, international)
and with the society.
In the meantime, new activities/roles are
performed to promote cohesion among EU
regions and enhance competitiveness.
In sum, most universities understand
the societal and techno-economic
requirements of an ERIA in the ‘Double
success’ EU, and are able to adapt to this
new environment.
A large(r) number of EU universities
become attractive for talents (students
and staff ) from advanced Triad regions.
Universities located in advanced and
laggard regions of the EU actively cooperate in promoting ‘two-way traffic’:
gaining experience, building contacts
in more advanced regions, and then
exploiting these contacts upon return to
‘cohesion’ regions via intense, mutually
beneficial co-operation. These become
wide-spread practices.
Grants offered by universities themselves
explicitly aim at both nurturing talents (for
excellence in RTDI and competitiveness)
and fostering cohesion (students from
laggard regions are requested to return to
their home regions for a certain period).
A certain degree of diversity among
universities is maintained in terms of
attracting foreign staff and students
(especially from advanced Triad regions).
Widely occurs across the EU and
globally; policies aimed at promoting the
integration of RTDI activities also have an
explicit aim of fostering cohesion, among
other EU-wide issues.
Reformed universities – understanding
their responsibilities in improving quality
of life and enhancing competitiveness,
i.e. their roles beyond the ‘pure science’
rationale – actively participate in these
co-operations.
Teaching; academic research; consultancy,
trouble-shooting, and other joint projects
with businesses are performed by newly
emerging players and/or by current
‘competitors’ of universities.
The EU puts in place incentives to boost
new activities/roles performed by these
players to promote cohesion among EU
regions and enhance competitiveness in
the meantime.
Intense exchange programmes both with
advanced Triad regions and inside the EU
among the ‘successors’ of universities.
Grants, offered by the EU and the
governments of ‘cohesion’ countries, are
in place to promote competitive-ness
and cohesion at the same time (e.g. by
nurturing talents from laggard regions,
and also requesting students to return to
a ‘cohesion’ region).
An increasing number of these new
players understand the importance
of cohesion, and thus offer grants to
students from laggard regions, on the
condition that they return later.
Widely occurs across the EU and globally;
the ‘successors’ of universities actively
participate in these co-operations.
Carefully designed policies (incentives)
make these new players interested in
participating RTDI projects aimed at
fostering cohesion.
An increasing number of these new
players also understand the importance
of cohesion (in a broader ‘picture’ for their
own success), and thus have some own
initiatives, too, for mutually beneficial
co-operation with laggard regions.
Teaching programmes are balanced in
A great variety of courses and degrees
terms of meeting societal and technoare offered – in terms of focus/
economic (competitiveness) objectives
rationale, themes, duration, approaches
(training students to understand both
[theoretical/scientific vs. practical], etc. –
societal and techno-economic challenges, by a host of diverse actors.
and the relationships between these
‘Blurring boundaries’ between activities
issues; developing relevant theoretical
(learning and working/conducting
and practical skills; etc.).
research) and organisations?
Life-long learning becomes a reality (not Formal degrees might lose their
just a slogan); most universities across
importance, as opposed to practice
the EU are flexible enough to offer the
gained by working at or for certain,
right ‘mix’ of longer (traditional) and
prestigious organisations.
shorter courses, adjusted to the new
The type of practice/experience (e.g. firms
structure and balance of learning and
vs. NGOs) might become of overriding
working (frequent changes between being significance.
a full- and part-time student or a fullSocietal needs – among them cohesion –
and part-time employee, at the level of
are understood, and reflected in the
‘customers’ of universities).
curricula.
101
Paper 5
Universities
Mobility of
researchers,
university staff and
students
Radically reformed universities
Wo rki ng
Universities
Trends,
Largely unchanged universities
driving forces
The role/mission of The main emphasis is on teaching and
universities
so-called basic research (science for the
sake of science), not much interaction
with other players in various innovation
systems (regional, national, sectoral,
international) and with society.
Increasing tensions thus emerge
between these ‘traditional’ universities
and the societal and techno-economic
requirements of an ERIA in the ‘Double
success’ EU.
The Future of Key Research Actors in the European Research Area
The Bologna process Having gone through some initial
difficulties and resistance from
universities, the Bologna process
functions relatively smoothly in
coordinating the process of obtaining/
offering degrees, following a ‘pure
science’ logic.
102
The Bologna process is also used to
facilitate cohesion (by making staff and
student exchange programmes smoother,
given the harmonisation of curricula).
The Bologna process becomes irrelevant.
The number and diversity of the new
players make it hardly possible to coordinate their ‘HE’ activities.
As formal degrees might lose their
importance, there is no strong need to
harmonise/coordinate the process of
obtaining and offering degrees.
Competition for
For the majority of universities it is not
A large number of ‘world-class’
A very intense competition for talents
talents (students and a major concern, given the importance
universities are located across the
among the ‘successors’ of universities,
faculty)
of their national context (e.g. funding,
EU. They can all attract talents from
both intra-EU and globally. Given the
cultural and language factors). Their
the Triad because there are no major
success of the EU and the nature of
mindsets are against any sort of
intra-EU regional differences among the EU polices: (i) a large number of these
competition, measurement and evaluation universities in terms of the quality of
players are successful in the global
– beyond the traditional indicators of
their teaching and research programmes, competition; (ii) quite a few of them
scientometrics. This attitude leads to
thanks to conscious efforts aimed at
put emphasis on facilitating cohesion
(i) an inferior performance and thus a
fostering cohesion.
when designing courses and research
weakening position of these universities The diversity among HE institutes
programmes/projects (as a means to
vis-à-vis the leading Triad universities;
remains, some of them are focusing on
attract talents), due to the incentives
and (ii) growing tensions between the
serving regional/local needs, mainly
offered by the EU, and/or because of their
strategies of ‘traditional’ universities
offering degrees and shorter courses
own agenda, e.g. in the case of NGOs.
and the social and techno-economic
required in the regional/local labour
requirements of an ERIA in the ‘Double
markets; i.e. these do not pay attention to
success’ EU.
attract talents from other countries, not
even from the EU.
Multidisciplinary
Multidisciplinary education slowly
Multidisciplinary education becomes a
An increasing number of the ‘successors’
education and
becomes a more widely used practice,
widely used practice across the EU. It is
of universities offer multidisciplinary
training
but limited to the logic of ‘pure science’
particularly relevant to make students
training, partly because they realise the
(courses/degrees, for example, in
understand the close relationships
relevance of these courses, partly because
bioinformatics). In other words, the
between societal and techno-economic
of incentives provided by EU policies. The
complexities of societal issues and
issues/challenges.
latter ones are based on the rationale
competitiveness are not addressed;
that multidisciplinary education is highly
the full potential of multidisciplinary
appropriate to make students understand
education is not exploited.
the close relationships between societal
and techno-economic issues/challenges.
Multidisciplinary
Multidisciplinary research becomes a
Multidisciplinary research becomes
A vast majority of the new players conduct
research
more widely used practice, but conducted a widely used practice at universities
multidisciplinary research, given the
in the rationale of ‘pure science’. In other across the EU. It is particularly relevant
complexity of the tasks they are faced,
words, the complexities of societal issues for universities to play their important
and in response to the demand expressed
and competitiveness are not addressed. societal role by better understanding
by firms, policymakers (at various levels)
The full potential of multidisciplinary
themselves the close relationships
and society.
research is not exploited.
between societal and techno-economic
issues/challenges, as well as by offering
these new types of insights for other
actors.
Table 6
Driving forces and their likely impacts on universities in the ‘Successful multi-speed EU’ case
Teaching and research at universities
put excessive emphasis on enhancing
competitiveness.
Other activities of universities – e.g.
consultancy, trouble-shooting, and joint
RTDI projects with businesses – might
become of increasing importance,
also serving the goal of enhancing
competitiveness.
A large(r) number of EU universities
become attractive for talents (students
and staff ) from advanced Triad regions.
More conscious efforts on a ‘one-way
street’ type mobility inside the EU,
and thus a ‘more efficient’ brain-drain
from laggard regions to booming ones,
promoted by grants offered by universities
located in the advanced regions.
Most talents attracted to study in more
advanced regions of the EU do not return
to ‘cohesion’ regions, and thus the
latter ones cannot benefit from intense,
mutually beneficial co-operation with the
former ones, set up thanks to the links
built by students from laggard regions,
while studying in the more advanced
ones.
Grants offered by universities themselves
only aim at nurturing talents (for
excellence in RTDI and competitiveness);
fostering cohesion is a non-issue:
students from laggard regions are not
requested to return to their home regions.
Integration of RTDI
Only a few ‘world-class’ EU universities
Mainly among strong, successful regions
activities (across
can join global networks at the forefront across the Triad, driven by businesses,
national boundaries) of RTDI activities.
and supported by EU policies. Laggards
Inside the EU, some universities actively are left out for not having sufficient
participate in cross-border RTDI activities, financial and intellectual resources,
mainly aimed at further enhancing the
lacking modern infrastructure.
competitiveness of the advanced regions, ‘Elite’ universities are active partners
while the majority of universities are only in these processes, the ones located
interested in so-called basic research
in laggard regions seek partners in the
projects (conducted in the logic of ‘pure
advanced regions (not paying attention
science’, i.e. isolated from innovation
to the cohesion needs of their own home
processes).
region).
Courses/degrees
Mainly ‘traditional’ (BA, BSc, MA, MSc,
Teaching programmes put more
PhD) courses/degrees are offered,
emphasis on meeting techno-economic
following a ‘pure science’ rationale; i.e.
(competitiveness) objectives at the
societal needs and competitiveness
expense of societal challenges (preparing
issues are largely neglected.
students mainly for jobs of technoShorter, more practical courses – geared economic relevance, with that sort of
towards the needs of jobseekers and
mindsets/rationales, i.e. students are not
potential employers – are missing or
trained to understand both societal and
exceptional.
techno-economic challenges).
Life-long learning is perceived as a
Life-long learning is a daily practice
challenge to centuries-long traditions,
mainly in the advanced EU regions; in
and not understood/taken as a great
the laggard ones it is available for, and
opportunity.
requested by, only a tiny share of citizens.
Universities located in the advanced
regions are flexible enough to offer the
right ‘mix’ of longer (traditional) and
shorter courses, adjusted to the new
structure/balance of learning and working
(frequent changes between being a fulland part-time student or a full- and parttime employee, at the level of ‘customers’
of universities). Most universities located
in the laggard regions are not prepared
or flexible enough to offer these ‘mixes’
of courses.
Universities disappear
Teaching; academic research; consultancy,
trouble-shooting, and other joint projects
with businesses are performed by newly
emerging players and/or by current
‘competitors’ of universities.
The main rationale of performing various
activities and roles by these players is to
contribute to the process of enhancing
competitiveness.
Intense exchange programmes both with
advanced Triad regions and inside the EU
among the ‘successors’ of universities.
The main rationale for the intra-EU
exchange programmes is to contribute to
the process of enhancing competitiveness
(cohesion is a non-issue).
103
Widely occurs across the EU and globally;
the ‘successors’ of universities actively
participate in these co-operations.
There are no EU policies (incentives) to
make these new players interested in
participating in RTDI projects aimed at
fostering cohesion, and thus the main
rationale of these projects is to further
enhance the competitiveness of advanced
EU regions.
A great variety of courses/degrees
are offered – in terms of focus/
rationale, themes, duration, approaches
(theoretical/scientific vs. practical), etc. –
by a host of diverse actors.
‘Blurring boundaries’ between activities
(learning and working/conducting
research) and organisations?
Formal degrees might lose their
importance, as opposed to practice
gained by working at/for certain,
prestigious organisations.
The type of practice/experience (e.g. firms
vs. NGOs) might become of overriding
significance.
Competitiveness issues determine the
main subjects and approaches in the
curricula.
Paper 5
Universities
Radically reformed universities
Wo rki ng
Universities
Trends,
Largely unchanged universities
driving forces
The role/mission of The main emphasis is on teaching and
universities
so-called basic research (science for the
sake of science), not much interaction
with other players in various innovation
systems (regional, national, sectoral,
international) and with society.
Some of the ‘elite’ universities are
already well adapted to this model,
putting emphasis only on enhancing
competitiveness.
Mobility of
Only a few ‘world-class’ EU universities
researchers,
can attract talents (students and staff )
university staff and from advanced Triad regions, and they are
students
also under increasing pressure from their
Triad competitors.
Most universities do not pay attention to
societal issues, among them cohesion.
Thus, inside the EU, mobility is mainly
a ‘one-way street’: brain-drain prevails
from laggard regions to booming ones,
promoted by grants offered by universities
located in the advanced regions.
The Future of Key Research Actors in the European Research Area
The Bologna process Having gone through some initial
difficulties and resistance from
universities, the Bologna process
functions relatively smoothly in coordinating the process of obtaining/
offering degrees, following a ‘pure
science’ logic.
Competition for
For the majority of universities it is not
talents (students and a major concern, given the importance
faculty)
of their national context (e.g. funding,
cultural and language factors). Their
mindsets are against any sort of
competition, measurement and evaluation
– beyond the traditional indicators of
scientometrics. This attitude leads to an
inferior performance and a weakening
position of these universities vis-à-vis the
leading Triad universities, as well as to
growing tensions between the strategies
of ‘traditional’ universities and the
requirements of an ERIA in the ‘Successful
multi-speed EU’, putting the main
emphasis on enhanced competitiveness.
Multidisciplinary
education/training
Multidisciplinary education slowly
becomes a more widely used practice,
but limited to the logic of ‘pure science’
(courses/degrees e.g. in bioinformatics).
In other words, ‘cross-cutting’ issues
relevant to enhancing competitiveness
are not addressed; the full potential of
multidisciplinary training is not exploited.
Multidisciplinary
research
Multidisciplinary research becomes a
more widely used practice, but conducted
in the rationale of ‘pure science’. In
other words, ‘cross-cutting’ issues
relevant to enhancing competitiveness
are not addressed; the complexities of
societal issues and competitiveness
are not addressed; the full potential
of multidisciplinary research is not
exploited.
104
The Bologna process is mainly
advantageous for the advanced EU
regions (via intense staff and student
exchange programmes among these
regions).
The Bologna process becomes irrelevant.
The sheer number and diversity of the
new players make it hardly possible to
co-ordinate their ‘HE’ activities.
As formal degrees might lose their
importance, there is no strong need to
harmonise/coordinate the process of
obtaining and offering degrees.
‘World-class’ universities are mainly
A very intense competition for talents
located in the most advanced regions
among the ‘successors’ of universities,
of the EU, and only these can attract
both intra-EU and globally. Given the
talents from the Triad (as there are major success of the EU and the nature of EU
intra-EU regional differences among the polices, a large number of these players
universities in terms of the quality of their are successful in this competition.
teaching and research programmes, given The main rationale behind being active
the lack of cohesion efforts).
in this competition for talents is to foster
The diversity among HE institutes
competitiveness of the advanced regions,
becomes even more pronounced,
i.e. cohesion is eclipsed when designing
especially across the advanced and
courses and research programmes/
laggard EU-regions. A large number of
projects (as a means to attract talents).
HE institutes – most of them are located
in the laggard regions, some in the
advanced ones, too – are focusing on
serving regional/local needs, mainly
offering degrees required in the regional/
local labour markets; i.e. these do not
pay attention to attract talents from other
countries, not even from the EU.
Multidisciplinary education is offered
An increasing number of the new players
in a limited sense: mainly integrating
offer multidisciplinary training, partly
disciplines relevant for tackling technobecause they realise the relevance
economic (competitiveness) issues (i.e.
of these courses, partly because of
somewhat neglecting societal issues).
incentives provided by EU policies. The
latter ones are based on the rationale
that multidisciplinary education is
instrumental to enhance competitiveness,
e.g. to make students understand the
close relationships between economic
success and innovation (the latter, in
turn, being a complex issue in itself:
the technological, managerial and
organisational aspects, and their
combination should be addressed).
Multidisciplinary research is pursued
A vast majority of the new players conduct
in a limited sense: mainly integrating
multidisciplinary research, in response
disciplines relevant for tackling technoto the demand expressed by firms and
economic (competitiveness) issues (i.e.
policymakers to enhance competitiveness.
somewhat neglecting societal issues).
Table 7
Further driving forces and their likely impacts on universities
Ever more
expensive physical
infrastructure for
education and
research
The impacts of new
technologies on HE
Radically reformed universities
Universities disappear
An ageing population is likely to lead to
a different composition of students in
terms of their age structure: the share
of ‘mature’ students is likely to increase
substantially. Thus, new methods/
approaches are going to be used at
reformed universities to teach these
students. Further, new types of contacts
emerge between teachers (and other staff
of HE institutes) and students, as well as
among students (coming from different
age groups, with different experiences).
A vast majority of the ‘successors’ of
universities understand the importance
of introducing new methods/approaches
to teach a different ‘population’ of
students (a significantly higher share of
‘mature’ students). New types of contacts
emerge between teachers (and other
staff of education service providers) and
students, as well as among students
(coming from different age groups, with
different experience).
Universities seek partnerships with
Universities are replaced by other
other knowledge producers, as well
knowledge producers and stakeholders in
as government agencies and NGOs to
the process of validating knowledge.
establish new rules – and organisations, if
necessary – to validate knowledge jointly
in a mutually acceptable way.
An overall outward-looking, pro-active
attitude prevails: to seek new partners,
new funding sources, new ideas for
curricula and research, new roles/
responsibilities.
Modern management techniques (e.g.
personnel, financial, organisational
and marketing management, strategic
planning) are applied.
Evaluation (efficiency, impacts) is seen
as a useful tool to improve performance,
enhance visibility and social esteem.
A large number of ‘traditional’ universities An increasing number of radically
cannot cope with these pressure as
reformed universities are likely to be able
their performance is not good enough
to generate the required extra revenues,
to generate revenues, and/or attract
and/or attract external funding, given
external funding.
their substantially improved performance.
A smaller number of ‘elite’ universities are
likely to be able to generate the required
extra revenues, and/or attract external
funding, given their sustained superior
performance and prestige.
New technologies are perceived as threats An increasing number of radically
by quite a few ‘traditional’ universities;
reformed universities are likely to be
some of them can benefit from them.
able to benefit from new technologies
A smaller number of ‘elite’ universities
by successfully incorporating them into
are likely to be able to benefit from
their education and research activities,
new technologies by successfully
and thus substantially improving their
incorporating them into their education
performance.
and research activities, and thus further
improving their performance and boosting
prestige.
Paper 5
Universities
105
Not applicable.
A great diversity among the new players in
terms of their capabilities to generate the
required extra revenues, and/or attract
external funding.
A great diversity among the new players in
terms of their capabilities to benefit from
new technologies.
Wo rki ng
Universities
Trends,
Largely unchanged universities
driving forces
Demographic trends An ageing population is likely to lead to
a different composition of students in
terms of their age structure: the share
of ‘mature’ students is likely to increase
substantially. Yet, traditional universities
do not understand the importance of
introducing new methods/approaches
to teach these students, or are reluctant
to introduce these changes. Further,
new types of contacts would be needed
between teachers (and other staff of
HE institutes) and mature students, but
these are also prevented by centuries-old
traditions.
Legitimisation,
Universities push hard to maintain their
validation of
centuries-old monopoly to validate
knowledge
knowledge. At the same time a number
of other organisations (e.g. think tanks,
private research organisations, private
non-profit research organisations,
government laboratories, consultancy
firms, patient organisations, various
NGOs, trade associations and interest
groups) are increasingly producing
knowledge.
Four options can be envisaged (following
Bonaccorsi [2005]):
a) universities progressively lose their
power to validate knowledge produced
outside their domain;
b) universities maintain their power to
validate knowledge produced outside
their domain;
c) a new public authority is set up to
validate knowledge produced by a large
variety of actors;
d) a clear separation of knowledge
produced by universities (and other
credible research organisations) on the
one hand, and knowledge produced by
other sources with a ‘lower status’, on
the other.
Methods,
An overall ‘inward-looking’ (passive,
approaches, norms to ‘traditionalist’) attitude prevails. Modern
organise and manage management techniques (e.g. personnel,
financial, organisational and marketing
management, strategic planning) might
be taught, but not applied. Evaluation
(efficiency, impacts) is seen as a burden.
The Future of Key Research Actors in the European Research Area
6. Impact analysis of scenarios on the ERIA
The likely impacts of the various visions for universities, depicted above, would heavily depend on the types
and intensity of the links between various research actors, and thus it should be a collective exercise for the
group as a whole to discuss this issue. Some preliminary thoughts are presented in Table 8 below.
Table 8
Key players of ERIA and their links
Prevailing ‘pure S&T’ rationale
Universities
Promote prestige/self-esteem (science
for the sake of science).
Secure/increase funding.
Public laboratories
Promote prestige/self-esteem (science
for the sake of science).
Secure/increase funding.
Academia–business links
Ad hoc links (they are the exception).
Society
Source of conflicts (or ignored).
Academia–society links
‘Uneven’ development: driven by the
agenda and needs of the academia.
EU policymakers
Secondary role; promoting businessdriven projects.
106
National policymakers
Prevailing business rationale:
Prevailing societal/socio-economic
‘Multi-speed success EU’
rationale: ‘Double success’
A few ‘elite’ universities ↔ ‘second and Teaching and research aimed at
third class’ ones (‘sub-contractors’ to
addressing societal issues and
the elite).
competitiveness at the same time.
Important role in setting local, regional,
national EU agenda/policies.
Main mission: to promote the
Research aimed at addressing societal
competitiveness of the advanced
issues and competitiveness at the same
regions of the EU.
time.
Important role in setting local, regional,
national EU agenda/policies.
Intense, business-driven links, funds
Intense, significant, but not at the
and ideas (challenges) for HE/R from
expense of addressing societal issues
businesses (both for curricula/teaching by the academia.
and research).
Posing ‘constrains’ (e.g. ethical,
Has a strong say in setting HE/R
environmental issues) – or perceived as objectives, policies, evaluation.
consumers.
Secondary issue.
Dialogue among equal partners.
Funding a few prestige projects
(following a ‘pure science’ logic).
Important (but not predominant) role
together with other actors, pressing
forward societal issues/interests;
promoting society-driven projects with
EU policy tools.
Policy schemes and framework
Policy schemes and framework
conditions are designed to support RTDI conditions are designed to support RTDI
projects aimed exclusively at enhancing projects aimed at socio-economic goals.
competitiveness.
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110
6
W o r k in g
Paper
Universities – Statistical Annex
Box 1
Box 4
Max Planck Institutes. Research Units. and
Working Groups
CSIC. Spain: Key figures
More than 12 000 staff members and 9 000
Ph.D. students. post-docs. guest scientists and
researchers. and student assistants work at the 80
research institutes of the Max Planck Society.
Source: http://www.mpg.de/english/institutesProjectsFacilities/index.html
Budget: €700.8 million (of which 26.13 per cent own
resources)
Personnel:
• 2 369 scientists
• 3 896 graduate and postgraduate researchers
• 4 084 support staff
Box 2
Budget for 2005: €2.299 billion (of which €333
million generated by CNRS)
Personnel:
• 26 080 permanent employees
• 11 644 researchers
• 14 416 engineers and technical staff
Source: http://www.csic.es/quien_somos.doc
Box 5
Academy of Sciences. Hungary: Key figures.
2004
Organisation:
• 6 research departments
• 2 national institutes
• 19 regional offices ensuring decentralised direct
management of laboratories
• 1 256 research and service units (85 per cent are
joint laboratories)
Source: http://www2.cnrs.fr/en/345.htm
Box 3
CNR (Italy) personnel activity. 2002
Type of contract
Payroll Researchers*
Contract Researchers*
Organisation:
• 116 centres (of which 40 are mixed centres and 10
services centres)
• 134 units associated with universities and other
institutions
Employees
%
3 992
49.8
292
3.6
Total Researchers*
4 284
53.4
Total Technicians
2 632
32.8
Total Administrative
1 099
13.7
Total personnel
8 015
100.0
* Including technologists
Source: http://www.cnr.it/sitocnr/Englishversion/CNR/Dataandstatistics/Resources/Staff
Budget: 29 716 million HUF (equivalent to 17.2
per cent of Hungary’s Gross Expenditure on R&D
[GERD])
Personnel:
• 2 862 scientists (full-time equivalent. FTE).
(equivalent to 19.2 per cent of total research
scientists and engineers [RSE])
• 865 technicians (FTE). (equivalent to 18.4 per
cent of total technicians [FTE])
Publications:
• 26.8 per cent of total books and book chapters
published by Hungarian authors abroad
• 27.0 per cent of total articles published in
scientific journals by Hungarian authors abroad
Organisation:
• 38 research institutes
• 171 research units associated with universities
Source: Research and development. 2004. Budapest. CSO; http://www.mta.hu
111
Wo rki ng Paper 6
Statistical Annex
CNRS. France: Key figures
The Future of Key Research Actors in the European Research Area
29.4
60.5
39.5
Slovenia
59.7
40.3
Cyprus
58.3
41.7
Belgium
36 167
Poland
56.2
43.8
Czech Republic
Hungary
54.0
46.0
Denmark
France
47.0
53.0
Germany
Germany
44.5
55.5
Estonia
Japan
40.5
59.5
Greece
Business
enterprise
70.6
Czech Republic
Average annual
growth rates of
sectoral shares (%).
1997-2003 (2)
Government
Slovakia
7.4
34.6
0.8
4.1
-1.8
30.6
27.3
0.3
-2.9
3.2
9.3
30.5
3.7
-3.4
-3.1
0.5
-1.2
-0.4
9.8
-5.4
-0.7
12.4
-6.6
-2.2
Business
enterprise
4.4
in % by sector.
2003 (1)
Business
enterprise
HERD
95.6
57.2
15 809
41.5
25 130
59.7
264 721
58.1
14.7
27.2
2 976
15.6
16.1
66.3
14 371
26.4
13.8
59.5
37.0
63.0
Spain
92 523
29.8
16.7
53.2
1.5
-3.8
0.8
35.6
64.4
France
186 420
51.1
12.9
34.1
1.6
-0.4
-1.9
US
35.1
64.9
Ireland
9 386
63.8
6.4
29.8
4.7
-5.7
-4.6
Italy
34.9
65.1
Italy
71 242
39.3
19.0
39.7
-1.3
-1.8
1.4
Spain
33.6
66.4
Cyprus
460
27.2
23.9
44.6
9.4
-7.0
0.2
Finland
33.5
66.5
Latvia
3 203
14.5
16.1
69.4
8.3
-13.9
5.1
Lithuania
33.4
66.6
Lithuania
6 606
6.7
25.5
67.8
26.4
-6.6
2.2
Netherlands
32.4
67.6
Luxembourg
1 646
85.0
13.6
1.3
..
..
..
Greece
31.5
68.5
Hungary
15 180
29.5
31.2
39.2
1.3
-1.9
0.7
43 539
46.9
15.6
36.4
2.7
-1.5
-2.7
66.3
4.1
28.9
1.5
-5.1
-2.4
EU-25
(2)
Latvia
112
Researchers (FTE) by institutional sector
Higher
education
GOVERD
Luxembourg
Data sheet 1
Government
Shares of government and higher education
R&D expenditures in total public expenditure
on R&D (%). 2003(1)
Total reseachers 2003 (1)
Figure 1
United Kingdom
31.0
69.0
Netherlands
Portugal
29.0
71.0
Austria
24 124
Ireland
28.0
72.0
Poland
58 595
11.7
22.6
65.6
-8.5
1.2
1.8
Belgium
26.7
73.3
Portugal
19 766
19.4
16.2
51.4
14.2
-4.5
-1.1
Estonia
25.0
75.0
Slovenia
4 789
36.2
32.0
28.3
1.0
-1.4
-0.1
Denmark
23.0
77.0
Slovakia
9 626
19.9
25.3
54.8
-8.5
0.4
4.8
Austria
17.4
82.6
Finland
41 724
56.6
11.3
31.2
1.4
-4.6
-0.6
Sweden
12.8
87.2
Sweden
45 995
60.6
4.9
34.5
1.7
-7.2
-1.5
Source: DG Research – Key Figures 2005
Data: Eurostat. OECD
Notes:
(1) LU. SE: 2001; IE. IT. NL. AT: 2002; BE: 2004.
(2) EU-25 was estimated by DG Research and does not include LU and MT.
UK
157 662
57.9
9.1
31.1
1.0
0.6
-2.1
EU-25(3)
1 178 237
49.0
13.4
36.5
0.9
-2.5
-0.2
US
1 261 227 80.5
3.8
14.7
0.8
-6.1
-2.1
Japan
675 330
5.0
25.5
-0.4
0.8
1.6
67.9
Source: DG Research – Key Figures 2005
Data: Eurostat. OECD
Notes:
(1) UK: 1998; US: 1999; LU: 2000; EL. SE: 2001; FR. IE. IT. NL. AT: 2002; BE: 2004.
(2) UK: 1996-1998; IE. NL. US: 1997-1999; DK. EL. ES. SE. JP: 1997-2001; FR. IT: 1997-2002;
AT: 1998-2002; CY: 1998-2003. BE 1998-2004.
(3) EU-25 was estimated by DG Research and does not include LU and MT.
Number of researchers (FTE) per 1 000 labour
force. 2003(1) and annual growth rates (in
brackets). 1997-2003(2)
Data sheet 2
Higher Education researchers as a percentage
of the national total. 1981-2004
1981 1990 1991 1999 2000 2001 2002 2003 2004
16.2
Australia
56.2 47.9
..
..
59.9
..
58.3
..
..
Sweden (4.6)
10.1
Austria
45.5
..
..
..
..
..
28.9
..
..
Japan (2.1)
10.1
Belgium
51.7
..
US (3.2)
9.0
Canada
46.7 41.5 42.3 33.4 30.7 29.8
Luxembourg (na)
8.7
Czech Republic
Denmark (2.1)
8.6
Denmark
Belgium (3.8)
7.9
Finland
France (3.0)
6.8
France
Germany (1.5)
6.3
Germany
22.8
United Kingdom (4.1)
5.5
Greece
Austria (5.7)
5.5
Hungary
EU-25 (2.8)
5.4
Ireland
39.1 50.1 48.1
Netherlands (1.2)
5.1
Italy
47.5 40.9 43.9 38.7 38.9 40.7 39.7
Ireland (2.5)
5.0
Japan
41.6
36
Slovenia (2.7)
5.0
South Korea
..
..
Spain (7.5)
4.9
Netherlands
31.5
..
Estonia (0.3)
4.5
Norway
38.7
..
Lithuania (-1.5)
4.0
Poland
..
Slovakia (-1.4)
3.7
Portugal
..
Portugal (4.5)
3.6
Slovak Republic
..
Hungary (4.5)
3.6
Spain
Poland (1.0)
3.5
Sweden
Greece (5.8)
3.3
United Kingdom 19.7 21.1 22.7
Czech Republic (4.2)
3.0
United States
14.4
..
14.1 14.8
Latvia (4.3)
2.9
Total OECD
24.2
..
23.8 26.4
2.8
European Union 32.0
..
Finland (7.1)
Italy (0.7)
Cyprus (10.3)
1.2
Source: DG Research – Key Figures 2005
Data: Eurostat. OECD
Notes:
(1) UK: 1998; US: 1999; LU: 2000; EL. SE: 2001; FR. IE. IT. NL. AT: 2002; BE: 2004.
(2) U
K: 1996-1998; IE. NL. US: 1997-1999; DK. EL. ES. SE. JP: 1997-2001; FR. IT: 1997-2002;
AT: 1998-2002; CY: 1998-2003. BE 1998-2004.
(3) EU-25 was estimated by DG Research and does not include LU and MT.
Source: OECD.
..
..
46.4 39.3 38.6 37.3 37.4 35.6
..
25
38.5 35.2 34.3 30.2
31
..
..
..
27.2 28.4 28.6 27.3 26.2
31.4 28.9 30.0
..
38.9 32.3 31.6 29.8 32.1 31.2
..
38.2 32.2 32.5 35.4 35.8 35.2 34.1 33.4
..
..
..
..
..
25.7 26.2
26
25.7 26.8 25.4
..
..
..
52.5 71.0
..
59.5
..
..
29.7
34
..
29
25.2 27.6 29.8 34.6 38.0
..
35.8 27.1 27.7 29.6 26.4 25.5
..
..
..
21.7 21.8 16.9 17.6 17.5
..
30.9 36.8 34.6 36.4
..
..
29.8
..
62.5 62.1 64.3 65.7 65.6
..
63.6 54.1 52.3 51.3 50.4 50.1 49.7
..
..
..
30.9 30.2
..
..
64.4 50.2 51.1
38
..
37.9 40.6 40.5 40.1 39.2 39.6
..
46.2 50.3
55
43.2 36.6
..
..
..
28.3
51
..
50.4 54.8 60.7
54.9 58.6 54.9 53.2
..
..
34.5
..
35.8
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
36.3 37.0 37.2 37.1
113
W o r ki ng Paper 6
Statistical Annex
Figure 2
The Future of Key Research Actors in the European Research Area
Data sheet 3
Data sheet 5
Business Enterprise researchers as a
percentage of the national total.
1981-2004
114
Australia
Austria
Belgium
Canada
Czech Republic
Denmark
Finland
France
Germany
Greece
Hungary
Ireland
Italy
Japan
South Korea
Netherlands
Norway
Poland
Portugal
Slovak Republic
Spain
Sweden
United Kingdom
United States
Total OECD
European Union
1981
14.3
43.0
40.4
38.1
..
34.4
..
41.0
61.8
..
..
28.7
37.4
49.1
..
43.4
41.8
..
..
..
16.7
53.6
60.6
73.0
61.2
50.0
1990
29.2
..
..
45.1
..
41.6
..
46.0
..
..
43.5
37.5
40.5
56.8
..
..
..
..
7.4
..
29.2
..
62.4
..
66.3
..
1991
..
..
48.3
44.5
..
42.8
36.8
45.9
58.3
16.7
36.9
41.2
39.3
57.0
..
..
50.0
..
11.6
28.6
50.2
62.5
79.1
64.9
..
1999
..
..
53.8
58.7
42.9
47.9
53.0
47.0
59.0
15.2
25.9
67.2
40.2
65.8
65.3
47.9
53.2
18.3
12.7
27.4
24.7
57.2
..
80.6
64.0
47.3
2000
24.6
..
54.6
61.9
39.9
..
54.6
47.1
59.4
..
27.1
66.1
39.5
65.1
66.3
47.6
..
17.8
14.1
24.3
27.2
..
..
80.5
63.8
47.1
2001
..
..
55.8
63.8
38.4
49.6
56.9
49.9
59.7
26.4
27.8
66.7
39.8
63.7
73.5
49.2
56.3
16.9
15.4
23.5
23.7
60.6
..
80.3
64.0
48.0
2002
28.1
66.3
55.1
61.8
41.3
61.6
55.1
51.1
58.5
..
29.0
63.9
39.3
66.7
73.4
46.9
8.3
17.2
23.6
29.6
..
..
79.9
64.3
48.4
Percentage of Gross Expenditure on R&D (GERD)
performed by the Higher Education sector.
1981-2004
2003
..
..
56.6
..
41.5
60.3
56.6
52.2
60.2
..
29.5
59.9
..
67.9
73.6
..
54.7
11.7
18.7
19.9
29.8
59.4
..
..
..
49.4
2004
..
..
..
..
44.8
..
..
..
..
..
28.9
56.8
..
..
..
..
..
..
..
16.9
..
..
..
..
..
..
Australia
Austria
Belgium
Canada
Czech Republic
Denmark
Finland
France
Germany
Greece
Hungary
Ireland
Italy
Japan
South Korea
Netherlands
Norway
Poland
Portugal
Slovak Republic
Spain
Sweden
United Kingdom
United States
Total OECD
European Union
Source: OECD.
Source: OECD.
Data sheet 4
Data sheet 6
Government researchers as a percentage of
the national total. 1981-2004
Australia
Austria
Belgium
Canada
Czech Republic
Denmark
Finland
France
Germany
Greece
Hungary
Ireland
Italy
Japan
South Korea
Netherlands
Norway
Poland
Portugal
Slovak Republic
Spain
Sweden
United Kingdom
United States
Total OECD
European Union
Source: OECD.
1981
28.1
8.1
5.0
14.2
..
25.9
..
18.4
14.3
..
..
30.2
15.1
7.4
..
23.4
18.5
..
..
..
18.8
8.0
15.7
8.7
11.7
16.0
1990
21.5
..
..
12.6
..
21.8
..
20.1
..
..
26.9
8.6
18.6
5.1
..
..
..
..
18.5
..
20.2
..
11.3
..
..
..
1991
..
..
4.3
12.3
..
21.4
23.1
20.0
16.0
30.8
29.1
6.8
16.8
4.9
..
19.2
..
23.8
..
19.9
6.5
11.7
5.9
9.9
..
1999
..
..
5.8
7.5
31.6
20.7
13.7
15.7
14.9
13.6
36.2
3.8
21.0
4.7
11.7
19.9
16.6
19.2
21.9
26.4
19.4
6.1
..
3.8
8.3
15.2
2000
13.2
..
5.9
7.1
31.9
..
12.9
15.2
14.6
..
32.3
8.7
21.7
4.8
10.7
14.1
..
20.1
21.2
25.4
16.6
..
..
3.7
8.2
14.7
2001
..
..
6.0
6.3
32.3
18.0
12.3
12.9
14.6
13.8
31.8
5.6
19.5
5.0
8.8
14.9
15.4
18.7
20.6
25.4
16.7
4.9
..
3.7
7.7
13.5
2002
11.0
4.1
6.7
6.9
29.6
8.9
11.9
12.9
14.7
..
30.9
6.3
19.0
5.2
8.0
15.6
..
25.9
18.7
25.9
15.2
..
..
3.6
7.7
13.2
2003
..
..
7.0
..
30.6
9.2
11.3
12.7
14.4
..
31.2
5.5
..
5.0
7.9
15.5
22.6
17.0
25.3
16.7
4.8
..
..
..
13.4
2004
..
..
..
..
28.6
..
..
..
..
..
31.5
5.1
..
..
..
..
..
..
..
21.9
..
..
..
..
..
..
1981
28.5
32.8
..
26.7
..
26.7
22.2
16.4
17.1
14.5
..
16.0
17.9
24.2
..
23.2
29.0
..
..
..
22.9
30.0
13.6
14.5
16.7
17.8
1990
25.5
..
..
29.6
..
23.6
18.7
14.6
14.6
..
14.4
23.5
20.7
17.6
..
28.0
..
..
36.0
4.4
20.4
..
15.6
14.4
15.8
17.8
1991
..
..
26.2
30.6
1.6
22.6
22.1
15.1
16.2
33.8
20.3
23.2
21.5
17.5
..
29.7
26.7
..
40.3
3.9
22.2
27.4
16.7
14.5
16.3
..
1999
..
..
21.0
28.8
12.3
19.4
19.7
17.2
16.5
49.5
22.3
20.7
31.5
14.8
12.0
26.2
28.6
27.8
38.6
9.9
30.1
21.4
19.6
11.5
16.0
20.8
2000
26.8
..
20.2
28.2
14.2
..
17.8
18.8
16.1
..
24.0
20.2
31.0
14.5
11.3
27.8
..
31.5
37.5
9.5
29.6
..
20.6
11.5
16.0
21.1
2001
..
..
19.7
28.3
15.7
18.9
18.1
18.9
16.4
44.9
25.7
21.8
32.6
14.5
10.4
27.0
25.7
32.7
36.7
9.0
30.9
19.8
21.7
12.1
16.5
21.5
2002
26.7
27.0
20.2
33.2
15.6
23.1
19.2
18.9
17.0
..
25.2
22.4
32.8
13.9
10.4
28.8
26.8
33.9
36.7
9.1
29.8
..
22.3
13.5
17.3
22.1
2003
..
..
21.2
35.7
15.3
22.8
19.2
19.4
16.9
48.1
26.7
25.2
..
13.7
10.1
..
27.5
31.7
37.5
13.2
30.3
22.0
21.4
13.7
17.4
22.1
2004
..
..
..
38.1
14.8
..
..
19.1
16.3
..
24.8
27.4
..
..
..
..
..
..
38.4
20.1
..
..
..
13.6
..
..
2003
..
..
74.0
53.0
61.0
69.7
70.5
62.3
69.8
30.1
36.7
69.9
..
75.0
76.1
..
57.5
27.4
33.2
55.2
54.1
74.1
65.7
69.8
67.7
63.3
2004
..
..
74.5
51.2
63.7
..
..
62.9
70.4
..
41.5
64.8
..
..
..
..
..
..
..
49.2
..
..
..
..
..
..
Percentage of GERD performed by the
Business Enterprise sector. 1981-2004
Australia
Austria
Belgium
Canada
Czech Republic
Denmark
Finland
France
Germany
Greece
Hungary
Ireland
Italy
Japan
South Korea
Netherlands
Norway
Poland
Portugal
Slovak Republic
Spain
Sweden
United Kingdom
United States
Total OECD
European Union
Source: OECD.
1981
25.0
55.8
..
48.1
..
49.7
54.7
58.9
69.0
22.5
..
43.6
56.4
60.7
..
53.3
52.9
..
..
..
45.5
63.7
63.0
70.3
65.7
62.0
1990
40.2
..
..
50.4
..
56.9
62.6
60.4
72.1
..
38.1
60.0
58.3
70.9
..
52.9
..
..
26.1
64.1
57.8
..
69.4
72.0
69.3
64.8
1991 1999 2000
..
.. 47.8
..
..
66.5 71.6 72.7
49.7 59.0 60.1
69.4 62.9 60.0
58.5 64.9 ..
57.0 68.2 70.9
61.5 63.2 62.5
69.3 69.8 70.3
26.1 28.5 ..
41.4 40.2 44.3
63.6 73.3 71.6
55.8 49.3 50.1
70.7 70.7 71.0
..
71.4 74.0
49.7 56.4 58.4
54.6 56.0 ..
..
41.3 36.1
23.4 22.7 27.8
74.6 62.6 65.8
56.0 52.0 53.7
68.5 75.1
..
67.1 66.8 65.0
72.5 74.9 75.2
68.7 69.3 69.7
.. 63.6 63.9
2001
..
..
73.7
60.9
60.2
68.6
71.1
63.2
69.9
32.7
40.1
70.1
49.1
73.7
76.2
58.4
59.7
35.8
31.8
67.3
52.4
77.6
66.2
73.0
69.3
64.0
2002
48.8
66.8
73.3
55.4
61.1
69.0
69.9
63.3
69.2
..
35.5
68.8
48.3
74.4
74.9
56.7
57.4
20.3
31.8
64.3
54.6
..
66.2
70.2
67.8
63.4
Data sheet 7
Data sheet 9
Percentage of GERD performed by the
Government sector. 1981-2004
Australia
Austria
Belgium
Canada
Czech Republic
Denmark
Finland
France
Germany
Greece
Hungary
Ireland
Italy
Japan
South Korea
Netherlands
Norway
Poland
Portugal
Slovak Republic
Spain
Sweden
United Kingdom
United States
Total OECD
European Union
1981
45.1
9
..
24.4
..
22.7
22.5
23.6
13.4
63.1
..
39.3
25.7
11.1
..
20.8
17.7
..
..
..
31.6
6.1
20.6
12.1
15
18.8
1990
32.6
..
..
19.1
..
18.3
18.8
24.2
12.9
..
19.5
14.8
20.9
7.5
..
17.1
..
..
25.4
31.5
21.3
..
13.1
10.5
12.4
16.5
1991
..
..
6.1
18.7
29
17.7
20.2
22.7
14.4
40.1
24.5
11.6
22.7
7.6
..
18.3
18.8
23.4
21.5
21.3
4.1
14.5
9.8
12.4
1999
..
..
6.2
11.9
24.3
14.5
11.4
18.1
13.8
21.7
32.3
6
19.2
9.9
14.5
16.5
15.4
30.8
27.9
27.5
16.9
3.4
12.2
11
12.3
14.7
2000
22.6
..
6.3
11.4
25.3
..
10.6
17.3
13.6
..
26.1
8.1
18.9
9.9
13.3
12.8
..
32.2
23.9
24.7
15.8
..
12.6
10.3
11.8
14.2
2001
..
..
6.2
10.6
23.7
11.8
10.2
16.5
13.7
22.1
25.9
8.1
18.4
9.5
12.4
13.8
14.6
31.3
20.8
23.7
15.9
2.8
9.8
11.3
11.9
13.5
2002
19.3
5.7
7.1
11.2
23
7.4
10.4
16.5
13.7
..
32.9
8.7
17.6
9.5
13.4
13.8
15.8
45.5
18.8
26.6
15.4
..
8.8
12.2
12.3
13.4
Higher Education researchers (FTE).
1981-2004
2003
..
..
6.8
11
23.3
6.8
9.7
16.7
13.4
20.9
31.3
7.9
..
9.3
12.6
15.1
40.7
16.9
31.6
15.4
3.5
9.7
12.4
12.3
13.4
2004
..
..
..
10.5
21.2
..
..
16.7
13.2
..
29.8
7.8
..
..
..
..
..
..
..
..
..
..
..
12.2
..
..
Source: OECD.
1981 1990 1991 1999 2000 2001 2002 2003 2004
Australia
Austria
Belgium
Canada
Czech Republic
Denmark
Finland
France
Germany
Greece
Hungary
Ireland
Italy
Japan
South Korea
Netherlands
Norway
Poland
Portugal
Slovak Republic
Spain
Sweden
United Kingdom
United States
Total OECD
European Union
Source: OECD.
13 610 20 667
..
39 507
42 780
3 051
..
..
..
6 977
6 588
..
8 405 11 673 11 778 12 034 12 272 12 294
18 230 27 300 28 680 33 020 33 300 34 200 34 910
..
..
3 380 3 768 4 249 4 283 4 318 4 274
2 611 4 045 4 138 5 722 5 813 6 021 7 379 7 666
..
..
5 455 10 555 10 999 11 008 12 392 13 033
32 700 39 883 42 146 56 717 61 583 62 427 63 555 64 403
28 470
..
62 171 66 695 67 087 67 962 71 292 68 243
..
..
3 270 10 471
..
8 544
..
5 204 4 926 4 768 5 852 5 938 5 999 5 957 5 902
827
2 315 2 482 2 286 2 148 2 473 2 797 3 474 4 151
24 754 31 845 33 007 25 209 25 696 27 146 28 301
163 264 209 898 214 462 178 418 179 116 200 272 170 512 172 396
..
..
21 723 23 674 23 083 24 953 26 419
6 123 12 310 12 460 12 491 15 480 15 750 15 828
2 901
..
..
..
..
..
4 154 5 521
..
5 670
6 251
35 284 34 246 36 597 37 275 38 455
3 755 4 647 8 242 8 592 8 942 9 502 10 062
..
4 254 5 009 4 891 4 629 5 273 6 509
12 410 18 904 20 775 33 840 42 064 46 964 45 727 49 196
11 447 14 623
..
25 000 28 000 29 000 49 023
6 800
..
..
98 300
..
138 259 186 049
..
382 158
..
571 681 869 246
..
156 249
..
15 851
17 146
375 873 398 937 416 366 429 340
115
Percentage of GERD performed by the private
non-profit sector. 1995-2004
Australia
Austria
Belgium
Canada
Czech Republic
Denmark
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Italy
Japan
South Korea
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States
EU-25
Total OECD
1995
..
..
1.4
0.7
..
1.1
0.6
1.3
..
0.7
..
3.2
0.8
..
4.4
1.1
..
0.4
1.0
..
..
..
15.0
0.0
1.1
0.2
..
..
1.3
3.2
0.9
2.5
1999
..
..
1.2
0.4
0.5
1.1
0.7
1.5
..
0.3
..
2.2
..
..
4.6
2.1
..
3.1
0.9
..
..
0.1
10.8
0.0
1.0
0.1
..
..
1.4
3.3
0.9
2.6
2000
2.8
..
1.2
0.3
0.5
..
0.7
1.4
..
..
..
1.9
..
..
4.6
1.4
..
0.3
1.0
..
..
0.1
10.8
0.0
0.9
..
1.9
..
1.8
3.5
0.9
2.7
2001
..
..
1.2
0.2
0.5
0.7
0.6
1.4
..
0.4
..
2.3
..
..
2.3
1.0
..
0.2
0.8
..
..
0.2
10.8
0.0
0.8
0.1
..
..
2.3
3.9
1.0
2.5
2002
2.8
2.4
1.2
0.2
03
0.6
0.6
1.4
..
..
..
2.2
..
1.3
2.1
1.3
..
..
0.7
..
..
0.3
11.2
0.0
0.2
..
..
..
2.7
4.2
1.1
2.6
Source: OECD. Main Science and Technology Indicators. November 2006.
2003
..
..
1.2
0.3
0.4
0.7
0.6
1.3
..
1.0
..
2.1
..
..
2.1
1.2
..
..
..
..
..
0.2
11.5
0.0
0.2
0.4
..
..
3.2
4.1
1.2
2.6
2004
..
..
..
0.3
0.4
..
..
1.3
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
0.2
..
..
..
..
..
4.1
..
..
Wo rki ng Paper 6
Statistical Annex
Data sheet 8
The Future of Key Research Actors in the European Research Area
Public and private expenditure on education
as % of GDP 2001
116
Belgium
Czech Republic
Denmark
Germany
Estonia
Greece
Spain
France
Ireland
Italy
Cyprus
Latvia
Lithuania
Luxembourg
Hungary
Malta
Netherlands
Austria
Poland
Portugal
Slovenia
Slovakia
Finland
Sweden
UK
EU-25(3)
US
Japan
Tertiary education
All levels of education
Public
Private
Public
Private
expenditure expenditure expenditure expenditure
1.36
0.21
6.11
0.44
0.80
0.13
4.16
0.41
2.73
0.04
8.50
0.28
1.12
0.09
4.57
0.98
1.07
..
5.48
..
1.19
0.00
3.90
0.23
1.01
0.30
4.41
0.59
1.02
0.16
5.76
0.48
1.24
0.20
4.35
0.35
0.81
0.20
4.98
0.32
1.21
0.79
6.28
1.31
0.90
0.54
5.75
0.70
1.34
..
5.92
..
..
..
3.84
0.001
1.11
0.26
5.15
0.57
0.88
0.02
4.47
0.85
1.32
0.28
4.99
0.45
1.35
0.06
5.70
0.32
1.07
..
5.56
..
1.09
0.09
5.91
0.09
1.33
0.45
6.13
0.85
0.83
0.05
4.03
0.12
2.05
0.06
6.24
0.13
2.05
0.20
7.31
0.21
0.81
0.30
4.69
0.81
1.08
0.20
5.10
0.60
1.48
1.77
5.08
2.22
0.54
0.61
3.57
1.17
Source: DG Research – Key Figures 2005
Data: Eurostat. OECD
Notes: (1) The values for EU-25 are estimations.
Figure 4
Public and private expenditure on education
1995-2003
Public expenditure on educational institutions
Private expenditure on educational institutions
Australia
Austria
Canada
Denmark
France
Germany
Index of change (1995=100)
Figure 3
Hungary
Ireland
Italy
Japan
Mexico
Netherlands
Portugal
Slovak Rep.
Spain
Turkey
UK
United States
0
50
100
150
200
250
Source: OECD
Data sheet 10
Percentage of HERD financed by industry
1995-2004
Australia
Austria
Belgium
Canada
Czech Republic
Denmark
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Italy
Japan
South Korea
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States
EU-25
Total OECD
1995
4.7
..
13.1
8.0
2.0
1.8
5.7
3.3
8.2
5.6
2.1
5.4
6.9
4.7
2.4
22.4
..
1.4
4.0
9.4
5.3
11.4
0.9
1.0
8.3
4.6
..
13.1
6.3
6.8
5.9
6.2
1999
..
..
10.5
9.1
1.3
2.1
4.7
3.4
11.3
5.0
6.1
4.0
5.9
..
2.3
10.8
..
7.8
5.1
5.8
5.1
9.8
1.2
0.9
7.7
3.9
..
18.5
7.3
7.4
6.6
6.5
2000
4.9
..
11.8
9.5
1.1
2.0
5.6
2.7
11.6
..
5.5
..
5.3
..
2.5
15.9
..
2.0
7.0
..
..
7.8
1.0
0.9
6.9
..
5.1
19.4
7.1
7.1
6.5
6.6
2001
..
..
12.7
9.4
0.7
3.0
6.7
3.1
12.2
6.8
4.4
10.9
4.4
..
2.3
14.3
..
1.1
7.1
5.3
5.8
6.3
0.8
0.9
8.7
5.5
..
21.1
6.2
6.5
5.7
6.4
2002
5.1
4.1
..
8.7
0.9
4.2
6.2
2.9
11.8
..
11.8
..
3.7
..
2.6
13.9
..
..
6.7
..
..
5.8
1.2
0.0
7.6
..
6.0
22.0
5.8
5.8
6.6
6.2
Source: OECD. Main Science and Technology Indicators. November 2005.
2003
..
..
..
8.7
1.0
2.7
5.8
2.7
12.6
7.5
10.6
9.5
3.0
..
2.7
13.9
..
..
..
3.6
5.0
6.0
1.5
0.0
6.4
5.5
..
..
5.6
5.3
6.5
6.1
2004
..
..
..
8.7
0.6
..
..
..
12.8
..
12.9
..
2.6
..
..
..
..
..
..
..
..
..
..
0.6
..
..
..
..
..
5.0
..
..
Figure 5
Figure 6
Finland
Australia
US
Switzerland
Poland
Austria
Latvia
Belgium
Estonia
United Kingdom
Slovenia
Germany
Sweden
France
Greece
New Zealand
Lithuania
Sweden
Ireland
Denmark
Spain
Ireland
Belgium
Norway
Denmark
Iceland
France
United States
EU-25
Netherlands
Portugal
Czech Republic
EU-15
Hungary
UK
Spain
Bulgaria
Finland
Austria
Japan
Hungary
Greece
Netherlands
Italy
Japan
Slovak Republic
Italy
Turkey
Germany
Chile
Slovakia
Russian Federation
Czech Republic
Poland
Malta
South Korea
Romania
Mexico
Foreign students as a percentage of all
students 2002
117
0
Luxembourg
0
10
20
30
40
Source: DG-Research
Data: UNESCO, Eurostat
Note: (1) DE: 1998/99
• Compared to the US, where almost 35% of the young population aged between 35 and 34
is enrolled in a tertiary program, the EU figures are ten percentage points lower. The US is
certainly benefiting from large shares of foreign, in particular Asian students.
• In Europe, Finland is having the highest share of its young population enrolled in university
education, the lowest share is recorded for Luxembourg (which does not have a full university
system), and Malta. While in Japan most students are already graduated by the age of 25,
Germany offers with its dual education system an alternative for university education.
2
4
6
8
10
12
14
16
18
W o r ki ng Paper 6
Statistical Annex
Enrolment of tertiary students as a share of
the young population (age 25-34) 2000/2001
The Future of Key Research Actors in the European Research Area
Data sheet 11
Foreign students by country/region of
citizenship 2001
Total
118
EU-15
US (1)
795 436
582 996
UK
225 722
Germany
France
199 132
147 402
Japan
63 637
CC-13 (2)
62 303
Spain
39 944
Belgium
38 150
Austria
31 682
Italy
29 228
Sweden
26 304
Netherlands
16 589
Denmark
12 586
Portugal
14 202
Hungary
11 242
Turkey
16 656
Romania
11 669
Norway
8 857
Ireland
8 207
Bulgaria
8 130
Latvia
7 917
Czech Rep.
7 750
Poland
6 659
Finland
6 288
Cyprus
2 472
Slovakia
1 690
Slovenia
864
Estonia
605
Iceland
Malta
421
340
Top Ten:
country or region of citizenship 2001
EL, FR, DE, IT, ES, PL, IE, UK, AT, BG
India, China, Korea, JP, Taiwan, Canada,
Mexico, TR, Indonesia, Thailand
Asia, EL, N. America, Africa, DE, FR, IE, US,
China, Malaysia
Asia, TR, Africa, PL, China, EL, IT, Russia, AT, FR
Africa, Morocco, Asia, Algeria, Niger, DE,
N. America, Somalia, S. America, ES
Asia, China, Korea, Europe, Malaysia,
N. America, Indonesia, Thailand, US,
S. America
EL, CY, SK, Macedonia, Albania, BG, LT, DE,
CZ, UK
S. America, IT, FR, DE, Africa, Morocco,
N. America, UK, PT, Colombia
Africa, FR, Morocco, IT, NL, Asia, D.R.Congo,
LU, ES, Cameroon
IT, DE, Asia, BG, TR, HU, Yugoslavia, SK, Africa,
PL
EL, Asia, Albania, Africa, S. America, Croatia,
DE, Cameroon, CH, San Marino
FI, Asia, DE, N. America, NO, FR, US, PL, DK,
UK
Asia, DE, Africa, Morocco, BE, S. America, TR,
ES, Surinam, UK
NO, Asia, IS, SE, DE, Bosnia & Herzegovina,
UK, Africa, N. America, US
Africa, Angola, Cap Verde, S. America, Brazil,
FR, Mozambique, Venezuela, N. America, ES
RO, SK, Asia, Yugoslavia, Ukraine, IL, DE, NO,
EL, N. America
Asia, CY, Azerbaijan, Turkmenistan, EL,
Kazakhstan, Russia, Kyrgyzstan, BG, Albania
Moldavia, EL, Asia, Ukraine, Africa, Albania,
Yugoslavia, Morocco, BG
Asia, SE, DK, Africa, Bosnia & Herzegovina, DE,
N. America, UK, Russia, US
N. America, UK, US, Asia, Malaysia, FR, DE,
Africa, ES, Canada
EL, FYR Macedonia, Asia, TR, Ukraine,
Moldova, CY, India, Yugoslavia, Africa
Asia, IL, LT, Russia, Sri Lanka, EE, Lebanon,
Pakistan, DE, N. America
SK, Asia, EL, UK, Africa, Russia, Ukraine, N. &
S. America, PL
Ukraine, Asia, BY, LT, N. America, Kazakhstan,
NO, US, Africa, Russia
Asia, China, Russia, Africa, SE, EE, N. America,
DE, US, UK
Asia, China, Bangladesh, EL, RU, Pakistan,
India, Africa, BG, Yugoslavia
Asia, CZ, EL, Yugoslavia, Africa, Ukraine, IL,
RO, UA Emirates, Kuwait
Croatia, Bosnia & Herzegovina, IT, Yugoslavia,
Macedonia, DE, Ukraine, S. America, Asia, AT
LT, LV, FI, Russia, Asia, N. America, SE, Canada,
DE, BE
DK, DE, NO, N. America, SE, FI, Asia, FR, US, IT
Asia, Russia, Africa, Yugoslavia, BG, Albania,
China, NO, Libya, Palestine
Source: DG Research – Key Figures 2003-2004
Data: Eurostat, NewCronos database; US: IIE (www.opendoors.iienetwork.org)
Notes:
Students at tertiary level (ISCED 5/6).
(1) US: Country of origin 2001/2002. No world regional grouping provided.
(2) Data for CC-13 refer to 2000.
Data sheet 12
Firm plans of foreign recipients of United
States science and engineering (S&E)
doctorates to stay in the United States by
place of origin
Place of origin
All non-US citizens
Europe
Greece
UK
Germany
Italy
France
Spain
Other
East / South Asia
Pacifica / Australasia
North / South America
Africa
Firm plans to stay
% share of foreign S&E doctorate recipients(1)
1990–1993
1994–1997
1998–2001
40.9
43.3
54.1
44.5
47.9
57.5
45.8
40.8
56.5
57.7
59.5
62.4
43.0
44.6
52.4
36.5
31.9
49.8
29.4
32.0
48.4
38.5
45.7
40.8
45.4
53.0
61.1
44.1
46.2
58.5
33.1
28.7
43.1
36.0
36.1
42.4
24.5
25.8
40.7
Source:DG Research – Key Figures 2005
Data: NSF
Notes:
(1) Data include foreign doctoral recipients who are either permanent or temporary residents.
Recipients with firm plans to stay have a post-doctoral research appointment or academic,
industrial or other firm employment in the United States.
7
W o r k in g
Paper
The future of RTOs:
a few likely scenarios
Jos Leijten, Head of Innovation Policy group, TNO
1. Introduction
This chapter introduces a specific and important set of
actors – Research and Technology Organisations (RTOs)
in national innovation systems. It describes briefly where
they come from, what their ‘raison d’être’ was, and how
they have changed over time.
fully privately owned for-profit contract research
organisations (CROs). For the purpose of this paper
these commercial CROs do not belong to the category
of RTOs. Even though their activities and roles in
the innovation system may be very similar, the
governance structure of such companies and hence
the driving forces for change are very different.
If we take this as a starting point the following
criteria appear to be useful to categorise RTOs:
1.The main activity of an RTO is to provide
research
and
development,
technology
and innovation services to firms and other
clients. Usually this is also laid down in the
mission statement of the RTO or in a law that
governs the existence of the RTO (which is
the case for TNO, RISOE, and many others).
There are at least two ‘grey areas’ in this
criterion:
a. The first is in the wording ‘R&D, technology and
innovation’. In particular the use of the word
‘innovation’ here refers to activities which are
rapidly changing nowadays. Innovation is also
concerned with organisational structures and
social processes, with creativity, design and
marketing, and even with systemic changes
on a macro level. This changes the classical
picture of an RTO as a place where people
work on R&D for applying ‘hard technology’.
Their work usually includes technology
transfer and sometimes also implementation
related activities for their clients. Some
RTOs even have activities which are quite
far removed from the field of technology,
like labour market studies in TNO, FhG and
Joanneum Research, health care systems
performance research in TNO, or management
support in SINTEF and VTT (see page 122);
b. The second grey area is in the use of the
words ‘services for firms and other clients’.
The difference between fundamental and
applied research is becoming less apparent
1.1 What are RTOs?
Most countries and regions have Research and
Technology Organisations located within their
borders. There is an enormously wide variation in
organisational and legal structures, ownership,
funding structures, activities, size, etc. This makes it
very hard to give a clear definition. But it is possible
to distinguish a number of common characteristics
of RTOs and to exclude sets of organisations that
superficially may look similar but differ on certain
key characteristics which cause their strategic
actions and futures to be driven by completely
different factors as compared to RTOs.
The European Association of RTOs (EARTO) states
that its membership is generally open to all
organisations which as their predominant activity
provide research and development, technology and
innovation services to firms or other clients and
which are managerially independent. Based on this
definition the EARTO membership also includes
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The future of RTOs: a few likely scenarios
K
nowledge is the only product which has a
tendency to grow by sharing it. Sharing was
a relatively well structured process as long as
knowledge production and the use of knowledge
was the job of a select group of specialists. But
nowadays knowledge production and usage are
becoming ubiquitous, global, and involve major parts
of the population in their roles as entrepreneurs,
employees, consumers and citizens. This changes
the processes and structures for production, sharing
and use of knowledge. How to deal with these
changes is at the heart of the challenges all actors
in the European Research Area now face. This paper
addresses the implications for the future of RTOs.
The Future of Key Research Actors in the European Research Area
and institutions once established for
independent fundamental research (e.g. CSIC,
Max Planck, CNRS, FOM) now slowly start to
collaborate with firms just as applied research
organisations do. With a view on the dynamics
taking place now, I propose to include such
organisations in our RTO category, even if
their share of contract research is limited or
even zero1.
120
2.RTOs are usually public not-for-profit
organisations. This does not necessarily
mean that all RTOs are deliberately created
by governments. With or without the help of
government some RTOs also have been created by
groups of companies or branch organisations to
serve a common interest. Here we also face ‘grey
boundaries’ and quite strong dynamics with regard
to the characterisation of RTOs as ‘public’ and in
the characterisation as ‘not-for-profit’. In many
countries the governance of science, technology
and innovation is in constant flux. Within the
boundaries of the mission orientation a lot of
changes are taking place in the status of RTOs.
Usually these changes are intended to increase
the flexibility of the RTOs to adapt to market
needs. So former government departments have
become independent public agencies or even
independent (public) companies. In particular
in the UK this process was even taken one step
further by fully privatising former public R&Dfacilities. But the reverse also happens: debates
about greater independence of RISOE in Denmark
or VITO in Flanders led to a re-confirmation of
their close linkages with the government. A
special case occurred in the Netherlands, when
telecom operator KPN wanted to close down
its research facilities in 2001. In the monopoly
days of telecommunications these research
facilities were fully public. With the privatisation
they eventually became part of a fully private
company. However, the loss of a public body of
knowledge which had only been private for 10
years or so was seen as undesirable. Eventually
KPN, the Dutch government and TNO agreed on a
take-over of KPN’s research laboratory by TNO.
3.RTOs are managerially independent. Usually
the management of RTOs are free to decide
on the best ways in which they can fulfil
their mission. This criterion excludes few
organisations, because nowadays most
1.Very often these organisations are not allowed to engage in contract
research or for tax reasons (they run the risk of losing tax-exemption status)
refrain from contract research. Sometimes this problem is solved in the
same way many universities do, through the establishment of a subsidiary
for contract research.
research organisations will have a certain
level of managerial independence, even those
fully owned and funded by the government.
Again I propose to look at the mission as the
distinguishing feature. I would like to exclude
organisations from the RTO category if their
sole mission is to support development and
implementation of policy in a one-on-one
relationship with a particular government
or government department. In such cases
dependencies are so strong that it would be
presumptuous to speak about managerial
independence. Examples are the Dutch National
Institute for Public Health and Environment
and the Joint Research Centres of the European
Union. The earlier mentioned examples of
RISOE and VITO are slowly moving away from
the one-on-one relationship by incorporating
other goals/clients in their mission.
4.Closely related to the criterion of managerial
independence is the criterion of funding.
Most RTOs have a mixed funding structure in
which longer term funding from governments
(both grants as well as ‘competitive funding’)
is combined with funding from contracts in
which a client directly pays for a specified
service or product. On top of this it is not
uncommon for RTOs to gain an income from
intellectual properties (patents, licences) or
from participations in spin-offs and start-ups. I
have the impression that this latter category is
becoming more important recently. But maybe
the combination of all of these different sources
of funding and income is – next to a public
mission orientation - the best differentiating
criterion for RTOs. Funding figures are difficult
to compare because of differences in calculated
costs and differences in the labelling of funding
sources. Therefore we present two pictures
that together represent an image of the funding
structure of a ‘standard RTO’.
Table 1
Funding structure of a number of RTOs
Core funding/grant (%) Contract research (%)
CSIRO
66
34
Fraunhofer
40
60
Joanneum research
25
75
SINTEF
7
93
TNO
34
66
VTT
30
70
IMEC
24
76
DPI
50
50 (25)
Source: TNO 2005, limited comparability because of differences in calculated costs and
labelling of funding categories.
Figure 1
Development of funding sources of the FhG
Basic funds
Contract financing (industry)
Public financing (among others, federal and state, EU)
350
1.2 The origin of RTOs (some examples)
million
250
200
150
100
50
77 79 81 83 85 87 89 91 93 95 97 99 01 03
priliminary
Source: Warnecke, 2002 EARTO conference, Graz
The distribution of funding presented above
is typical for the RTOs with a strong applied
technology orientation, and is sometimes even
seen as a target. But as stated before also
public research organisations which started
as fully publicly funded fundamental research
organisations are now broadening their funding
base by engaging in strategic research programs
(such as the EU framework programme) and
contract research. In the case of the Max Planck
Society these additional funding sources are now
close to 20 per cent of the budget, even though
none of this is formally labelled as contract
research.
5.Apart from a limited focus on industrial
technologies the scope of activities in terms of
knowledge areas, client groups, or geographical
coverage does not seem to be a very important
issue in the definition of RTOs. Even though
there are several regionally operating RTOs, like
Joanneum Research in Austria (the province of
Styria), and that in many cases national and/or
public issues and clients dominate the operations,
geographical area limitations are disappearing
very rapidly. Most RTOs now focus on developing
their competences, which in principle can
be traded world wide. The same happens to
inherited boundaries with regard to scientific or
technological disciplines and application areas
and/or sector coverage. The competences are
traded where they are needed. Newer technology
trends such as the pervasive role of ICT in many
applications, the advent of other pervasive
enabling technologies like nanotechnologies and
biotechnology and the generally perceived trend
towards convergence of technologies makes it
Many RTOs were established with the explicit mission
‘to provide research and development, technology
and innovation services to firms and other clients,
in order to support their competitiveness and
sustainability and thus contributing to economic
growth’. Many other organisations which started
out in fundamental research or direct policy support
(government laboratories) have developed a similar
profile either as a result of deliberate policy, or as a
reaction to reduced basic funding, or on the basis of
their own and internal dynamics. But many countries
still have a relatively strong, although increasingly
complicated, division of research labour between
applied (industrial) technology organisations and
fundamental research organisations. Often the
organisations were established at the same time as
part of the same policy package (e.g. TNO and NWO
in the Netherlands, the Fraunhofer Gesellschaft and
the Max Planck Society in Germany).
TNO can serve as a typical example of the group of
applied research organisations. TNO was founded
(TNO Act, 1930) by the Dutch government to support
the industrial development of the Netherlands
with applied research and technical support.
Strengthening the economy by means of innovation
based on R&D was in those days also seen as a
political priority. The feeling was that the Dutch
academic research was of relatively good quality,
but that the implementation of research results was
lagging behind.
Over time the scope of the organisation was broadened
to include not only industrial research but also defence
research, food research and health research. Each of
these fields was governed by a separate and relatively
autonomous research organisation. These four
organisations together shaped TNO, as a rather loose
federation under a central administrative umbrella.
Near the end of the 1970s the need was felt to bring
these research fields under a single strategic and
operational management. In 1980 the four research
organisations and the central organisation were
brought together in one new organisation, TNO, under
a single Board of Management appointed by the Dutch
government. This model was laid down in a revised
TNO Act (1985) which – with minor revisions of which
the latest took place in 2005 – still serves as the legal
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The future of RTOs: a few likely scenarios
300
0
increasingly difficult for small, highly focused
organisations to survive. There is a pressure to
grow in size or, alternatively, to be able to cope
with increasing technological complexity through
strong networking.
The Future of Key Research Actors in the European Research Area
framework for TNO. The Act (Art. 4) states the TNO
goal: ‘to serve public interest and the specific interests
of society through the effective contribution of applied
technical and scientific research and related social
scientific and other applied research’. The Act (Art. 5)
states that TNO undertakes the following activities to
attain this goal:
• Applied research, initiated
commissioned by customers;
by
TNO
or
• Making research results accessible and
transferring these to users by giving; information
and advice and by supporting user activities
aimed at practical applications;
• Co-operation in the field of applied research with
other research organisations;
• Contributing to the co-ordination of applied
research in the Netherlands and to international
co-operation in applied research;
• Activities assigned by law or ‘order in council’.
122
SINTEF enjoyed its most rapid phase of growth in the
1970s due to the growing demand for technology in
the young Norwegian petroleum industry. Important
laboratories such as the Ocean Basin Laboratory and
the Multiphase Laboratory began operating during
this period. Today, the Ocean Basin Laboratory is
part of MARINTEK. The Multiphase Laboratory is
part of SINTEF Petroleum Research.
VTT in Finland was founded about 10 years later. The
history of VTT began on 16 January 1942, when the
president signed the Act on the Technical Research
Centre of Finland. VTT then operated directly under
the auspices of the Ministry of Trade and Industry.
Its mission was ‘to engage in technical research for
the benefit of science and society’. VTT also had to
test materials and structures at the request of the
authorities, private citizens, companies and other
organisations. In addition it had the right to engage
in commercial research work.
The Fraunhofer Gesellschaft was founded in 1949, in
the same year as the Federal Republic of Germany,
and started out as a small office with just three
employees. The original purpose of the non-profit
organisation was to distribute grants and donations
for research directly relevant to industry. But FhG
rapidly developed and grew to become the largest
RTO in Europe.
The SINTEF Group was founded in the mid-1980s
when the Ship Research Institute of Norway, the
Norwegian Research Institute of Electricity Supply
and the Continental Shelf Institute were drawn
under the SINTEF umbrella. These institutes were
transformed into research companies with SINTEF
being the central shareholder. The fourth research
company, SINTEF Fishery and Aquaculture, was
established in 1999.
Today the SINTEF Group consists of six research
divisions: SINTEF Health Research, SINTEF ICT,
SINTEF Marine, SINTEF Materials and Chemistry,
SINTEF Petroleum and Energy and SINTEF Technology
and Society.
The regionally-based Joanneum Research in Austria
originated in the 1950s when the Graz universities
needed expensive mainframe computer capacity,
atomic research facilities and electron microscopes.
This need could not be fulfilled nationally and so the
regional government of Styria stepped in, under the
condition that the investments were made in legal
entities separate from the universities. These legal
entities became Joanneum Research in 1984, with a
much broader list of research areas than the one on
which the initial groups were based. For reasons of
strengthening its sustainability, Joanneum Research
sought international collaboration and in 2004 TNO
took a 10 per cent share in Joanneum Research
(the other 90 per cent belongs to the Styrian
government).
1.3 A short RTO history
• to encourage technological and other types of
industrially oriented research at the Institute;
The broad development of RTOs follows the major
economic trends or waves, the trends in science and
technology and – at a later stage – trends in innovation
policy. TNO is one of the oldest RTOs in Europe. It
was established after the 1929 stock market crisis
to support industrial sectors (discussions about the
need for support had already started long before
the crisis because the Netherlands lagged behind in
industrialisation).
• to meet the need for research and development
in the public and private sectors.
Against this background TNO started as a rather
loose collection of institutes each covering the
SINTEF was established in 1950 by the Norwegian
Institute of Technology (NTH), which now forms
part of the Norwegian University of Science and
Technology (NTNU). It had two aims:
Many RTOs were established after the Second
World War. This was the period (roughly 19501970) of ‘big science’ (nuclear research, mainframe
computing, large chemical laboratories and test
facilities, etc.) and of generic support for scientific
and technological research. RTOs were (re-)shaped
to fit this picture.
Next came a period (roughly 1970-1985) of research
driven by public issues: environmental research,
human factors research, public health, and research
for industries of national strategic importance.
This was also the period in which science policy,
technology policy and innovation policy came on the
national policy agendas.
The period from 1985-2000 can best be characterised
as the period of differentiation. The general trend
was that of a reduction of basic government funding
and a growth of contract research, which many RTOs
tried to cover by broadening their range of client
driven activities.
For the sake of convenience we take 2000 as the
start of another period in which new RTO strategies
emerge. The dynamics that govern the position and
behaviour of RTOs in this period and its possible
consequences are the focus of this paper.
Despite the fact that most RTOs have experienced
many changes over the years, it is – for the context
of this paper – good to recall that some of the basics
have not changed. Even though the amount of
funding from international sources (mainly industry
clients and the EU framework programme) has grown
quite sharply in recent years, RTOs are basically still
national organisations, subject to national policies
and governed by national bodies. The 10 per cent
share of TNO in Joanneum is an exception to this
rule. To serve their growing international client base,
several RTOs have established foreign offices (e.g.
SINTEF in Houston, the heart of the US oil industry
and TNO in Detroit, heart of the US car industry).
Only in the case of the fully privatised RTOs, such
as the former UK defence research labs now called
Qinetiq, has internationalisation been taken a step
further. Qinetiq is partly owned by a US-based
investment company and the British government
considers a further sale of shares.
What has also been rather consistent over the years
is the position of RTOs vis-à-vis universities and
the fully commercial research organisations and
engineering consultants. Almost inevitably there
have been many overlaps and cases of competition
for the same funding sources or contracts. But by
and large RTOs have stayed away from teaching and
their research has mostly been mission-oriented,
strategic or client-driven and not curiosity-driven, as
was the case in universities, or fully commerciallydriven, as was the case in the private sector.
2. (Re-)shaping RTO roles
in progress
This chapter gives an overview and analysis of the
important forces that are now shaping RTOs. It
discusses how these forces may change in direction
or magnitude over the next ten years or so, and
which new forces may arise.
2.1 Open innovation
The most pervasive factor of all is the development of
networked innovation systems and networked R&D.
Companies and research organisations increasingly
have to focus on certain core competencies or
core products. They can only do so by engaging
in extensive networking with other players in the
innovation system. The R&D actors have to take
account of the fact that they are embedded in
increasingly diffuse and distributed innovation
processes. The keyword today is open innovation.
Table 2
Open vs. closed innovation principles
Old ‘closed’ innovation
We have the most talented people.
We discover, develop and market
ourselves.
To be first to market means
winning.
Create most and best ideas means
winning.
Control IP to control entrance of
competitors.
New ‘open’ innovation
Many talented people outside.
Internal R&D cannot cover all
needs.
External R&D also creates value.
To achieve market growth means
winning (also if it has to be
shared).
Profit is in combining internal
and external processes in a good
business model.
Sharing IP is becoming the rule.
Under the rules of open innovation, outsourcing of
R&D by companies in collaborative programs and
projects is growing. In many cases this goes hand in
hand with a shift of R&D funding from the private to
the public sector or with the growth of mixed publicprivate funding models. But there are no general
rules; the outcomes may differ over time, from
country to country, from sector to sector and from
technology area to technology area.
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The future of RTOs: a few likely scenarios
broad range of topics necessary for supporting an
industrial sector.
The Future of Key Research Actors in the European Research Area
The characteristics of different technology areas (e.g.
compare development of IT systems for enterprise
resource planning with stem cell research) or
different markets (e.g. compare chemicals where
capital investment seems to be the dominant factor
with pharma where IP protection dominates) make it
increasingly difficult to think in terms of fixed roles for
the players in the innovation systems. The division of
labour between players may differ from case to case.
124
One of the most influential factors behind the different
outcomes is probably the nature of markets. In ICT,
and other technology areas in which externalities play
a major role, there is a tendency towards ‘winner takes
all’ mechanisms. It is widely accepted that the ‘winner
takes all’ rule will become increasingly important with
the advent of the networked knowledge economy.
This leads to strong contradictory forces. On the one
hand there is an increasing need for many players to
join forces to realise the increasingly complex and
costly innovations of new products, services and
systems. And on the other hand the rewards of being
the first and only one to introduce an innovation can
be very high. Given their public mission orientation on
innovation, most RTOs will most likely choose the first
option of becoming a networking organisation (with
relaxed IP-rules, etc.). But further privatisation and
specialisation in a unique technology base can also
be imagined, as well as a mixture of the two (most
RTOs are big enough for such dual strategies).
2.2 Globalisation
The ‘old’ models that point toward aligning R&D
activities with the needs of local/regional industries
and other actors are no longer tenable. Of course
it helps to have such strong linkages when they
are productive, but internationalisation and/
or globalisation of R&D are moving forward at a
rapid pace. The outcomes of the process are still
very difficult to predict. For most national or public
research institutes (less for academia) that are
subject to national priorities and governance this
leads to a problematic situation for which there is
no obvious solution other than to internationalise.
Internationalisation requires establishing global
excellence in certain areas. This may very well conflict
with traditional national (or regional in the case of
regional institutions) public-interest-led demands2.
2.In the case of TNO this situation even led to questions in parliament a
couple of years ago. The outcome was that TNO was allowed to use national
public funding for internationalisation of its activities. But in the present
discussion about strengthening demand-led publicly funded research
this decision may encounter some reconsideration. Until recently the
Fraunhofer Gesellschaft faced the same reluctance with regard to using
German tax-payers money for expansion abroad. The regionally based
governors of Joanneum Research from Austria took another approach and
‘sold’ 10 per cent of the shares to TNO in order to gain the independence to
internationalise.
This leads to contradictory forces working on RTOs:
on the one hand they will have to seek international
excellence, which can only be sustained by an
international market for their services, and on the
other hand they will have to serve local, regional or
national interests. The contradiction will be most
obvious where politicians take an opportunistic
short-term view and fail to understand the complex
nature of the linkages between internationalisation
and national/regional interests. But in the longer
run governments themselves will also seek the best
available knowledge and technologies for policy
support and bypass their own institutions if they do
not live up to the international standards.
If we follow the simple (but still to be confirmed)
hypothesis that production follows markets, and
that R&D follows production, it is clear that fast
growing markets (like China, India and Brazil) are
attractive. But they are also ‘easy’. Mature markets
like Europe, Japan and the US, and those not far
from being mature, such as South Korea, should
be attractive in other ways, e.g. through their
diversification, sophistication and highly demanding
character. This could open up a line of thinking in
which global excellence can be well accommodated
in the national or regional public interests (e.g. the
first country that succeeds in solving its mobility
problems has won global excellence).
For RTOs it means that some of their clients and
markets are relocating to benefit from the fastgrowing markets elsewhere. Simply trying to follow
this trend would not be a bad idea for first-mover
RTOs that take the opportunity to build strong
alliances with knowledge institutions and clients in
the fast growing markets. But in the long run this
could very well be counterproductive. They would
miss the opportunity to learn what the new demand
driven R&D needs and strategies will be in mature
markets and economies.
2.3 Changing location of the public
interest
Another angle to this story is the potential conflict in
the governance of RTOs between public interest tasks
and market orientation. The use availability of public
funding for public tasks could easily be interpreted
as a factor leading to potential disturbance of level
playing fields in the market. This is influenced by
two factors simultaneously.
On the one hand traditional linkages between
governments and RTOs are becoming weaker.
Governments are increasingly looking for the
‘best buy’ in procuring R&D services. So there
is a general tendency that governments find it
increasingly difficult to give clear directions,
priorities and guidance to their RTOs. On the
other hand, larger parts of society (RTO clients or
stakeholders) are becoming more independent
from government. In modern democracies many
public sectors like education, health care, transport,
energy, communications and welfare services are
gradually being liberalised. In the process the
privatised players in the fields of public interest
are also becoming the agenda-setting actors with
independent strategic powers.
politically be guided by already-experienced rather
than potential threats, and thus will lead to a short
term focus. A second danger is that a sudden flow of
extra government funding weakens the position of
the RTO in the marketplace in the longer term.
Public research organisations and governments in
Europe are now becoming aware of these changes.
The research organisations still have strong linkages
with government departments, but only for some
of their tasks and government still feels ownership
of the research organisation with regard to these
tasks. But increasingly the research organisations
are building stronger linkages with the independent
agencies and (public) companies that are now
responsible for the execution of the former
public tasks. They are the new users of research
outcomes.3
2.5 Growing managerial freedom
2.4 The fear factor
The emergence of the new global threat of
fundamentalist or nationalist extremism and
terrorism leads to growing concerns about both
preventing terrorist attacks and minimising the
impacts of such attacks on states, the economy
and society. Safety has been a traditional area of
attention for many RTOs, for instance in areas such
as industrial safety, environmental and chemical
hazards. Capturing this knowledge base is a reason
for many governments to seek support from RTOs in
the fight against terrorism. Many RTOs see this as a
positive development, because it gives them a new
undisputed reason to exist as a government-funded
institution. But there are potential distorting effects
which should be taken into account. One of the
dangers is that the programming of such work will
3.The fact that RTOs are large and not directly controllable organisations with
strong links to policy-making bodies which the new players were once part
of, very often leads them to choose to build their own research capabilities.
Several developments taken together, such as
an overall reduction in direct (basic) government
funding, changing ownership (more shareholders)
or legal positions (at ‘arms length’), lead to a
growing managerial independence of RTOs.
Most RTOs are now responsible for their own
strategic development, usually within fairly broad
boundaries set by their owner, main shareholder
or legal mission. This has generally led to a growth
of entrepreneurial behaviour in RTOs, such as:
expansion outside of the home country, take-over
of smaller RTOs and professionalisation of IPmanagement and spin-offs.
Among the larger public RTOs the case of the Dutch
TNO taking a 10 per cent share of the Austrian
Joanneum Research is still an exception. But for
more privatised RTOs like British Qinetiq, this form
of expansion is becoming very common. Further
restructuring on an international scale is almost
inevitable. How long it will take before a new
consolidated structure appears is however still very
much dependent on a further widening of managerial
freedom and on a further opening of national funding
rules. This will in turn lead to a change in the legal
status of RTOs to private sector status. A change in
the state-aid rules may be an important factor in the
speed of this process.
2.6 F ading boundaries:
technology convergence
It has been clear for some time already that ICT
applications play a major role in the development
of other areas of science and technology. Certain
applications such as mapping the human genome or
non-linear curves in new buildings and construction
would not, or only at great cost, have been possible
without advanced computing capabilities. But
we have now entered a period in which different
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The future of RTOs: a few likely scenarios
In general the role of governments as agenda-setting
agents is declining. Most likely the longer term
outcome will be that the existing difference between
public tasks and market-orientation disappears
(except in specific cases). This again puts into
question the very rationale for the existence of RTOs
as a separate function in innovation systems.
But the most difficult possible consequence for
RTOs to deal with will be caused by the fact that
research on safety and security tends to take place
in sheltered and protected environments. If RTOs
become strongly involved in this kind of work they
might face difficulties because other stakeholders
require openness and transparency of research.
The Future of Key Research Actors in the European Research Area
technology areas are not only mutually dependent
on each other but in which the actual combination
of technologies speeds up innovation processes
and introduces new applications. The public
discussion about the newly arising opportunities
and consequences of such technology blending, or
convergence as it is generally called, was greatly
stimulated by the 2002 NSF conference report on
NIBC convergence (nano, info, bio and cogno).
In 2003 the European Commission established
an expert group to study the consequences of
technology convergence for Europe. Developments
in the US seem to be largely driven by opportunityseeking entrepreneurship and a drive to improve or
enhance the ‘human being’. The Asian approach to
the convergence of technologies is very pragmatic:
‘technology blending’ is the term used to indicate the
process of seeking new product opportunities based
on convergent technologies. Europe in comparison
tends, for the time being, to take a rather ‘socially
embedded’ conceptual approach (e.g. ambient
intelligence).
126
There seems to be a growing common scientific
base for converging technologies: mathematical
modelling, complex systems theory, modelling
biological systems, growth of cognitive sciences,
etc. Given the fact that the ‘big science’ era has been
the growth period for many RTOs, many still have
expertise and interest vested in big technology. An
important factor for the RTO future and for the future
of converging technologies in Europe is the speed
at which the RTOs succeed in adapting their ‘old’
expertise to the new questions.
2.7 Fading boundaries:
fundamental and applied research
A particular but clearly related change in the research
process itself deserves separate attention. We are
referring to what is generally seen as the ‘end of the
linear model’ from fundamental science, via applied
science and product development to marketing.
Developments in the nature of scientific research
itself (nanotechnologies are a good example of a ‘let
us see if this works’ experimental model), competitive
pressures on the speed to deliver and the growing
need to involve application environments in the
process of technology development at the very least
compress the time-scale of the linear model and often
even lead to a direct mix-up of the different functions.
However, in many countries the knowledge
infrastructure is still neatly organised according
to the linear model. Academia and public research
institutes are concerned with fundamental science,
companies are responsible for developing products
and bringing them to the market, and in north-west
Europe in particular we have so-called ‘bridging
institutions’ (also called research and technology
organisations or RTOs) for applied research. They
generally target the transfer of the results of
fundamental research to companies with products
such as proof of concept, demonstrators and
prototypes.
But due to pressures on the linear model, today
universities and fundamental research institutes
very often move into the applied research area. The
reverse is also true. Both parties are also moving
into product development and bringing products to
market by creating spin-off companies.
The direct consequence of this change is that
the traditional linear model no longer describes
the role and positioning of bridging institutions
like TNO and other RTOs. All research institutes
– universities, RTOs and company labs alike – will
have to learn to cover the whole knowledge chain,
either alone or by establishing very strong and
effective partnerships. This process could be called
‘functional convergence’.
2.8 Fading boundaries:
users and producers
The basic question of many technology developers
is: what do we want the very flexible and versatile
enabling technologies to do? This question does
not come as a surprise. The trend toward masscustomisation, in which the potentials of ICT are used
to build flexible systems that ultimately can deliver
individualised products and services, was already
recognised many years ago. The growth of the Web
and e-commerce strongly favour and reinforce the
possibilities of individuals to choose and even build
their own preferential arrangements4, supported
by a drive toward one-on-one marketing. The
development of ICTs promises personal assistants
and agents full of adaptive learning programs that
are capable of adjusting themselves to the needs
and habits of their users. The somewhat longer
term is captured in visions such as ‘ubiquitous
computing and networking’, ‘intelligence enhanced
objects’5, and ‘ambient intelligence’6, which foresee
4.This may be read on many different levels: 1) the configuration of hardware
and software used (e.g. Apple, Wintel, Palm); 2) the personalised
configurations within the platforms (e.g. desktop or applications settings);
3) selectivity within certain application areas (e.g. setting of filters, use
of agents) and 4) usage (e.g. communication with friends, belonging to a
virtual community, making transactions).
5.e.g. as in the MIT Medialab ‘Things that think’ consortium.
6.ISTAG Scenarios for Ambient Intelligence in 2010, European Commission
Information Society DG 2001 (www.cordis.lu/ist/istag.htm).
These developments all point to the fact that ICTs
provide a growing and endlessly wide range of
technological and economic opportunities in which
the specific innovations or applications have to be
shaped by the users themselves. What this means
is that the users no longer only select and adapt
specific technologies for their own use, but in the
process also ‘invent’ and develop new information
technologies or at least new applications. This
process is now already very apparent in the
development of ICTs, but there are signs that this
may also be the case for biotechnologies and
materials or nanotechnologies in the near future,
provided that tools for easy and cheap manipulation
of the basic building blocks become available for a
wider public. Some people think that this can never
happen in the life-sciences, but that is precisely what
most experts thought about computer technologies
until the late 1980s. And of course, the information
technologies themselves will help greatly in building
and mastering cheap tools in other technology areas.
This is well captured in the concept of ‘personal
manufacturing’ (Gershenfield), which foresees a
future in which the user has the tools to produce
many things they use at home with the aid of a
personal, versatile manufacturing device.
This may sound like science fiction, but for many
large companies – mostly still in the ICT-based
sectors – it is a day-to-day reality. The number and
range of choices they have to make about what and
how to produce and deliver new products and/or
services has grown enormously. And their clients are
pushing hard for even more possibilities. The main
problem of the companies is no longer to invent,
develop and market new products or services. Their
main problem is to choose or to select what to make
– or let their customers make this choice.
The technological basis for this is a continuation
of the pervasive ICT-developments of today
(increasing memory, processing, storage, and
transmission capacities and increasing software
capabilities), combined with further technological
convergence e.g. based on wireless networking
and Next Generation Internet technologies. These
technologies all contribute to the dominance
of distributed networking as the paradigm for
ICT developments. There is a general trend that
‘intelligence’ (processing power) grows much faster
at the edges of networks – in the devices attached
to the network or used to access networks – than
in the network centres. It is only 20 years ago that
PCs changed the centrally controlled ‘master-slave
model’ of mainframe computing into a ‘client-server
model’. The development of the Internet contributed
a lot to the weakening of central control. The next big
change was ‘peer-to-peer networking’ (e.g. Napster,
Kazaa, etc.). In software there is a trend toward
easily accessible, open and modular systems. It
seems that these developments all systematically
aim at putting more power (including the controls) in
the hands of the users.
The possibilities do not stop at the boundaries
of information technologies. Advanced computer
technologies used as ‘tools for thought’ increase
the speed of development in many other areas
of science and technology. More and more, the
combination of ICT with, for example, new materials,
biological processes and new energy technologies
starts to inspire visions of future developments. In
a couple of years these technologies may become
as generic, flexible and versatile as ICT already is
today. If that is the case, the number and range of
technological options will increase manifold. And
for some it already appears as if ‘the technology is
ready to do anything or be anything we want it to
be’ (Kurzweil).
During the process the functional dividing line
between producers and users becomes thinner and
thinner. For RTOs or for any research organisation
how this will change their R&D processes and the
competences needed is a very exiting question.
Certainly it changes the client: in the future this is
most likely not an individual company anymore,
but a network of companies of a very diverse nature
working together to set a standard, to be able to cover
the service chain linked to any product and probably
including also users or user-representatives. This
presents an enormous challenge for RTOs, because
they would need to drastically change some of the
processes on which their existence is based, like
‘contract research’ and ‘basic funding’.
2.9 Fading boundaries:
science, technology and socioeconomic analysis
All research organisations have to take into account
that due to various reasons the research process
itself is changing. Some of these reasons are:
• The size of investments in new technology
development make it increasingly risky for
companies and thus for research organisations
to make such choices in isolation. Risk aversion
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an information environment which is so adaptive to
our needs and preferences that we will hardly notice
the technological basis of its existence.
The Future of Key Research Actors in the European Research Area
strategies, usually leading to conservative
behaviour, could very well also lead to openness
and collaboration;
• The development of technologies for new service
applications inevitably is a process that involves
many different actors. Such processes are
even very often driven by the end-users.7 Many
examples of this can be found in ICT, and the
same models are now also entering into the field
of life sciences;
• In the so-called knowledge economies and in
societies with high education levels, knowledge
and scientific thinking are increasingly socialised.
Making innovations really work in social and
entrepreneurial environments and at home
requires many different skills. The growing
complexity has led to the growth of ‘mode 2
knowledge organisations’ and in particular the
growth of a vast sector of ‘knowledge intensive
business services’ as necessary parts of
innovation systems;8
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• And finally, the new pervasive technologies of ICT,
biotechnology, nanotechnology, etc. very often
touch upon the fundamentals of interactions
between people, their health and well-being and
on the properties of things. At some point in the
process people want to know and understand
how these fundamentals are changing.
At the macro level these factors lead to a need to
increase the transparency of research and technology
development through increased interaction with the
public. Social factors and economic impacts need to
be taken into account even in the very early stages
of the research process. Nanotechnology research
programmes around the world are now almost
everywhere complemented by a social sciences
research programme studying social, economic,
cultural and ethical factors in relation to technology
development. In relation to this development there
are now good reasons to bring research centres
closer to the people, instead of ‘hiding’ them in
secluded and secured ‘ivory tower’ places.9
At the company level the same kind of trends can
be seen. The stage of simply developing products
and bringing them to the market is long gone. To
bring an innovation to the market in the networked
7.Theoretical ground for this (although contested) can be found in Richard
Barras’ ‘reverse product cycle theory’ and in Carlota Perez’s recent work on
financial sector innovations.
8.See Gibbons and others on ‘The new production of knowledge’.
9.See also Nowotny and others (2001) on ‘Re-Thinking Science’ and the
Demos (2004) report ‘See-through science’.
environments of today requires extensive study
into potential business models, of the way the
product may change customers’ behaviour, and
of the way to implement the services associated
with the product. It leads to a closer collaboration
between technology, production, marketing and
strategy divisions in companies. In some cases the
organisational differences between disciplines seem
to disappear entirely in something which is broadly
called ‘systems engineering’.
In general, RTOs are seen as well equipped for this
development. Much more so than universities,
they are capable of organising themselves along
multidisciplinary lines which is necessary to
produce integrated outcomes. But it also means
that they have to drastically change the traditional
way of working in which the technology experts
of the RTO dealt with the technology experts of
the client. The complexity of the world of their
clients directly translates in an increased internal
complexity of RTOs.
This change comes after a period in which most
European RTOs have been confronted with pressure
from their owners (governments) to work closer
with the market and produce results which can
immediately be applied to respond to the demands
of clients. It could be argued that this so-called
‘instrumental thinking’ (e.g. TNO, SINTEF and VTT)
has led in some cases to an erosion of the deeper
and often quite unique knowledge base of the
organisation in favour of short-term contracts and
results. Awareness of this process has grown and
now the threat of not being able to distinguish the
RTO from consultants or engineering companies is
recognised in many strategy discussions. In the US
this change could be avoided to a certain extent
because of the stronger ‘scientific entrepreneurship’.
In most Asian countries the notion of contract
research and contract research organisations is
much less present; the model of collaborative
research is instead much stronger.
2.10 F ading boundaries:
institutional convergence
Despite all the differences mentioned, the overall
pattern of development in relation to fading
boundaries is one which could be called ‘institutional
convergence’. It means that the actors in R&D are
becoming more similar or, to be more precise, there
is one single actor space developing in which they all
operate. They all need to cover the whole knowledge
chain, from fundamental research to marketing to
technology. The precisely middle ground of bridging
For individual companies with a sizable R&D
capacity it becomes increasingly difficult to exploit
all the research potentials within the boundaries
of the company. The efforts of realising all external
networking needed to exploit only one technology
may be so big that the overall ‘take-up capacity’
of the company for new technologies decreases.
Some opportunities need to be ‘externalised’ to
be successfully developed into applications. This
makes company research labs very similar to other
parties which offer R&D and innovation services.
Universities increasingly need to show their
relevance with reference their contribution of their
research to welfare and public wellbeing. Together
with the mounting pressures on university budgets,
this leads to a growing drive to exploit the results of
their curiosity-driven work in every possible way.
It appears that the differences between universities,
RTOs and company labs can no longer be described in
the traditional knowledge chain model of fundamental
research in universities, commercially driven R&D in
company labs and a bridging role for RTOs. Maybe
the mission-based differences – university research
seeking scientific opportunities, companies seeking
commercial opportunities and RTOs seeking to
contribute to innovation as a public goal – can be
sustained somewhat longer. But we are also seeing
differences fading in this respect. Universities take
the public goal of innovation on board; they not only
put the exploitation of research results higher on
their agendas but also put their competences to use
for client driven work. Companies are starting to take
up public responsibilities. So the mission of RTOs is
impinged on by both sides in certain areas and their
‘additionality’ is increasingly difficult to define, or is
at least changing in character.
2.11 I nstitutional forces:
the RTO perspective
As stated in the beginning of this paper, managerial
independence is one of the factors that distinguishes
RTOs from government laboratories. So ultimately
the actions that the RTOs themselves can and want to
undertake in reaction to or to prepare for market and
political forces will be very important in determining
their potential futures.
Of course the strategic capabilities of the RTO
management are very important, because they deal
with future positioning, making the right choices
with regard to research focus areas, and with regard
to partnerships and networking. We have seen that
all of these areas are changing very rapidly. Our
impression is that none of the European RTOs have a
clear picture of how their future looks. Most of them
have been evaluated/reviewed recently (e.g. VTT,
FhG, TNO, and probably most others as well). The
outcomes of these reviews were not at all consistent
with each other, so different RTOs have received
different messages with regard to their future
positioning and strategies. We can think of many
explanations and reasons why the evaluations differ
so much in their outcomes. But it is probably more
important to recognise that European RTOs do not
really have a collective answer to this. The overall
picture is one of fragmentation. Because of that,
the association in which they are united (EARTO)
is relatively powerless. The EUROTECH subgroup
brings together the management of little more than
ten large European RTOs, such as FhG, TNO, ARC,
QinetiQ and the JRC. This informal group has set
itself the following goals:
• Exchange of views/information among large
research organisations on important issues
concerning European research policy;
• Active involvement in the development of the
European Research Area;
• Stimulation of scientific cooperation
benchmarking projects between members.
and
Both EARTO and Eurotech occasionally succeed in
reaching a common position with regard to issues
of common interest (e.g. the EU rules with regard
to state aid for R&D). But they still have a long way
to go to make a joint strategic contribution to the
development of the European Research Area.
There are several issues on the very practical
institutional level that also deserve some attention.
Most critical for the future of RTOs are the following:
• Finding and keeping the human resources needed
to respond to the rapidly increasing complexity
of R&D problems, especially when the local
interest for studies in science and technology is
declining;
• Finding new ways of shared management of
assets (IP) in networked environments and PPPs
to create a ‘open innovation’ environment;
• Organising networked programs and projects, in
particular in the early stages of their development,
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functions in which RTOs operate will be contested
from two sides.
The Future of Key Research Actors in the European Research Area
when joint goals and responsibilities have to be
established;
• Develop impact assessment and new ways of
being accountable as alternatives to increasingly
rigid control mechanisms, which can only lead
to a reduction in the vital creative behaviour of
researchers and institutional excellence;
• Institutional
learning
and
knowledge
management are particularly important to
increase productivity, which is a necessity
because of growing competition in research,
development and innovation services.
• For RTOs it may also prove to be important
how they are embedded in their regional/local
environments. How much synergy (e.g. labour
market, supply chains and knowledge networks)
is being built at these levels is largely dependent
on whether the broader socio-economic policy
environment is focusing on global competitiveness
or on building local/regional strengths.
3. Future outlook
Some of the drivers mentioned above require
extensive strategic interpretation, organisational
development and building new types of linkages
with other actors:
This chapter draws attention to the way in which different
actors interact in the levels of R&D and innovation
systems and how this shapes the space in which RTOs
operate. It discusses which forces and variables are
specifically relevant for the future of RTOs and how they
can be perceived differently.
130
of integration leaves much room for uncertainty,
which is partly linked to the development of the
role of the nation states. How much does their
vision and strategy deviate from the ‘European
model’?
3.1 Drivers for change summarised
The forces described above can all be considered as
drivers for change of RTOs. None of the forces is very
specific for the RTOs - most work on the level of the
innovation or R&D systems in which the RTOs are
just one specific set of actors. It is hard to analyse
the future change of RTOs in direct causal linkages.
As RTOs are part of larger systems, their future is
dependent on the actions of other actors as much as
on the amount of control they can exert on their own
position and on the role of other actors. And many
developments and drivers are less certain than may
appear from the account above. Perceptions of where
things are going with regard to uncertainties in the
drivers mentioned above are a very important basis
for strategic action. For the purpose of our analysis
(in particular for the development of scenarios) not
all drivers need to be treated in the same way.
Some of the drivers are seen as contextual but very
influential:
• We assume that the development of global
markets and of global sourcing is a fact of life in our
contemporary world, which can only be stopped
by major political upheaval on a global scale.
• The same goes for the building of Europe and
the European Research Area. However the pace
• The pace of the socialisation process of science,
technology and innovation is uncertain and
unevenly distributed among sectors (e.g. a
relatively high pace in ICT-driven areas and a
relatively low pace in the chemical industry).
• The concept of open innovation requires the
invention of new networked business models
and in particular a new approach with regard
to intellectual property rights. This change will
go together with a lot of strategic behaviour of
organisations.
• ‘Fading boundaries’ are a complex set of drivers
on many different levels. The uncertainties
are not so much associated with the fading of
the boundaries as much as with the ability to
invent a new ‘regime’ in which functions and
roles are taken care of and actors can recognise
themselves.
Another set of drivers is largely internal to the RTOs.
They are confronted with a number of potentially
problematic internal static and dynamic factors, e.g.
the availability of qualified personnel, a shortage
of strategic capabilities outside the direct domain
of technology development and the difficulties any
large organisation has in managing creativity and
excellence.
3.2 Uncertainties
The changes that are now taking place in the
innovation systems and/or R&D systems level in
which RTOs are embedded do not automatically
follow from the driving forces described before. The
1.The interlinked development of a knowledge
economy/society and a networked economy/
society is leading to an increasing number of
actors that play a role in the systems. New
structures, institutions and co-operation models
appear. RTOs need to re-position themselves in
this changing environment. But even though
RTOs may be managerially independent, they can
only do so in close co-operation and in agreement
with their public ‘owners’.
2.The internationalisation (the building of a
European Research Area) and globalisation of
R&D is particularly strong in the most R&Dintensive sectors of the economy (e.g. ICT or
biotechnology based sectors). This process
is beginning to have a serious impact on
RTOs which have until recently been seen
and governed primarily as parts of national or
regional systems. In many focus areas RTOs need
to build international technology positions. In the
short term, discussions will most likely focus on
the selection and/or establishment of European
centres of excellence and the role of the existing
institutions in this international context. The
pace with which RTOs can make the change will
determine their future position.
3.There is growing uncertainty about the concept
of innovation systems and even more so about
how we can judge the functioning of innovation
systems.
•There is no clear vision and even less a clear
set of indicators that can be used to judge
the performance of innovation systems. Even
the straightforward linking of innovation
to competitiveness and the measurement
of competitiveness itself is far from being
resolved.
•Another factor of great uncertainty is the
future financing of innovation (in particular
the division between private and public
financing) and, as a consequence, the future
financing regime for RTOs. The present
situation is one of divergent and sometimes
even contradictory tendencies. In certain
areas private funding is growing, in others it is
declining. There is pressure to increase public
financing, but in practice most governments
are reluctant to do so.
•A third uncertainty relates to the concept of
knowledge production or the changing nature
of science, technology and innovation. On the
one hand we see a move towards user-oriented
approaches in which experimentation, social
sciences, design and a shorter time horizon
tend to become more important. But at the
same time we can witness a growing interest
in and growing expectations of longer term
fundamental research in new technologies
(note the increasing flow of funding to nanosciences and biotechnology).
These uncertainties translate into strategic
uncertainties for RTOs themselves and even more
so for the public bodies that govern them. RTOs
are usually too big (facing too many risks) to take
an experimental trial-and-error approach and
public bodies are simply incapable taking such an
approach. RTOs have largely succeeded in becoming
learning organisations focusing on technology,
but they are still very far away from being learning
organisations with a focus on innovation.
Developments in innovation systems and RTOs will
be largely dependent on how the different actors
perceive the above-mentioned developments and
uncertainties and on how they strategically act
based on their perceptions.
4. Scenarios
This chapter outlines three scenarios based on different
trajectories which could follow from the previously
described developments, drivers and uncertainties.
The time horizon taken is one of 10 to 15 years. Given
the dynamics for change there is no real ‘business as
usual’ scenario thinkable. The first scenario – ‘strong
RTOs’ – comes closest to this, seen from the perspective
of continuity of the organisations, but it is a scenario in
which many of the characteristics of RTOs change. The
other two scenarios involve more radical changes for the
organisations themselves.
4.1 Words come true: strong RTOs
This scenario sees the development of RTOs in
the context of the hypercompetitive, globalising
markets dominated by a limited number of large
companies, governed by policies which are largely
based on a strong belief in free market mechanisms
but which also see improving competitiveness as
an important national policy goal. Over the next 10
to 15 years we will witness a movement towards
the establishment up to 10 globally operating
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most important sources of uncertainty, different
perceptions and different strategic behaviour can be
summarised as follows:
The Future of Key Research Actors in the European Research Area
RTOs or RTO ‘conglomerates’ as strong R&D and
innovation actors in increasingly networked and
internationalised innovation systems. They will be
the focal points in large networks of many actors,
including smaller and regionally based RTOs. Their
activities will be a mixture of industry/marketdriven research and (international) public mission
(e.g. environment, health, security,...) research.
The funding structures will be more or less similar
to now. The governance structures and government
support will reflect the internationalisation. To that
purpose not only RTOs but also governments will
join forces and resources.
This scenario supposes that European RTOs will
realise their stated goals (the ‘words come true’
in the scenario title) to become global players and
preferred suppliers in certain selected technology
areas. They will manage to transpose the image of
strong organisations that they have now in their
national contexts to the global playing field which is
rapidly being established.
132
They can only do so with strong support from
national and European policies, in particular
through the growth of public research funding and
through inventing new ways of governance which
support internationalisation. Simply transposing
the national RTO model to the European level (one
European Institute of Technology) most likely
will not work. But a model in which several strong
alliances are forged is very realistic. Strong crossboarder collaboration and most likely the merging of
activities and/or entire RTOs are necessary to build
sustainable positions. Rapid internationalisation
of activities is necessary to cope with fast growth
of S&T-driven development in China, India and
other emerging markets. Most likely this involves
developing a strong presence with R&D facilities in
these markets.
Universities will not be able to make the necessary
transition fast enough, as they are facing other
problems with regards to quality and attractiveness
of (science) education and selection of research
focus areas, which are hard to solve within existing
structures.
With increasing competition for new markets,
company research tends to focus on the short term,
with the exception of a few research areas.
Implicit to this scenario is a concept of knowledge
and knowledge production which is not very different
from what we know now. It is largely based on the
linear model which goes from basic research, via
applied research and development to the marketing
of products and services. Policy concepts based on
this linear model are driven by a strong belief that
more investment in basic research leads to results
which need more applied R&D to be translated into
useful products and services.
Competition for markets for innovative goods and
services is led by globally operating companies,
with relatively large budgets for development.
The fast-growing markets in China, India, Brazil
and other countries will attract major production
facilities, followed by the research necessary to
sustain long term competitiveness of the facilities.
New generic technologies originating in life
sciences and nano sciences will be the main drivers
for economic growth based on this competitive
model. Being competent in these technologies
requires considerable investment and ‘big research
infrastructures’ backed by large scale public research
investment. Several public-private collaborative
programmes will drive the development of these
generic technologies. The RTOs will have long term
programmatic arrangements with a number of large
companies, providing them with key knowledge in
specific areas based on the opportunities of RTOs to
make long term investments in certain areas. Public
support includes extensive funds for knowledge
transfer to SMEs.
The EU will support the globalisation of European
RTOs with increased funding at the European level
and most likely will try to complement this with the
creation of a truly European RTO or network of RTOs,
as proposed in the European Institute of Technology.
The Member States complement EU policies with
growing support for research and development. In
other words, this scenario builds on fully realising
the Lisbon targets of increasing investment in R&D
and greater numbers of researchers in Europe and
abroad. It supposes the dominance of researchdriven modes of innovation.
4.2 D
inosaurs lose:
the dissolution of RTOs
This scenario supposes a rise of conservationist
tendencies (based on fundamentalist and/or
nationalist sentiments) in politics, stressing the
preservation of values instead of innovation. People
have become fed up by the constant pressure to be
more productive and to consume more new products.
In other words their ‘take-up capacity’ has reached
its limits. The funding of R&D is largely left to the
private sector and governments concentrate their
R&D efforts on classical public issues such as safety
Knowledge production is a bi-polar concept in
this scenario. On the one hand we observe some
emphasis on basic (university) science as one of the
fundamental values in society, with relatively little
pressure on results, except maybe for its educational
value. On the other hand we also find a strongly
demand-driven, almost instrumental approach in
research addressing public issues (e.g. to raise
productivity in healthcare as a response to the
increasing demands due to aging populations). In
other words, in this scenario knowledge production
is not a major issue in itself, not for society at large
and certainly not for politics. It is a tool to solve
certain well identified problems.
In such a cultural and political environment, R&Ddriven industries will probably move fairly rapidly to
world regions where competition-driven innovation
is valued as a major driver for growth. But most likely
these regions will face the same kind of problems
as soon as they have reached a certain level of
welfare. And they will have to face the fact that their
strategies for export-led development do not work
anymore. Europe seems largely to be satisfied with
its relatively successful service-driven economies
and being a very attractive centre of history, culture,
architecture and creativity-driven activities (at least
within the boundaries of the value-driven politics)
for people from all over the world.
A first policy step may be a full privatisation/
liberalisation of the public research sector (along the
lines of the Thatcherist UK example), except in those
areas considered to be essential for certain public
issues. The Member States’ support for EU policies
and R&D-funding is weakening and it is generally
felt that there is no more need for funding European
R&D collaboration (e.g. because it is perceived that
industries will use the funding to prepare for their
move to Asia). The resources that remain available will
be largely used for basic research and probably some
large scale international research infrastructures.
Support for ‘industrial technologies’ and private
sector innovation-oriented activities will be stopped.
The pressure on SMEs to become more innovative,
usually a major strategic target for RTOs, will fade
away. The overall size of the RTO activities rapidly
shrinks by at least 50 per cent because of lack of
public and private support, without the functions
being taken up by other actors. The knowledge
economy will lose science and technology as a
major driving force and instead a slow or no growth
economy appears which largely builds on services.
In this context RTOs rapidly lose ground. Some of
their activities are only sustainable when they move
with their industry clients to other parts of the world,
where similar competing technological capabilities
are rapidly being built. Public sector activities will
be taken out of the RTOs and brought (back) into
government. A radical shift of focus of RTOs on
service activities is highly unlikely. First they face
the constraints in (human) resources to work on the
completely new models of knowledge production
required for services (e.g. user-driven, reverse product
cycles). Secondly, it is even more unlikely that the
organisations themselves, having been shaped in the
supply-driven environment of ‘big technology’, can
cope with the flexibility and direct user-interaction
which is required for services innovation.
4.3 Networks of networks for innovation
Most markets around the world have reached
maturity at a very fast pace. Rapid double-digit
export-based growth to catch up on basic needs
as is happening today in India, China or the new
Member States of the EU has become an exception.
Old innovation models based on competition with
new products and processes in the marketplace
or on public needs programmes (e.g. healthcare,
energy and environment) do not work anymore. It
is recognised that the take-up capacity of markets
for innovations is limited, whereas the possibilities
to create innovations are growing. Most innovations
have become subject to extensive processes of
‘social embedding’ and require intensive interactions
between all stakeholders. However, contrary to the
present situation this is not seen as problematic,
but simply regarded as the way things are done in
democratic, economically mature societies. From the
perspective of firms this is the only way to reduce
risks and build perspectives for market growth or
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The future of RTOs: a few likely scenarios
and security, healthcare, environment and energy.
Research on such issues will be taken out of the RTOs
with their managerial independence and be brought
back under direct government responsibility. Many
RTOs will lose a major part of their longer term public
funding sources. A certain level of public support
for fundamental scientific research will remain in
place. Fundamental research is seen as a university
task, and maybe also as a task of a few specialised
institutes with close linkages to universities, such
as the Max Planck Society institutes. The move
of such institutes in the direction of more applied
research and associated linkages with companies
is not publicly supported and will not take place.
Competition by innovation has disappeared from the
public agenda and is being replaced by competition
in values.
The Future of Key Research Actors in the European Research Area
entirely new markets. From an innovation perspective
it is the only way to cope with the endless range of
choices based on the new generic and converging
technologies. And from a public interest perspective
it is the only answer to the spread of higher education
throughout the population.
This scenario supposes that the systematic
production and use of knowledge have become
wide-spread throughout society. Knowledge
production is being ‘socialised’. It has become part
of everyday life. The interactions that govern the
process of knowledge production now cover the
entire ‘knowledge chain’ from basic research, via
applied research and development to introducing
and implementing applications. The challenge in
this scenario has been to develop the mechanisms in
which supply (the knowledge about opportunities)
and demand (the knowledge about needs and
wants) effectively meet and interact throughout the
entire knowledge chain.
134
Scientific and technological research and
development has become essentially fully
transparent, which also shows in its physical
infrastructure. The image of big research laboratories
in relatively secluded places has disappeared. The
facilities are now located in daily life environments
which facilitates interactions on the many levels
required. The buildings in which the activities are
housed are ‘permeable’ to facilitate transparency
and interaction (see for example the plan for the
Seoul Media City). Concentrations of this kind of
intellectual activities do occur, but the overall look
and feel is one of highly flexible small-scale outfits.
This is necessary because in this scenario users and
being close to them have become really important
and recognised drivers of innovation.
The overall picture is one in which the emphasis
lies much more on innovation as a social process
than on gaining competitive advantage. Systematic
knowledge production or research and development
are simply part of this model.
It has been a great challenge, but after initial
problems and often having been ‘dragged in’ by
their clients, RTOs have been very fast to recognise
the changing conditions and have managed
the transition successfully, benefiting from the
many linkages they already had in their regional,
national and European environment.10 The greatest
complicating factor in the process was that most
10.A network analysis of framework programme participation showed for
example that the Fraunhofer Gesellschaft in the area of ICTs is on average
less than 2 collaboration steps away from all other participants (Peter
Johnston, e.o.).
RTO management had to give up ambitions to turn
the RTOs into big and strong global organisations,
and instead focus on opportunities to enter into
productive and organisationally flexible interactions
with other players. For the management this meant
giving up a lot of autonomy and handing over power
to a multitude of players in different alliances.
RTOs have managed to capture new trends like userdriven research and ‘research by design’ in their
collaboration networks, thus fully adjusting to new
ways of interacting between knowledge production
and usage. And they managed to build all the
necessary linkages with public decision-making
in government, civil society and with companies.
This was crucial to developing the new funding
mechanisms which are essentially directed toward
interaction and collaboration and which due to the
timely compression of the knowledge chain could no
longer be built on the outputs of a specific step (e.g.
basic research with peer review and scientific outputs).
The whole system is now built around programmatic
agreements between stakeholders. In many cases,
but not necessarily, the programmes are of a publicprivate partnership nature in which universities
usually participate with basic research (also to
increase the group of knowledgeable people).
The RTOs have put building such programmes with
other players at the centre of their strategy. They have
become fully open and very flexible organisations.
Their internal structures and strategies have moved
to the background, and have almost become part of
another level of governance on a programmatic level
between many stakeholders. RTO personnel are
put at the service of the programmes, including of
course a strong contribution to the initiation and/or
the building of new programmes.
As public bodies, RTOs play a major role in most
countries in creating the best conditions for building
new innovation-oriented programmes and for
carrying out these programmes. This is based on the
fact that traditionally they have the most linkages
with other players. Governments generally felt that
is was impossible for them to acquire the knowledge
necessary to fulfil this role. Government policy
gradually limited itself to setting and maintaining the
financial framework for the innovation programmes,
including the cross-boarder aspects. On the other
hand government policy also had a growing role
in articulating the public longer term political,
economic and cultural vision that is implicit in the
development of the programmes. This vision in turn
guides the development of new programmes and
provides a basis for evaluation.
Each of the three scenarios is more or less internally
consistent but most likely they will not be mutually
exclusive. On the contrary, if we take a look at the present
day realities of political economy and the development of
innovation systems we can easily identify forces pointing
in the direction of each of the scenarios. This final chapter
looks back at the implications of the scenarios from a
policy goals perspective and gives a first evaluation.
5.1 The policy perspective on the scenarios
The first ‘words come true’ scenario is definitely
geared towards increasing the competitiveness
of Europe, European industry and European R&D.
The problem with this scenario, however, is that
it starts from a limited or reduced concept of
competition, in which the world is seen as one
big single-minded marketplace. In policy terms it
may run the risk of focusing too much attention
on input factors such as increase of investments
in R&D and present industrial strengths instead of
building a learning and innovative society which
leads to sustainable competitiveness. It also runs
the risk of focusing too much on strengthening
individual key actors such as the RTOs instead of
taking a systems perspective which focuses on
linkages between actors.
The second ‘dinosaurs lose’ scenario emphasises
more static ‘conservationist’ social values such as
safety and security and a healthy living environment.
It may also include values such as community, family,
cohesion and solidarity. But it does not include
‘enlightenment values’ which would stress openness,
dynamism, learning and innovation. There are
certain forces that could point to the global viability
of such a scenario. But this scenario may end up in
real decline when major parts of the rest of the world
aggressively follow one of the more dynamic models
(like China). It is more likely that due to a decline in
exports in, countries such as China will suddenly be
faced with a lot of internal problems and lose most of
the aggressive dynamism. For RTOs there is no real
future perspective in this scenario, but it also points
out how important some of the basic socio-political
values are for their future and that these values
should be addressed in the research, development
and innovation programmes.
The ‘networks of networks’ scenario emphasises
a rapid change to new ways of working in
innovation, R&D and RTOs. It could be read as an
idealist network society model, but in this case
most of the forces behind the scenario are real.
Contributions to speeding up solutions for social
problems are expected to come from an effective
mixture of social and technological innovations.
The system of governance changes very rapidly
to accommodate the need to make social choices
about science, technology and innovation, the
involvement of the wider public and in general the
interdependence of stakeholders in the networks
in which they operate. In other words, this
scenario makes a choice for a radical step forward
to allow the new features of science, technology
and innovation to develop and flourish. The
drawback could very well be that such a choice
is made in a world which is still governed by
relatively aggressive market-driven innovation
and competition (scenario one). This scenario
probably requires a very strong shared vision and
political backing to come true in such a world,
but it may very well be the only way Europe and
European RTOs can make real progress.
5.2 The scenarios and RTO strategy
135
If it is accepted that the scenarios are very crude
and simplistic but still adequate descriptions of the
forces with which RTOs have to deal when defining
their strategy, it is clear that there is no ‘one way out’
solution for RTOs. They have to face all the forces
which lead to the three scenarios:
• There is increasing competition in globally
liberalising markets;
• There are strong ‘conservationist’ tendencies,
coming from many different sources such as
aging populations, environmentalism, religion,
nationalism, etc., all supporting resistance to a
high pace of change in society;
• There is a need to make choices about opening up
science, technology and innovation to networks
of stakeholders and public involvement.
RTOs most likely have some comparative advantages
in reconciling these different forces into one
consistent strategy in comparison with other actors.
RTOs are used to working in a world between
public and private governance, to being evaluated
on the strength of their technology positions, to
collaborating and networking with many different
partners in many different contractual relationships,
and to being flexible in their internal organisational
structures compared with many other actors.
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The future of RTOs: a few likely scenarios
5. Scenario evaluation:
policies and RTO
strategies
The Future of Key Research Actors in the European Research Area
Some elements of the future for RTOs are relatively
clear:
• Effective networking is a key competence for the
future;
• Global excellence in certain technology areas
is necessary, even when regional stakeholders
need broad support (T-profile?);
• The steering role of governments is declining,
and discussions about government ownership of
RTOs are heating up;
• Initiating and participating in strategic
programmes will gradually become more
important than building strong institutions;
• It will be increasingly difficult to distinguish
between public tasks and market-driven
activities.
Other elements of the future will pose great
challenges for RTOs:
136
• A key issue for RTOs will be how to cover the
whole knowledge chain, from basic research to
bringing results to the market. Are RTOs aiming
for stand-alone strategies or will they give up
institutional identity in favour of effective and
flexible partnerships?
• Another issue for RTOs will be how to shape
a longer term approach toward competence
building. This can be translated into the more
general question of how to build a learning
organisation, how to put creativity to work, and
how to learn effectively about future needs from
the many interactions with other stakeholders
and from their own activities.
These are just some of the questions the scenarios
provoke. The answers are not easy but that does
not make them less important for the future of RTOs
and innovation systems in Europe. I hope this paper
conveys that the future of RTOs is not self-evident
and that development of future-proof strategic
visions and actions is urgently required.
6. Bibliography
Discussions and documents in EURAB: http://europa.eu.int/comm/research/eurab/index_en.html
6CP innovation policy network conference, The future of research, Rotterdam, April 2005, http://www.6CP.org
Bogdanowicz, M. and Leyten, J. (2001) ‘Sympathy for the Cyborg: Research Visions in the Information Society’, Foresight vol. 03, no. 04,
pp.273-283.
Chesbrough, H. (2003) Open Innovation: The New Imperative for Creating and Profiting from Technology, HBS.
High Level Expert Group ‘Foresighting the New Technology Wave’ (EUR 21357), Converging Technologies: Shaping the Future of
European Societies.
Eurolab project (2002), A Comparative Analysis of Public, Semi- Public and Recently Privatised Research Centres, final report of the EU
sponsored project, prepared by PREST on behalf of the research consortium.
Gershenfeld, N. (2005) FAB, The coming revolution on your desktop – From personal computing to personal manufacturing. New York,
Basic Books.
Gibbons, M. (1994) The new production of knowledge, the dynamics of science and research in contemporary societies, London.
Hales, M. (2001) Birds were dinosaurs once - The diversity and evolution of research and technology organisations, Synthesis report,
workpackage 6, CENTRIM, University of Brighton.
Kurzweil, R. (1999) The age of spiritual machines: When computers exceed human intelligence, Penguin Books.
Leadbeater, C. (2000) The weightless society, living in the new economy bubble, Texere, New York.
Leyten, J. (2001) ‘Public Experimentation for new ICT Markets’, Communications & Strategies 44.
Leyten, J. (2002) ‘Assessing Project e-Europe: the way forward’, Communications & Strategies, Issue 48, 4th quarter, pp. 83-96.
Leyten, J. (2004) ‘Directions for Future Socio-Economic Research on ICTs’, The IPTS Report 85, pp. 34-40.
Prahalad, C.K., and Venkat R. (2004) The Future of Competition: Co-creating Unique Value with Customers, HBS.
Thomke, S.H. (2003) Experimentation matters: Unlocking the potential of new technologies for innovation, HBS.
TNO (2005) Contributions to the Deagu-Gyongbuk Institute of Science and Technology Master Plan, Delft.
137
Willis, R. & Wilsdon, J. (2004) See through science: Why public engagement needs to move upstream, DEMOS.
7. Curriculum Vitae
Dr. Jos Leijten is head of the Innovation Policy group of the Netherlands Organisation for Applied Scientific
Research TNO. Until 2005 he was research director of TNO-STB. In 2000-2001 he was a Visiting Scientist at
the Institute for Prospective Technological Studies of the Joint Research Centre of the European Commission
in Seville. He studied geography and urban and regional planning at the Radboud University of Nijmegen
(1975) and received his PhD from the Free University of Amsterdam for a thesis on technology assessment
and technology policy (1991). He built and headed the ICT policy research group in TNO and was acting
director of TNO-STB during 1995-96. For most of his career he worked in a highly multidisciplinary research
environment. He advised and published on technology assessment and foresight; on economic, social and
public policy issues in telecommunications and the media; on political and policy-making processes in
the information society, on trends in R&D and the management of R&D institutions. He is a member of the
steering committee of the ‘6 Countries Programme – the innovation policy network’, elected president of the
European Techno-Economic Policy Support (ETEPS) network and active member of several other innovation
policy related networks.
Wo rki ng Paper 7
The future of RTOs: a few likely scenarios
TNO (2005) TNO 2015 scenario study (in Dutch, internal).
The Future of Key Research Actors in the European Research Area
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8
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Paper
Multinational Enterprises
Guido Reger, University of Potsdam
T
his report is on multinational enterprises
(MNEs) as one of the key research actors. The
specific objective here is to analyse trends and
possible future changes in knowledge production
by multinational enterprises and the relative role
of MNEs in knowledge production in the European
Research Area. The time horizon of the scenario will
be to 2020.
The conservatively estimated 70 000 MNEs in the
world play a major role in global R&D, not only
through activities in their home countries but also,
increasingly, abroad. They account for a major share
of global R&D: with USD310 billion spent in 2002,
the 700 largest R&D spending firms of the world – of
which at least 98 per cent are MNEs – accounted for
close to half (46 per cent) of the world’s total R&D
expenditure (USD677 billion) and more than twothirds (69 per cent) of the world’s business R&D
(USD450 billion). The R&D spending of some large
corporations is higher than that of many countries
and six MNEs (Ford Motor, Pfizer, DaimlerChrysler,
Siemens, Toyota, General Motors) spent more
than USD5 billion in 2003 on R&D. Further, MNEs
dominate industrial R&D not only in quantitative
terms but also in qualitative ones. The qualitative
importance of MNEs in the overall innovation
process lies in complex and radical innovations,
the high availability of resources, production and
commercialisation of new products or services, very
good market access and distribution networks.
The management of technology and R&D in
multinationals has dramatically changed in the
last decades. The following aspects are mainly
mentioned in empirical studies:
• R&D as an strategic element in competition;
• Time-based strategies to decrease time-to-market;
• Integrating the various elements of the value chain;
• Increasing relevance
networking;
of
innovation-related
• Internationalisation of innovation;
• Organising R&D activities in MNE, centralisation
versus decentralisation.
After the analysis of changes in knowledge
production methods by MNEs and the relative role
of MNEs for knowledge production in the European
Research Area, the next step of our analysis is the
detection and identification of key factors. They
are driving forces for change and future trends of
knowledge production of MNE. For all key factors,
we develop future projections which show how these
key factors may develop in the future until 2020. The
future projections are the basics for the scenario
development and the creation of future spaces. As a
result of this step, we develop four scenarios:
1. ‘The Long Boom’;
2. ‘Ups and Downs’;
3. ‘Handpicked Innovation’; and
4. ‘Zero Growth’.
The developed scenarios describe future spaces,
which are several, possible images of a future
situation and provide a basis for the following impact
analysis and recommendations.
1. ‘ The Long Boom’
Impact and Policy Recommendations
Multinational enterprises have a strong focus on their
innovation strategy in the scenario ‘The Long Boom’.
The investment in innovation can be characterised
as dramatic. The internationalisation strategy
includes the export of innovation as well as centres
of excellent innovation abroad (CoEIs). Furthermore,
the technological competencies are covered by an
open innovation model. Under ‘The Long Boom’
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Multinational Enterprises
Executive Summary
The Future of Key Research Actors in the European Research Area
scenario the public R&D system is very important
and high-tech SMEs also have a strong impact on
the European Research Area. These high-tech SMEs
are pushing technological innovation; they are very
competitive and the entrepreneurial spirit is the basis
and stimulus for technological innovation.
In ‘The Long Boom’ scenario, EU policy may follow
a ‘Policy of Balance’ and find adequate forms of
regulations and intervene only in a modest way.
The policy intervention should be limited to ensure
the frame conditions for competition and a climate
for innovation and entrepreneurial spirit. Regarding
the public R&D system, technological competencies
are very important and should be continuously
built up and cultivated. High-tech SMEs and their
competencies should be heavily supported by the
European Union. The ‘Policy of Balance’ hereby also
means not to privilege MNEs over the other actors in
the European Research Area. This type of policy may
try to find a balance between the different actors
and between globalisation and localisation.
innovation abroad and import innovation to the
European market. The innovation is only applicationbased with a low degree of technological novelty.
MNEs are characterised by a strong ‘inside-orientation’
in the innovation process. Due to the stronger focus
of multinationals on internal knowledge generation,
the importance of the public R&D system is lower. The
same is true for the importance of SMEs as technology
generators for multinational enterprises. High-tech
SMEs are only one possible option; MNEs prefer their
internal innovation activities.
The main opportunity for EU policy therefore
seems to be a ‘Policy of Balance’, which includes
two tasks primarily. Due to the economic ups and
downs, which are characteristic in this scenario,
the EU policy needs to balance the economic cycle.
Another challenge for EU policy is to establish a
fruitful balance between the export and import of
innovation, permanent and accidental innovation
activities, application- and technology-oriented and
radical innovation.
2. ‘Ups and Downs’
Impact and Policy Recommendations
4. ‘ Zero Growth’
Impact and Policy Recommendations
In the second scenario ‘Ups and Downs’, innovation
and especially radical innovation dominates in
multinational enterprises. However, the overall
investment in innovation stagnates. Part of their
internationalisation strategy are centres of excellent
innovation abroad (CoEIs) and an open innovation
model. The public R&D system is very important as a
competent partner for industry. High-tech SMEs have
developed good technological competencies and
are partners in the open innovation process as well.
However, due to the economic up-and-down-swings,
a cyclical ‘birth and death’ of high-tech SMEs arises.
In our ‘Zero Growth’ scenario, multinational enterprises
and networks of MNEs and other companies dominate
the economy and restrain competition. Innovation as
the engine for economic development becomes less and
less important to differentiate in competition. Mutual
formal and informal agreements, cartels, or oligopolies
– either between MNEs or networks – dominate the
economic scenery. This situation is supported by an
MNE-dominated EU policy and leads to a lack of linkage
between innovation and company strategy, accidental
innovation, handpicked investment in knowledge
production, and only incremental innovation. All in all,
multinationals in Europe are no longer competitive
and are the losers in the innovation race. Due to the
described lack of innovation in multinational enterprises,
there is only a limited demand for the technological
competencies of the public R&D system. Joint R&D
projects and contract research have become less and
less in that ‘Zero Growth’ scenario. The awareness of
industry and policy for a sophisticated and specialised
public R&D system has decreased. As a consequence,
investment in the public R&D system dramatically
dropped. Finally, the technological competencies of the
European public R&D system are no longer competitive
and are regarded as average or below-average
compared with other nations. As a consequence of that
situation high-tech SMEs have nearly disappeared from
the marketplace. It is no longer attractive to found a
technology-based start-up firm. The entrepreneurial
spirit is completely nonexistent.
140
The conclusion shows that the influence of policy
regulations and even interventions at the EU level
seems to be fairly limited in this ‘Ups and Downs’
scenario. One main task and also a challenge of EU
policy is to balance the economic cycle. A further
recommendation for EU policy is to try to increase
investment in knowledge production and to improve
the attractiveness of Europe as the best place for
foreign investment in innovation.
3. ‘Handpicked Innovation’
Impact and Policy Recommendations
The ‘Handpicked Innovation’ scenario draws a picture of
a future situation in which MNEs generate innovations
only by chance. The strategy to make only handpicked
investment dominates in MNEs. They generate
1. Introduction
1.1 Objectives
The Science and Technology Foresight Unit of DG
RTD of the European Commission has launched an
expert group on ‘The Future of Key Research Actors
in the European Research Area’. The group will
accomplish its tasks by producing a series of reports
on the key actors relevant for the European Research
System, i.e. universities, public research institutions,
enterprises, researchers, civil society, national
governmental bodies, and regional governmental
bodies. The general objective is to develop various
scenarios of the future of knowledge production by
each of the actors and a synthesis of the different
scenarios in order to improve the performance and
effectiveness of the European Research System.
This report is on multinational enterprises (MNE) as
one of the key research actors. The specific objective
here is to analyse trends and possible future changes
in knowledge production by multinational enterprises,
and the relative role of MNEs in knowledge production
in the European Research Area. The time horizon of
the scenario will be to 2020. The core question of this
scenario is how the long-term trends influenced by
the behaviour and interaction of MNEs might shape
the European knowledge society and be taken into
account in designing the European Research Area
strategy. The sub-aims of this report are:
• Identifying important trends and changes of
knowledge production by MNE;
• Assessing the relative importance of MNEs in
knowledge production within society;
• Developing a scenario on the future of knowledge
production of MNEs until 2020;
• Analysing the impact of the scenario on the
European Research Area and the European
knowledge society.
1.2 Approach
The term scenario is used for a variety of different
objects from simple alternative projections to the
results of complex simulation-models. By scenario
technique we understand here the integration of
methods for handling uncertainty (future-open
thinking), complexity (linked thinking or system
thinking) and competition (strategic thinking). Our
scenario approach is based on the eight steps of
scenario building originally introduced by Ute von
Reibnitz (1988, 1992) in Germany, and the further
work of Fink, Siebe and Kuhle (2004, pp. 174-175).
We understand by a scenario a tool that can be
regarded for improving decision-making against the
background of possible future environments. Our
scenario for MNEs as one of the key research actors
will be developed according to the following steps:
1.Defining the subject of the scenario process:
The specific object here is to analyse trends and
possible future changes in knowledge production
by multinational enterprises and the relative role
of MNEs in knowledge production in the European
Research Area. The focus will hereby be on the
production of technological knowledge.
2.Detection of key factors: Every scenario field
consists of a large number of influence factors.
Using the full number of identified factors during
the building of scenarios would lead to very
complex scenarios. Only those factors that are
either characteristic for the development of the
whole scenario field or have a strong influence
on the scenario field are selected. These ‘key
factors’ are extracted with the help of an influence
analysis.
3.Foresight of alternative projections: In this
step we have to define a time horizon by the
scenario team, i.e. 202. After this, possible future
projections of each key factor are identified.
The aim is not only to find the one projection
that is most likely to take place, but also to find
plausible alternative.
4.Calculation and formulation of scenarios: The
goals of this step are, on the one hand, that
each scenario should represent a possible and
consistent future situation and, on the other
hand, that the set of scenarios should represent
the best ‘windows of possibilities’. To work
out the scenarios, the consistency of all pairs
of projections is assessed and all possible
combinations (projection bundles) are checked
by specific software. To find a suitable set of
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Multinational Enterprises
A first but crucial step to come out of this situation
is to provoke a much higher degree of competition.
European policy should leave behind the ‘MNEdominated policy’ in order to address all actors of the
European research area. The general recommendation
for EU policy could be to follow a path of deregulation.
Furthermore, innovative products and services could
be stimulated by public procurement.
The Future of Key Research Actors in the European Research Area
5.Analysis, mapping and interpretation of
scenarios: In this step each scenario is
analysed in detail. What are the drivers? Who
are the winners and losers? Opportunities
and risks are estimated for each option under
the conditions which are described by the
scenarios. What are the chances and risks that
result from each single scenario? What would
have to be done if we could assume that this
scenario appears?
142
6. T
he structure of the paper will be the
following: chapter two will describe the role of
MNEs in knowledge production and research
systems and chapter three recent key trends.
In chapter four, the driving forces for change
are analysed and future trends elaborated
which will serve to develop four scenarios
for MNEs in chapter five. The impacts of the
four scenarios on the European Research Area
and the European knowledge society will be
analysed in chapter six.
2. The Role of
Multinational
Enterprises in the
Knowledge Production
and Research System
In this chapter, the main terms will be defined and
the quantitative and qualitative role of MNEs in
knowledge production and the research system will
be analysed.
2.1 Defining the Main Terms
A multinational enterprise (MNE) or multinational
corporation (MNC) or transnational corporation
(TNC) is one that spans multiple nations with its
business activities and value chain. MNEs have
offices, factories, branch plants, and innovation
activities in different countries and usually they
are very large. The term multinational enterprise
is used here to include all large corporations
which are active in multiple countries. However
it is clear, that the internationalisation behaviour
and strategies of MNEs can differ very much from
each other. For example, Bartlett and Ghoshal
(1989) distinguished the behaviour and strategy
of internationally-active corporations between
forces for global integration and forces for local
responsiveness, and divided them into four
different types of corporations (see Figure 2.1).
This distinction in turn has consequences for
the management, values, configuration, control
mechanisms, knowledge transfer, innovation and
role of the subsidiaries of the corporation.
Figure 2.1
Internationalisation behaviour and strategies
of large corporations
high
Forces for Global Integration
scenarios, the highly-consistent projection
bundles are systematically grouped in a specific
kind of cluster analysis. The characteristic
elements of each bundle are described in the
scenario formulation, which can differ from
formal descriptions to stories about the future.
Global
Transnational
International
Multinational
low
low
high
Forces for Local Responsiveness
Source: Bartlett, Ghoshal 1989.
Innovation can be understood as the transformation
of knowledge into new products, processes, and
services. This includes technological knowledge as
well as other types of knowledge (e.g. knowledge
about the organisation, processes, markets,
customers, external partners, diffusion) which
is necessary to innovate. Among economists,
innovation is widely recognised as the main
driver for productivity, economic growth and
development.
Research and development (R&D) is clearly
only one component of innovation activities and
knowledge production. However, it is still at the
core of technological innovation and knowledge
generation and represents the most developed and
Figure 2.2
R&D expenditure by selected MNEs and
economies, 2002, USD billion
MNEs
Economies
Ford Motor (US)
7.2
Spain
6.8
Taiwan Province of China
6.5
Switzerland (2000)
6.3
DaimlerChrysler (Germany) 5.9
Siemens (Germany)
5.7
Belgium
5.5
2.2 Quantitative Importance of MNEs for
Knowledge Production
General Motors (US)
5.4
According to the World Investment Report (UNCTAD
2005), the conservatively estimated 70 000 MNEs in
the world play a major role in global R&D, not only
through activities in their home countries but also
increasingly abroad. They account for a major share
of global R&D: with USD310 billion spent in 2002
(see DTI United Kingdom 2004), the 700 largest
R&D-spending firms of the world – of which at least
98 per cent are MNEs – accounted for close to half
(46 per cent) of the world’s total R&D expenditure
(USD677 billion) and more than two-thirds (69 per
cent) of the world’s business R&D (USD450 billion).
The R&D spending of some large corporations is
higher than that of many countries (see Figure 2.2).
In six MNEs (Ford Motor, Pfizer, DaimlerChrysler,
Siemens, Toyota, General Motors), R&D spending
exceeded USD5 billion in 2003.
Over 80 per cent of the 700 largest R&D spending
firms come from only five countries: the United
States, Japan, Germany, the United Kingdom and
France, in that order (see United Kingdom, DTI
2004). Only one per cent of the top 700 are based in
developing countries, although several have moved
up the ranks since the late 1990s (see UNCTAD
2005). Almost all these firms come from Asia,
notably from South Korea and Taiwan, while only one
is from Africa (South Africa) and two are from Latin
America (Brazil). The 700 largest R&D spenders are
concentrated in relatively few industries, more than
half of them were in three industries: IT hardware,
automotive, and pharmaceuticals/biotechnology.
All in all, MNEs clearly dominate business R&D in a
global perspective. Only a few countries, generally
the largest R&D spending ones, account for the
major share of business R&D. Within those countries
a relatively small number of enterprises dominate
R&D activity. Most R&D is conducted by firms in
the ICT, automotive and pharmaceutical/ biotech
industries.
Israel (2001)
5.4
Pfizer (US)
4.8
Brazil (2003)
4.6
Toyota Motor (Japan)
4.6
Finland
4.5
Austria
4.5
IBM (US)
4.4
GlaxoSmithKline (UK)
4.4
Denmark
4.3
Matsushita Electric (Japan) 4.3
Russian Federation
4.3
Volkswagen (Germany)
4.3
Microsoft (US)
4.0
Intel (US)
3.8
India (2001)
3.7
Johnson & Johnson (US)
3.7
Motorola (US)
3.5
Sony (Japan)
3.4
Nokia (Finland)
3.4
Aventis (France)
3.3
Cisco Systems (US)
3.2
Ericsson (Sweden)
3.1
Honda Motor (Japan)
3.1
Hewlett-Packard (US)
3.1
NTT (Japan)
3.1
Philips (Netherlands)
3.0
Hitachi (Japan)
3.0
Novartis (Switzerland)
2.9
Mexico
2.7
Singapore
1.9
Ireland
1.4
Turkey
1.2
Poland
1.1
Hong Kong, China
1.0
Czech Republic
0.9
South Africa
0.7
Hungary
0.7
Malaysia
0.7
Chile
0.5
Argentina
0.4
Thailand
0.3
Egypt (2000)
0.2
Source: UNCTAD 2005 and DTI United Kingdom 2004.
143
Wo rki ng Paper 8
Multinational Enterprises
widely available comparable statistical indicator
of industrial innovation activities. According to
international guidelines, R&D comprises creative
work ‘undertaken on a systematic basis in order
to increase the stock of knowledge, including
knowledge of man, culture and society, and the
use of this stock of knowledge to devise new
applications’ (OECD 2002b, 30). R&D involves
novelty and the resolution of scientific and
technological uncertainty and includes basic and
applied research along with development.
The Future of Key Research Actors in the European Research Area
2.3 Qualitative Importance of MNEs
for Knowledge Production and the
Relationship with New Technologybased Firms
The question of how firm size relates to the ability
and propensity to innovate is one of the oldest
in political economy. Inspired by the contrasting
hypotheses of Schumpeter, this question has
been widely but inconclusively examined, giving
rise to the second largest body of empirical
literature in the field of industrial organisation.
According to Tether (1998) the existence of
such a large literature is indicative of both the
importance of the question and the inconclusive
nature of the results.
144
Schumpeter’s hypothesis that large firms have an
advantage in innovation has sparked this debate.
However, this seems to contradict his earlier
contention that new, entrepreneurial firms are
more vigorous innovators. The first hypothesis
is based on the appropriability advantages
from which large firms benefit. Obviously,
an innovation will produce more profits the
larger quantities that are sold, if profit margins
are identical. Since new firms are on average
smaller than established firms, they have a
disadvantage in this respect. However, small and
young firms have more to gain from innovation,
since innovation will boost their profits more.
This applies with the greatest force when new
(and small) firms can reach a large size quickly
(see Brouwer 1998). A series of studies for both
the United States (see Acs, Audretsch, Feldman
1987, Acs, Audretsch 1988 and 1990) and Great
Britain (see Pavitt, Robson and Townsend 1987)
found that while large corporations have the
innovative advantage in certain industries, in
other markets small firms are more innovative.
This finding posed something of a paradox (see
Acs, Audretsch, Feldmann 1994), because it is
well-known that the bulk of R&D is concentrated
among the largest industrial corporations (see
Scherer 1991). The empirical research on the
relationship between firm size and innovativeness
did not produce unambiguous answers to the
question of which firm size is most conducive to
innovation (see Brouwer 1998). Which firm size
has the innovative advantage varies by industry
and by the dependent variable used. Research
has shown that large firms predominate in R&D.
The number of industries in which R&D spending
increased more than proportionally with size
slightly outnumbered those with the opposite
pattern (see Scherer and Ross 1990). But small
firms are much more innovative than large firms
when an output measure of innovation is used
(direct innovation counts). Acs and Audretsch
(1987, 1988) demonstrated that small firms are
much more efficient at innovation than their
larger counterparts.
All in all, it can be concluded from the results
that, following the oversimplified perception of
Schumpeter’s theories, the question ‘Are large or
small enterprises more innovative?’ is wrongly put,
and we shall proceed instead from the hypothesis
of a division of labour between small and large
enterprises. This division of labour refers to the
market size, the degree of novelty of innovations
and their proximity to actual production, and
the extent to which small and medium-sized
enterprises (SMEs) are involved in important
inventions, not ‘major innovations’. As regards
the size of the enterprise, various advantages and
disadvantages of small or medium-sized and large
enterprises are made clear.
The approach of Utterback (1994) is easily
compatible with the hypothesis of the division of
labour between large and small and medium-sized
enterprises in the field of innovation. The latter
play a special role in the development phase of
a product line and display a high innovation rate;
in the further course of the product lifecycle,
they can either survive by adopting market niche
strategies or will be pushed aside by larger
enterprises. Strategic solutions can be to change
to other product lines or technologies in good
time. Enterprises with several product lines can
offset these fluctuations by skilful portfolio
management. If considerations of size are
introduced to the product lifecycle model, then
it can be shown that small and medium-sized
enterprises can be sure of a secure livelihood.
A relatively long-term one, if based on a market
niche and component supplier strategy, a rather
temporary one with a first-mover or leadingedge technology strategy. The main thoughts
of Utterback and his colleague Abernathy are
summarised in Figure 2.3.
All in all, the qualitative importance of MNEs in
the overall innovation process lies in complex
and radical innovations, the high availability of
resources, production and commercialisation of
new products or services, very good market access
and distribution networks.
Dominant design, number of competing firms
and division of labour between large and
small firms
Dominant
Design
Number of firms
Late Follower
50
Early Follower
Innovation Leader
0
Invention Leader
R&D Focus on:
• Products
• Ideas
• Time
• Many hopes
R&D Focus on:
• Process
• Rationalisation
• Cost
• Few survivors
3. Recent Key Trends
The main changes in technology and R&D
management of MNEs are described here and
summarised in various models (or generations)
of technology and R&D management which may
develop over time.
3.1 Main Changes in the Management of
Technology and R&D
The management of technology and research and
development (R&D) in multinational enterprises has
changed dramatically in the last decades. Regarding
the changes in the technological knowledge production
of MNEs in the last two to three decades, the following
aspects are mentioned in empirical studies (see
overview in Edler, Meyer-Krahmer, Reger 2002):
1.R&D as a strategic element in competition;
2.Time-based strategies to decrease time-tomarket;
3.Integrating the various elements of the value
chain;
4.Increasing the relevance of innovation-related
networking;
5.Internationalisation of innovation;
6.Organising R&D activities in MNE, centralisation
versus decentralisation.
These changes are summarised in the following subchapters.
3.1.1 R
&D as an Strategic Element in
Competition
Large multinationals have more and more developed
overall strategies for their management of technology.
This is due to the fact that the cumulative nature of
technological know-how emphasises the need for
strategies to enable firms both to build knowledge
in existing core technologies and to access newly
emerging technologies to sustain long-term
competitiveness of the corporation. A survey among
209 of the top R&D spending multinationals in North
America, Japan and Western Europe shows that R&D
and technology have become key cornerstones of
the corporate and business strategy of the large
corporations (see Edler, Meyer-Krahmer, Reger 2002,
pp. 152-154). Most firms in this sample have defined
an explicit and differentiated technology strategy
in writing or included important technical elements
in their corporate and business strategy. This was
not always the case. Roberts (1995, 44) pointed out
that in the 1980s and the beginning of the 1990s
very few companies worldwide were doing much
to develop overall strategies for their management
of technology. Obviously, in the past decade major
changes can be observed in formal efforts to
develop and implement a strategic management of
technology, especially in the largest R&D-performing
companies in the Triad ((US, Western Europe and
Japan). The function of R&D is therefore changing
towards a strategic element in competition and R&D
itself may become more application- and problemoriented.
3.1.2 Time-based Strategies to Decrease Timeto-market
The time horizon for market introduction of new
products has shortened in many sectors, due to
intensifying international competition, the rapid
rate of technological change in some areas (esp.
electronics), and phased to growing expenditure for
innovation activities. Companies are reacting more
and more by shortening their innovation cycles and
including ‘time-to-market’ as a significant part of
their innovation and competition strategy (see in the
beginning of the 1990s e.g. the survey conducted
by EIRMA 1994 or Wheelwright, Clark 1992, Gupta,
Wileman 1990). The acceleration of innovation cycles
led on the one hand to the growing importance of
time in the innovation strategy. On the other hand,
innovation activities are more and more oriented to a
short-term return on investment and the new product
145
Wo rki ng Paper 8
Multinational Enterprises
Figure 2.3
The Future of Key Research Actors in the European Research Area
can ‘cannibalise’ the older one but not the mature
one at too early a stage. Von Braun (1994) argues
that innovation expenditure is increasing from cycle
to cycle and leads to an ‘R&D race’ between R&Dperforming companies. Even the large corporations
may have difficulty both in keeping pace with this
race and in financing R&D from private sources.
3.1.3 Integrating the Various Elements of the
Value Chain
146
The relation of basic research – development –
implementation is undergoing a lasting change.
Enterprises are increasingly thinking in terms of
integrated process chains of innovation. Basic
research, too, is an element in these chains and
for this very reason needs to be organised to
network closely with the areas of application. The
traditional institutional separation of basic research,
applied research, development, production and
application may be overcome. Large multinationals
are increasingly gaining their competitive edge
from a close, undistorted link-up between basic and
applied knowledge. Integrated product development
processes, simultaneous engineering and the
continually closer links between R&D, marketing
and product/process development are increasingly
emerging into the foreground as an important part
of the innovation strategy (see Gerybadze, MeyerKrahmer, Reger 1997, Leonard-Barton 1995, Nonaka,
Takeuchi 1995). This strategy of integrating the
elements of the value chain is in line with a more
‘holistic’ view of the innovation process.
3.1.4 I ncreasing Relevance of Innovationrelated Networking
There is a growing tendency of multinational
corporations to acquire technology from external
sources. Our survey among 209 technologyintensive MNEs points out the high reliance for
technology on external sources (see Edler, MeyerKrahmer, Reger 2002, 156-157). Taking into account
the results of the prior benchmarking survey (the
1991 data come from Roberts 1995a, 1995b), it can
be stated that a very important change in strategic
technology management over the past decade is
the increasing intensification of all companies’
dependence upon external sources of technology.
The number of companies which judged themselves
as highly dependent on external sources to acquire
technology dramatically increased: 35 per cent
of Japanese firms, 22 per cent of European and
10 per cent of North American firms considered
themselves to have a high reliance on external
sources in 1991. In contrast, 84 per cent of the
Japanese firms, 86 per cent of the European and
85 per cent of the North American firms made the
same statement in 1998. Our results show that the
importance of external sources for North American
companies is growing stronger in comparison with
the other sample firms (see Figure 3.1). Obviously,
North American companies paid less attention
to external technology acquisition in the past
than the western European and Japanese firms.
While there are very similar patterns of external
technological co-operation – customers, suppliers
and universities are most often mentioned – the
motives to appropriate external technological
knowledge differ between the three regions
considered. Obviously, technology-related cooperations and horizontal and vertical networking
even in core technologies, have gained in
importance.
Figure 3.1
Reliance on external sources for technology
acquisition (survey among 209 R&D-intensive
MNE)
1995
1998
2001
4
3
2
1
0
Europe
Japan
N. America
Source: Edler, Meyer-Krahmer, Reger 2002, 157.
Networking can take place between partners
belonging to the same country or across national
borders. The desire to collaborate with a foreign
partner is dictated by the need to acquire technical
or market expertise which is not equally available
domestically. Empirical evidence has reflected
this strategy and shown that, since the 1980s, the
number of newly established strategic technology
alliances has increased considerably (see Hagedoorn
and Schakenraad 1990, 1993). Strategic technology
alliances are here understood as those inter-firm
agreements that contain arrangements among firms
for joint R&D or technology transfer. It is interesting
to observe that these alliances are becoming more
and more international: agreements across borders
constitute by now almost 60 per cent of the ones
registered in the MERIT/ CATI database.1 The
number of newly-established intraregional alliances
1.The MERIT/CATI databank is a relational database which contains
information on nearly 10 000 cooperative agreements involving some 3 500
different parent companies. For more detailed information, see Narula and
Hagedoorn 1997.
Data for a more recent period (1991-2001) show a
doubling of new international technology alliances,
from 339 to 602, and a growing dominance of nonequity forms within alliances (see UNCTAD 2005,
126, based on the MERIT-CATI database). Indeed,
while the number of non-equity alliances increased
from 265 in 1991 to 545 in 2001 (i.e. in more than
90 per cent of the alliances) the number of equitybased partnerships declined from 74 to 57. US
firms continued to participate in a large majority
of strategic alliances, although their share in the
total of such alliances declined from 80 per cent in
1991 to 73 per cent in 2001. At the same time the
participation of non-Triad firms increased from 4
per cent to 14 per cent. Between 1991 and 2001, the
industry composition of alliances shifted strongly
from IT (whose share dropped from 54 per cent to 28
per cent) to pharmaceuticals/ biotechnology (whose
share increased from 11 per cent to 58 per cent). In
the latter, there is a strong incentive for MNEs to
form strategic alliances as no single company could
possibly develop excellence in all the areas of R&D
that may be required to develop a new drug.
Figure 3.2
Number of Newly Established Strategic
Technology Alliances in the Triad
(1980-84, 1985-90, 1990-94)
900
Number of technology alliances
800
US-US
700
600
500
EU-US
400
300
200
JP-US
EU-EU
100
JP-JP
EU-JP
0
1980-1984
1985-1989
1990-1994
Source: CEC 1998 and data from the MERIT/CATI dataset (see Narula,
Hagedoorn 1997).
The growing importance and extent of networking
with partners from industry or the public research
system can be continuously observed. Companies
formulated and implemented cooperation and
networking strategies more and more explicitly.
A broad bulk of empirical studies and theoretical
literature exists on this topic since the late 1980s
(see e.g. Dodgson 1993, Freeman 1991, Gerybadze
1995, Hagedoorn 1992, Hagedoorn, Schakenraad
1993, Reger, Kuhlmann 1995, Sydow 1992). The
rationale behind (formal and informal) networking
is to lower the costs and risks associated with
innovative activities, to gain access to knowledge
and competences which are not available inside
the company, to enter a new technology field or
market, to accelerate the innovation process or to
facilitate standardisation. A lack of own internal
competencies and resources can be compensated
and enriched by access to external technology. The
possible loss of technological competencies is the
flipside of this networking coin: corporations are
‘outsourcing’ greater shares of R&D and increasing
the dependency of the company on other external
actors, thus making R&D management more
complicated.
147
Recent literature point out the qualitative ‘jump’
between ‘closed’ and ‘open’ innovation (see
Figure 3.3). In closed innovation, a company
generates, develops and commercialises its
own ideas in a fully-integrated model. Large
corporations invested more heavily in internal
R&D than their competitors and took on the
best and the brightest people. Innovation-leader
strategies enabled MNEs to capture high profit
rates and build up market-entry barriers. Profits
were reinvested for funding more R&D, which
then led to creating a virtuous cycle of innovation
(see Chesbrough 2003a).
Due to a growing complexity and need for
cooperation, a more flexible open innovation
approach has occurred: skilled workers’
increasing availability and mobility, external
suppliers’ increasing capability, external options
available for unused ideas, and a dynamic
venture capital market. The multinationals
linked up closely to start-up firms, spin-offs and
the public R&D system through its permeable
boundaries. In a world where knowledge seemed
to be ubiquitous, the actual goal shifted to
building a business model where even others’
use of the corporation’s intellectual properties
could contribute to advancing its own business
(see Chesbrough 2003b).
Wo rki ng Paper 8
Multinational Enterprises
has lost relevance in Europe and Japan. In contrast,
interregional alliances with industrial partnership
between Japan-US and Europe-US have gained
importance: new alliances which contain at least
one Japanese and one US partner have grown from
186 (1980-84) to 213 (1990-94) (see Figure 3.2). In
particular, newly established Europe-US technology
alliances have increased from 221 to 457 in the same
time span, mostly in the biotechnology area.
The Future of Key Research Actors in the European Research Area
Figure 3.3
Closed and open innovation
3.1.5 Internationalisation of Innovation
Companies’ strategies to internationalise innovation
activities mainly encompass three basic subelements (see Archibugi and Michie 1995):
1.The international exploitation of technology
produced on a national basis includes exports,
granting of licences and patents, and foreign
manufacturing of innovations generated in the
home country.
2.The international techno-scientific collaboration
of partners in more than one country for the
development of know-how and innovations,
whereby each partner retains his own institutional
identity and ownership remains unaltered.
Partners here are small and large enterprises as
well as the academic world (universities, public
R&D institutes).
3.The international generation of innovation is
mainly carried out by multinational enterprises,
which aim at creating innovations across borders
by building up internal R&D networks. Innovation
activities which are carried out simultaneously in
the home and host country, the innovation-related
acquisition of, or merger with, foreign companies
and the establishment of new R&D units in the
host countries are all means to this end.
148
Source: see Chesbrough 2003a.
Gassmann and Enkel (2004) identified three core
open-innovation processes after researching a
database of 124 companies:
1.The outside-in process: enriching a company’s
own knowledge base through the integration
of suppliers, customers, and external
knowledge sourcing can increase a company’s
innovativeness.
2.The inside-out process: the external exploitation
of ideas in different markets, selling intellectual
properties and multiplying technology by
channelling ideas to the external environment.
3.The coupled process: linking outside-in and
inside-out process by working in alliances with
complementary companies during which give and
take is crucial for success; consequent thinking
along the whole value chain and new business
models enable this process.
The results of various studies which worked with
different methods are summarised in Figure 3.4. Since
this is not the place to present the data in more detail,
the analysis should focus here on two important
issues (see for a detailed presentation of the data
in CEC 1998). Firstly, the empirical studies show the
growing quantitative relevance of internationalisation
of innovation activities for all three basic subelements. Secondly, the empirical data so far shows
that the core companies from the Triad are involved in
these processes. The results point out that most of the
basic sub-elements of internationalisation strategies
can mainly be characterised by ‘Triadisation’, with
a trend towards locating more R&D activities in a
selection of developing countries. Trade and foreign
direct investment are becoming more and more global
as compared with the other sub-elements.
Since both knowledge creation and exploitation and
international competition are constantly gaining
in importance, the internationalisation of R&D has
increasing relevance for knowledge production.
One way to get a notion of the importance of R&D
internationalisation in quantitative terms is to look
at the degree of internationalisation, defined as the
Figure 3.4
Overview of empirical results and summarised
trends of the internationalisation of innovation
activities
Categories
International
exploitation
of technology
produced on a
national basis.
Forms
Exports of
innovative
goods.
Granting of
licences and
patents.
Foreign
production
of innovative
goods
internally
designed and
developed.
Empirical Results and Trends
• International high-tech trade grew
from 9.5 per cent of world trade (1970)
to 21.5 per cent (1995).
• In 1981, 38 per cent of the patents in
European countries were, on average,
applied by domestic investors, in 1993
only 19 per cent (US 53 per cent and
Japan 87 per cent).
• All countries of the EU became net
importers of technological knowledge,
whereas the US and especially Japan
are net exporters of technology.
• Analysis of the technology
balance of payments shows a
growing international know-how
transfer between R&D units within
multinationals.
• Annual average growth rates of FDI
inflows and outflows of 15 per cent and
17.4 per cent respectively (1983-95).
International Joint ventures • 60 per cent of inter-firm technology
technoor alliances.
agreements are across borders, the
scientific
Productive
vast majority thereof with partners
collaboration. agreements
from the Triad.
with the
• Strategic technology alliances have
exchange
doubled over the 1980s.
of technical
• New interregional alliances (between
information or
Europe-US and Japan-US) have gained
equipment.
in importance since the 1980s.
Joint R&D
projects with
companies and
public research
system.
International Innovative
• R&D investment by foreign firms in the
generation of activities both
US has grown by 11.4 per cent per year
innovations.
in home and in (1980-94).
host countries. • The generation of innovations is
Acquisitions of heavily concentrated in the US, Europe
existing R&D
and Japan.
labs or high• Measured by patent analysis, 22.4 per
tech firms.
cent of European large firms’ R&D is
Greenfield R&D conducted outside Europe, 11.9 per
investment
cent conducted in Europe by foreign
abroad.
large firms (Top 359 largest firms).
• Dramatic increase in the number of
inventions developed by European
multinationals’ subsidiaries outside
Europe (growth rate of 149 per cent
from 1985 to 1995).
• Highly-internationalised firms tend
to concentrate R&D in a few leading
locations worldwide and to establish
centres of competence.
Source: see CEC 1998.
Figure 3.5
Percentage of R&D budget spent outside the
home country (survey among 209 MNE)
1995
1998
25.75
30.27
4.67
7.02
23.17
28.38
Source: Reger 2002, 175.
2001
33.37
10.52
31.67
Estimated
for 2004
43.72
14.56
35.07
Investigated
companies from
Western Europe
Japan
North America
Those companies who perform R&D in their labs
abroad were asked in our survey about the function
and organisation of these activities. The most striking
result is that the concept of ‘centres of excellence’
has had a breakthrough in recent years. Out of four
possible characteristics of foreign laboratories,
almost one third of the sample labelled their foreign
laboratories as ‘centres of excellence’. However,
European companies have a much higher tendency
to set up a centre of excellence with worldwide
responsibility (43.6 per cent) than North American
(31.5 per cent) and especially Japanese companies
(21.4 per cent) do (see Figure 3.6). In contrast, 34.5
per cent of the North American and 24.5 per cent of
the Japanese companies mentioned that their R&D
units perform the same activities as domestic R&D
facilities, but adapted to the local market.
Figure 3.6
Most important functions of R&D facilities
located abroad (survey among 209 MNE)
100%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Europe
Japan
N-America
T hey focus only on regional technical support activities
They focus only on basic and/or applied research
They represent worldwide centres of excellence for a particular
technology, discipline, etc.
They perform the same activities as domestic R&D facilities, but
adapted to local market
Source: Edler, Meyer-Krahmer, Reger 2002, 160.
149
W or ki ng Paper 8
Multinational Enterprises
share of the overall R&D budget spent for R&D beyond
the borders of a company’s home region. This figure
includes R&D activities of a company’s researchers
abroad as well as the purchase of technology or
technologically-important products. Our survey among
209 R&D intensive MNEs shows a striking imbalance
if one looks at the regional origin of the companies
(see Figure 3.5). Japanese companies are much less
inclined to generate technological knowledge abroad
and to engage in international R&D activities than
North American or Western European ones. The
forward projection for the year 2001 from the point of
view of the companies investigated indicates that the
internationalisation of R&D proceeds.
The Future of Key Research Actors in the European Research Area
Other empirical studies confirm the findings
of our survey among 209 technology-intensive
MNEs and point out the growing role of longterm research conducted abroad and the
increasing responsibility of foreign R&D labs to
generate and maintain core technologies (see
Florida 1997, Kuemmerle 1997, US National
Academy of Engineering 1996, OECD 1997). In
this sense, foreign R&D investment is more and
more a strategy to maintain and gain competitive
advantage by generating new technological
assets and capabilities and increasingly reflects
a technology-oriented posture as opposed
to simply supporting offshore markets and
manufacturing or adapting products to the local
requirements.
150
An in-depth study among multinationals shows that,
when deciding to establish or expand R&D abroad,
firms are motivated by the wish to gain access to
highly sophisticated resources which cannot be
found anywhere else, and to learn about specific
customer requirements, market and production
constellations on the spot. Multinational firms give
particular emphasis to the following motives for
internationalisation of R&D (see Gerybadze, MeyerKrahmer, Reger 1997):
• Access to leading research results and talents;
• On the spot presence, learning in lead markets
and adaptation to sophisticated customer
needs;
• Initiation and strengthening of R&D at locations
where the effects of greatest usefulness can be
expected and the highest cash flow generated;
• Monitoring and taking advantage of regulations
and technical standardisation;
• Supporting production and sales on-the-spot by
local R&D capacities.
This study also points out that highly
internationalised firms are no longer satisfied
with locations that will enable them to ‘just about
keep up’ with the technology race, but deliberately
search for the unique centres of excellence (see
Gerybadze, Meyer-Krahmer, Reger 1997). Other,
less advanced business processes and functions,
by contrast, are increasingly outsourced to
the second- and third-tier locations. Large
multinational corporations are thus restructuring
their portfolio of activities, and they concentrate
their most strategic and prestigious projects at
a few leading-edge locations. They are incurring
high costs for the scanning, evaluation and
selection of the most sophisticated centres of
competence, for the building-up of networks and
for the coordination of tasks with other groups
and locations.
The share of foreign affiliates in business R&D has
increased from 1995 to 2003 in many countries
(see Figure 3.7, and appendix 8.1). The World
Investment Report (UNCTAD 2005) concludes
that developed countries remain the main host
locations of foreign R&D activities by MNE,
however, there is a clear trend towards locating
more R&D activities in developing economies.
This is confirmed by available national statistics
as well as by corporate surveys and case studies.
The kind of R&D being undertaken by MNEs in
developing countries is also changing. While
it has traditionally involved mainly product
or process adaptation to meet local market
demands, recent developments suggest that
some developing economies and markets are
emerging as key nodes in the global R&D systems
of MNEs. A really prominent role here is played by
China, with its R&D-related FDI inflow boom: the
accumulated R&D investment of MNEs in China
had reached approximately USD4 billion by June
2004 (estimated by the Ministry of Commerce),
while the number of foreign-affiliate R&D centres
reached 700 by the end of 2004 (see UNCTAD
2005, 140-143). A similar development can be
observed in India. At the same time, the extent to
which developing countries participate in these
systems varies considerably, and large parts of
the developing world remain de-linked.
Figure 3.7
Trends in R&D spending by foreign affiliates,
selected economies, 1995-2003 (in per cent)
Share of foreign affiliates in business R&D, selected
countries, 2003 or latest year available
72.1
62.5
59.8
47.9
46.6
45.3
45.0
41.1
34.8
33.0
32.5
30.9
28.1
27.3
24.7
23.7
23.2
22.1
20.7
19.4
19.1
19.0
15.9
15.0
14.1
10.6
4.5
3.6
3.4
3.4
1.6
Case study research in European and Japanese
multinationals shows that changes in the overall
organisation of the corporation frequently have
a very strong impact on the R&D organisation
(see Reger 1997): corporations which are highly
diversified and in a process of decentralisation tend
to decentralise their R&D to a greater extent as
well (examples for this are ABB, Philips, Siemens).
In contrast, corporations which are in a process
of more centralisation (as a consequence of overdecentralisation) tend to centralise their R&D
organisation (an example here is Hitachi).
In general, there seems to be a shift from the
centralisation of R&D towards decentralisation of
R&D since the 1980s (see Edler, Meyer-Krahmer,
Reger 2002, Reger 1997). These changes include the
following aspects:
• A move of control/responsibility over R&D budget
and programs from the corporate level to the
divisions and business units;
151
• An increase of R&D budgets allocated to, and R&D
activities performed at, the divisional/business
unit level;
Change over 1995
Hungary
Czech Republic
Sweden
United Kingdom
Slovakia
Israel
Portugal (1999)
Australia
Germany
Argentina (1996)
Poland (1997)
China (1998)
Ireland
Canada
Average
Netherlands (1997)
Mexico
France
Singapore
Japan
India
Korea, Rep. of
Finland
United States
Greece
Brazil (2000)
Spain
Turkey (1997)
Chile
Thailand (2003)
Italy (2001)
• Linking corporate research through a high share
of contract research (up to 90 per cent of the
budget of corporate research) to the needs of the
business units;
40.7
25.8
26.0
15.4
15.1
14.0
13.0
10.8
9.1
8.9
8.8
5.7
5.4
5.1
4.8
4.4
3.2
2.3
2.2
2.0
1.8
1.3
1.0
0.6
0.8
-0.1
• Liquidating corporate research labs and full
decentralisation of R&D activities towards the
responsibility of the divisions or business groups
or complete integration (of parts) of corporate
research into the strongest division.
-2.7
-4.2
-10.5
0
0
Source: UNCTAD 2005, 127; UNCTAD’s own calculations based on national sources and data
provided from the OECD AFA database.
Note: In Argentina, Chile, Israel, South Korea and Mexico, the R&D expenditure of US-owned
affiliates has been used as a proxy for the R&D spending of all foreign affiliates. In India, the
share of foreign affiliates in total R&D spending has been used as a proxy for their share in
business R&D spending.
Obviously, there are regional differences between firms.
Roberts (1995) reports from his global survey that US
companies are more diversified, and are therefore
more decentralised, than comparable European or
Japanese companies. However, the major companies in
the US have been moving even more strongly towards
R&D decentralisation. In contrast, the same pattern of
organisational change does not occur in European or
Japanese firms to the same extent.
The outcomes of the trend towards more R&D
decentralisation are twofold. On the one hand, a shift
to decentralise R&D increases the responsiveness
to customers, the market-orientation of R&D and
the ability to implement changes in current product
Wo rki ng Paper 8
Multinational Enterprises
Ireland
Hungary
Singapore
Brazil
Czech Republic
Sweden
United Kingdom
Australia (1999)
Canada
Italy (2001)
Mexico (2001)
Portugal (2001)
Thailand
Spain
Netherlands (2001)
China
Argentina (2002)
Germany (2001)
Israel (2001)
France (2002)
Poland
Slovakia
Average (2002)
Finland (2002)
United States (2002)
Turkey (2000)
Greece (1999)
Chile (2002)
India (1999)
Japan (2001)
Korea, Rep. of (2002)
3.1.6 C
hanges in the Organisation of R&D
Activities
The Future of Key Research Actors in the European Research Area
lines; firms are more competitive in short-term
performance. On the other hand, a stronger business
unit-controlled R&D hampers long-term investments
in R&D, builds up organisational barriers and stops
the creation of new core strengths; the long-term
competitiveness of the company may erode.
3.2 Generalised Models of Changes
A valuable summary of the changes in the
management of R&D and technology is given in
generalised models which are based on empirical
observations or the perceptions of the innovation
process in the literature and describe the main
changes over time. These models were developed
in the beginning of the 1990s and 2000. Three of
them will be presented here which explicitly analyse
multinational enterprises.
3.2.1 Three Paradigms Scenario for the
Organisation of R&D
152
The model of ‘Three Paradigms Scenario for the
Organisation of R&D’ was developed by Coombs and
Richards (1993). The authors identified two traditional
paradigms of R&D organisation. The characteristics
of paradigm 1 (1950-70) are the centralisation and
corporate dominance in the funding, ownership,
and control of R&D. Management thinking was
dominated by a technology-push focus and R&D
spending grew. Paradigm 2 (from 1970 till the late
1980s) can be characterised by decentralisation
and business unit dominance in R&D. Management
philosophy and practice moved towards a market
focus and ‘market-driven R&D’.
However, and this is the main thesis of the authors,
the shift towards the decentralisation of R&D has a
number of negative consequences. Firstly, business
unit ownership of R&D is very effective at consolidating
strength within an existing technological regime but
turns into a severe disadvantage if this technological
regime loses competitiveness. Secondly, if
new technologies emerge and destroy existing
competencies of the business unit, decentralised
R&D is too short-term oriented and may not be able
to cope with this change.
The negative development of paradigm 2, the increasing
scale and the global character of many R&D actors and
the completion of the institutional learning process of
companies are seen as decisive challenges for today’s
R&D management. As an answer to this, a new pattern of
R&D management is identified and visible so far only in
some firms. Paradigm 3 tries to combine market-driven
benefits from decentralised, business-funded R&D, with
technology-push benefits from a long-term oriented,
centralised R&D at the corporate level. Companies
with this R&D organisation have mixed corporate and
business-unit funding for R&D, with attention given to a
subtle balance of incentives.
3.2.2 Third Generation R&D
The model of the ‘Third Generation R&D’ is created
on the empirical observation of the management
of R&D in multinational enterprises by Roussel,
Saad and Erickson (1991). The ‘first generation R&D
management’ occurs up to the mid 1960s and can
be characterised by a lack of a long-term strategic
framework for the management of R&D (see Figure
3.8). There is no explicit link between business and
technology/R&D strategy. R&D is treated as an
overhead cost and a line item in the general manager’s
budget. Corporate management participates little in
defining R&D programmes or projects, the results of
R&D are rarely evaluated. Typically for this generation,
R&D is organised into cost centres. R&D activities
are centralised and concentrated at the corporate
level, whereas incremental R&D is conducted by the
business units. The main characteristic of this first
R&D management generation is the lack of linkage
between R&D and the corporation as well as the
centralised R&D activities on corporate level.
The ‘second generation of R&D management’ is a
transition stage towards the third generation and is
the beginning of a strategic framework for R&D and
the stronger linkage between business and R&D
management. A supplier/customer relationship
is established between R&D as supplier and the
various businesses as customers. Fundamental R&D
is centralised on corporate level and incremental
R&D is distributed to the business units. Matrix
and project management are actively used. Project
managers get more responsibility. However, since
plans for R&D are formulated on a project-byproject basis, separately and independently for each
business unit and the corporation, there is a lack of
integration between R&D and business strategy.
The ‘third generation R&D management’ in
the 1990s seeks to balance the R&D portfolio
strategically across the whole corporation. General
and R&D managers jointly assess and decide upon
the aims, the strategy, the content and the budget
of R&D. Technology/R&D strategies are integrated
into business strategies worldwide. Targets of
R&D are selected by setting fundamental research
in a business context and funds are allocated
according to the short-, medium- and long-term
needs of the business units and the corporation.
Figure 3.8
First and Second Generation R&D
Management
Figure 3.9
Third and Fourth Generation R&D
Management
Third Generation R&D Management:
Strategic and Purposeful
Management and
strategic context
Philosophy
First Generation R&D Management:
the Intuitive Mode
Organisation
• no long-term strategic framework
Management and • R&D is an overhead cost
strategic context • m
inimum of evaluation of R&D results
• management of R&D inputs
Technology/
R&D Strategy
Philosophy
Organisation
Technology/
R&D Strategy
• R&D decides future technologies
• business decides current technology objective
• R&D is organised into cost centres
and disciplines
• Centralised R&D on corporate level
• avoidance of matrix structure
• transition state between 1st and 3rd generation
Management and • partial strategic framework
strategic context • i mprovement of communication between business
and R&D management
Philosophy
Philosophy
Strategy
Organisation
• judge-advocate management/R&D relationship
• establishing a customer/supplier relationship
between business and R&D activities
Organisation
• centralised and decentralised R&D activities
• matrix management of project
• increasing responsibility of project manager
Technology/
R&D Strategy
• Strategic framework by project
• R&D not integrated business- or corporate wide
• R&D plans are formulated on a project-byproject
basis
Source: see Edler, Meyer-Krahmer, Reger 2002.
3.2.3 Fourth Generation R&D
However, the two models above do not tackle the
extent and challenges of the internationalisation
of technology-related activities. Furthermore, since
the described models draw their conclusions from
the results made at the beginning of the 1990s, we
could conduct our own survey among the top R&D
spending companies worldwide (209 MNEs from North
America, Western Europe and Japan) which gives us
the opportunity to analyse empirically the strategic
management of technology of large multinational
firms in the late 1990s (see Edler, Meyer-Krahmer,
Reger 2002). Based on our empirical analysis,
cornerstones of a fourth generation R&D management
can be developed which focus on the management
issues philosophy, strategy, organisation, and resource
allocation (see Figure 3.9).
• strategic and operational partnership between R&D
and other functions
• coordination of central and decentral R&D
• breaking the isolation of R&D
• full responsibility of project managers
• exploitation of synergies
• technology/R&D and business strategies integrated
worldwide
• selecting targets by setting fundamental research in
business context
Fourth Generation R&D Management
• No explicit link to business strategy
• technology first, business implications later
Second Generation R&D Management:
the Systematic Mode
• strategically balanced R&D portfolio across the
corporation (holistic strategic framework)
• long-term vision
Resource
Allocation
• R&D and technology regarded as strategic
instruments
• research and development is located there where
the value is created
• tapping into the ‘pocket of innovation‘ worldwide
• increasing productivity of R&D
• explicited formulated corporate technology strategy
• corporate technology is highly integrated into the
corporate and business unit strategy via members
of the top management as linking pins
• coordination of central and decentral R&D
• locating research to the place of needs
• fully integrating the various elements of the value
chain
• establishing and coordinating centres of excellence
with their own responsibilities/competencies
worldwide
• horizontal and vertical networking with external
partners even in core technologies
• shared corporate and business unit ownership of
R&D portfolio and resources
• more emphasis on technology foresight activities
to keep abreast with newest technology and setting
the research agenda
Source: see Edler, Meyer-Krahmer, Reger 2002.
The philosophy regards R&D and technology as a
very important strategic instrument for long-term
competitiveness. R&D should be located where the
value is created and used to tap into the ‘pockets of
innovation’ worldwide. Productivity of R&D should
be increased by using different instruments.
Regarding strategy issues, the corporate-technology
strategy is formulated explicitly and highly
integrated into the corporate and business-unit
strategy. Linking pins and the strategic key persons
are the CEO, CTO, Vice President R&D, and the
General Manager of the specific business unit.
Obviously, there is a need for strong co-ordination of
central and de-centralised R&D activities regarding
organisational issues. Research should be located
at the location of the needs. The various elements
of the value chain should be integrated. The R&D
153
Wo rki ng Paper 8
Multinational Enterprises
Centralised and decentralised R&D is co-ordinated
by matrix organisation, the intensive use of project
management and making the project manager fully
responsible for the R&D project. There is a resourceallocation principle for a strategic balancing between
radical and incremental R&D activities.
The Future of Key Research Actors in the European Research Area
organisation of a multidivisional company in the
future will be worldwide. Centres of excellence
with their own responsibilities and competencies
worldwide are established and coordinated as a
‘portfolio of opportunities’. Technology-related
horizontal and vertical networking with external
partners is performed even in core-technology areas
of the company.
Figure 4.1
Development of scenarios – from key factors to
future spaces
A
154
By developing ‘generations of R&D’, major changes
in the R&D management of multinational enterprises
over time are observed (e.g. the approach of Coombs
and Richards 1993, and Roussel, Saad, Erickson 1991).
However, this approach clearly has its limits because
a company’s strategy or behaviour is not linked to
a specific situation, as is done, for example, in the
contingency theory. Furthermore, various generations
exist beneath each other. This is the reason why in
contrast to other authors it is not assumed here that
the generations of R&D built upon each other, instead,
the various generations co-exist at the same time.
I
D
Subject
Regarding resource allocation, corporate and
business unit ownership of R&D portfolio and
resources is shared. More emphasis on technology
foresight activities is necessary to keep abreast with
the newest technology and setting the research
agenda, i.e. to know what to do (project selection
and prioritisation) will become more important.
B
C
SF
A
SF
II
B
C
Key Factors
What are the
driving forces
in the scenario
field?
IV
Future
Projections
How may the key
factors develop
in the future?
III
Scenarios
Future Spaces
Which possible
future scenarios
are imaginable?
How are the
different
scenarios
inter-linked?
Conclusions?
4.1 I nfluence Analysis and the
Identification of Key Factors
4. Driving Forces for
Change and Future
Trends
First, all areas of influence which affect the knowledge
production of MNEs in the European Research Area have
to be identified. The aim is to identify external areas
and influence factors as well as their interrelationship
and the system dynamics in a stepwise process.
With the help of the central question ‘On which areas
depend the knowledge production by MNEs in the
European Research Area?’ in a free brainstorming and
discussion process, we defined the relevant areas of
influence. Second, we identified, as areas of influence,
several influence factors and created a differentiated
system. Based on this process, we identified the
five influence areas knowledge, market/economy,
technology, competition/regulation and MNEs inside
and the including 23 influence factors (see Figure 4.2).
After the analysis of trends and future changes in
the way of knowledge production by MNEs and
the relative role of MNEs in knowledge production
in the European Research Area, the next step is
the detection and identification of key factors. Key
factors are driving forces for change and future trends
in the field of investigation. For all key factors, future
projections show how these factors may develop in
the future until 2020. The future projections are the
basics for the scenario development and the creation
of future spaces (supported by a cluster analysis).
The developed scenarios describe future spaces,
which are several, possible images of a future
situation and provide a basis for conclusions and
recommendations. The scenario development steps
from key factors to future spaces are illustrated in
Figure 4.1.
All these factors contribute to the knowledge production
of MNEs in the European Research Area. The next step
is to identify the interrelationship, the system dynamics
and as a consequence the key factors. For that purpose
we used the instrument ‘influence analysis’ (see
Figure 4.3). At first we discussed the influences between
all factors with the help of a matrix. The question we
discussed is how factor A influences factor B. The
strength of the influence was measured with the help
of a rating form 0 (no influence) to 3 (strong, immediate
influence). We tried to find out the importance of
several factors in order to investigate their ability to
act as a key influence factor in the process of scenario
development. With help of the matrix we considered
only direct influences among the factors. Additionally
we used a scenario software tool in order to consider
indirect influences between the factors as well.
Figure 4.2
Development of scenarios – from key factors to future spaces
Knowledge
1. Speed of knowledge production
2. Novelty of knowledge production
3. Costs of knowledge production
4. Property of knowledge production (IPR)
5. Globalisation of knowledge production
6. Efficiency of knowledge production
7. Complexity of knowledge production
8. Investment in knowledge production
Technology
14.Technological competencies of public R&D system
15.Technological competencies of high-tech SME
16. Technological competencies of MNE
Market/ Economy
9. Attractiveness of foreign markets
10. Change of the population
11. Change of the age pyramid
12. Economic development
13. Change of values
MNE Inside
20. Corporate Governance
21. Organisation of R&D activities
22. Customer orientation
23. Innovation in company strategy
Competition/ Regulation
17. Industrial structure
18. Competition
19. Regulations and policy interventions at EU level
Figure 4.3
Influence matrix
Wo rki ng Paper 8
Multinational Enterprises
155
The Future of Key Research Actors in the European Research Area
The interpretation of the influence analysis is carried
out by a so-called system grid. In general four
different kinds of factors can be distinguished within
the system grid (see Figure 4.4):
• Indicators: All factors located in the field below
right have relatively high passivity but low activity;
• Independent factors: All factors located in the
field below left have relatively low passivity and
relatively low activity;
• Active driving forces: The factors located in the
top left field have a relatively strong influence on
the other areas but are little influenced by other
factors;
• Dynamic system knots: The factors located in the
top right field are characterised by high activity
and high passivity; they influence very much other
factors and are influenced by other ones as well.
• active driving forces which are not influenced by
other ones (e.g. (11) change of the age pyramid or
(20) corporate governance);
• dynamic system knots which influence other factors
and are influenced by others (e.g. (18) competition
or (2) novelty of knowledge production).
For the interpretation of the system grid and the
selection of our ten key influence factors, several
criteria can be taken into account. The criteria we
used for the extract of key influence factors are
presented in Figure 4.6.
Figure 4.5
System Grid: MNEs and knowledge production
in the European Research Area
Figure 4.4
General interpretation of system grid
ACTIVE
DRIVING
FORCES
DYNAMIC
SYSTEM
KNOTS
INDEPENDANT
FACTOR
INDICATORS
Active Sum
156
Passive Sum
The 23 influence factors were evaluated in the
influence matrix and an active and passive sum for
each influence factor was calculated. The result of
this process is the creation of the system grid. Figure
4.5 shows the location of our 23 influence factors.
With the help of the system grid all factors can be
characterised, for example, as:
• indicators which are influenced very much but do
not have a strong influence on other factors (e.g. (6)
efficiency or (3) costs of knowledge production);
• independent factors which have no strong
influence and are not influenced by other factors
(e.g. (22) customer orientation);
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
Influence Factors
Speed of knowledge production
Novelty of knowledge production
Costs of knowledge production
Property of knowledge production (IPR)
Globalisation of knowledge production
Efficiency of knowledge production
Complexity of knowledge production
Investment in knowledge production
Attractiveness of foreign markets
Change of the population
Change of the age pyramid
Economic development
Change of values
Technological competencies of public R&D system
Technological competencies of high-tech SME
Technological competencies of MNE
Industrial structure
Competition
Regulations and policy interventions at EU level
Corporate Governance
Organisation of R&D activities
Customer orientation
Innovation in company strategy
Figure 4.6
Interpretation of the system grid with help of
various criteria
Criteria
Active sum
Description
Active total = Sum of one line in the matrix
(see Figure 4.3)
How does one factor influence all the other
factors?
Passive sum
Passive total = sum of column in the matrix
(see Figure 4.3)
How strongly is one factor influenced by all
the other factors?
Direct dynamic index (DI) Active sum x passive sum
DI shows the influence of one factor on the
whole system
High DI = strong cross-linked in the system
Direct impulse index
Active sum/ passive sum
Direct impulse index shows the influence
caused by one factor without any change of
that factor by other factors:
high ratio = impulse factors
low ratio = reactive factors
Based on the direct dynamic index (active sum
x passive sum) we calculated the following ten
factors:
7.Innovation in company strategy;
8.Property of knowledge production (IPR);
9.Regulations and policy interventions at the EU
level;
10.Technological competencies of public R&D
system.
Our final selection of the ten key factors is based on
several aspects. First, we chose very active factors
and second, factors which properly describe the
knowledge production by MNEs and their relative
role for knowledge production in the European
Research Area. Third, we wanted to take into
account the feedback and discussion from the
second meeting of the expert group in Brussels on
September 20-1, 2005. Following these aspects, we
decided to develop our scenarios with these ten key
influence factors (for a detailed description of each
factor see appendix 8.2):
1.Competition;
1.Competition;
2.Complexity of knowledge production;
2.Economic development;
157
3.Globalisation of knowledge production;
4.Globalisation of knowledge production;
4.Innovation in company strategy;
5.Industrial structure;
5.Investment in knowledge production;
6.Innovation in company strategy;
6.Novelty of knowledge production;
7.Investment in knowledge production;
7.Technological competencies of MNE;
8.Novelty of knowledge production;
8.Change of the population;
9.Speed of knowledge production;
9.Change of values;
10.Technological competencies of MNEs.
10.Regulations and policy interventions at EU level.
Based in the indirect impulse index (active sum/
passive sum) we calculated the following ten factors:
1.Attractiveness of foreign markets;
2.Change of the age pyramid;
3.Change of the population;
4.Change of values;
5.Corporate Governance;
6.Customer orientation;
4.2 Alternative Projections
After the definition of key influence factors, we
anticipated the future of the key factors and
created alternatives for the development of each
factor. The development of projections is based on
a literature review, discussions with experts and
our own perceptions. An overview of the ten key
influence factors and the several projections are
depicted in Figure 4.7. The full description of all
projections and the ideas and assumptions behind
the projections are included in the appendix (see
appendix 8.2).
Wo rki ng Paper 8
Multinational Enterprises
3.Economic development;
The Future of Key Research Actors in the European Research Area
Figure 4.7
Projections of the ten key influence factors
Key influence factor
Projection
Competition
hyper-competition
cooperation
co-opetition
monopolies
Economic development
(see Becker-Boost, Fiala 2001, Dent 1998)
The long boom
Zero growth
Ups and downs
Mega recession
Globalisation of knowledge production
(see Gerybadze, Reger 1999)
Centres of excellent innovation abroad (CoEI)
Home-based innovation
Export innovation
Import innovation
Innovation in company strategy
4.3 Clustering Alternatives – Consistency
Analysis
The aim of the consistency analysis is to assemble
all alternatives according to their consistency and
to form logical and plausible future scenarios and
to select the most contrasting ones for evaluation
(see von Reibnitz 1999 5/16). To achieve plausible
and reliable scenarios, we examined the consistency
of all possible combinations of projections with the
help of a consistency matrix (see Figure 4.8 and
appendix 8.3). For the assessment of the consistency
we used the following valuation key:
• 1 = Total inconsistency: both projections exclude
each other absolutely, they do not occur together
in one plausible and reliable scenario.
• 2 = Partial inconsistency: both projections are
inconsistent with one another; the occurrence
of both projections in a scenario would not be
plausible.
Innovation-dominated strategy
Innovation by chance
Innovation-rejection strategy
158
Investment in knowledge production
Dramatic increase
Stagnation
Dramatic decline
Handpicked investment
Novelty of knowledge production
(see Hauschildt 1997)
Radical innovation
Incremental innovation
Technology-based innovation
Application-based innovation
Technological competencies of MNE
Completely outsourced
Closed innovation
Open innovation: outside-in process
Open innovation: inside-out process
Change of the population
Growth of the population outside European
countries
Emigration of nations to Europe
Emigration of Europeans
Change of values
(see Siemens AG 2004)
Society of Modesty
Fuzzy Society
Regulations and policy interventions at the EU level
Policy of Balance
Policy of Over-Regulation
MNE-dominated Policy
Laissez-Faire Policy
• 3 = Neutral: both projections do not influence
each other and the occurrence of both projections
in a scenario will not influence the plausibility of
a scenario.
• 4 = Consistency: both projections can occur
together in a scenario.
• 5 = Very high consistency: if one projection
occurs in a scenario, the other projection will
become part of the scenario, too.
The calculation of the scenarios is delivered by a
cluster analysis which is supported by special scenario
software. The number of scenarios is not defined
at the outset. Figure 4.9 shows the so-called scree
diagram, which is based on the cluster analysis. The
scree diagram shows the expected information deficit
according to the number of scenarios. The more
scenarios we chose the deficit of information becomes
smaller. On that stage of the scenario development
process, we had to find a compromise between an
information deficit and the aim to develop clear,
definable scenarios. On the one hand, a high number of
scenarios enable a more detailed view over the future
space. On the other hand, it is very useful for planers
and decision-makers to work with a small number of
scenarios because this improves the communication
and further processing with the scenarios. We decided
to develop four scenarios because the information
deficit between scenario four and five is fairly small
(see Figure 4.9). The consideration of five scenarios
would not bring out more benefit than four scenarios
according to the scree diagram. This correlation is
pictured as an inflexion point in Figure 4.9.
Additionally, it is helpful to visualise the correlations
between several scenarios with the help of future-space
mapping. Very similar scenarios would be presented
very close to each other; very different scenarios would
be presented far away from each other. The respective
scenarios are illustrated with help of different colours
(see Figure 4.10). Scenario one (‘The Long Boom’) is
illustrated as a red bundle, scenario two (‘Ups and
Downs’) is coloured in yellow, while scenario three
(‘Handpicked Innovation’) is pictured as a black
bundle and scenario four (‘Zero Growth’) as a blue
bundle. Figure 4.10 makes obvious that scenario one
and three are very far away from each other, which lead
to the conclusion that these scenarios describe very
different and definable future spaces. With the help of
the 3D future-space mapping, scenarios are presented
in a three dimensioned space (see Figure 4.11). The 3D
scenario presentation shows that all four scenarios
– even scenario one (red) and two (yellow) – are very
different from each other because of their positioning
in the future space.
Figure 4.8
Consistency matrix (cutout) – MNEs and knowledge production in the European Research Area
Wo rki ng Paper 8
Multinational Enterprises
159
Figure 4.9
Figure 4.10
Scree Diagram – scenario overview
2D Future space mapping
10
9
Scenario 4
Scenario 1
8
Relative error
7
6
5
4
3
2
Scenario 3
1
0
1
2
3
4
5
6
7
Number of rough scenarios
8
9
10
Scenario 2
The Future of Key Research Actors in the European Research Area
excellent innovation (CoEI) abroad also occur in
this scenario but do not play a prominent role. The
CoEIs are globally linked amongst each other, which
enables transfer of technological competencies. The
CoEIs of MNEs in Europe participate and benefit
from this process.
Figure 4.11
3D Future space mapping
Scenario 4
Scenario 1
Scenario 3
Scenario 2
160
5. Scenarios on the
Knowledge Production
of Multinational
Enterprises
As a result of the cluster analysis we received
– supported by the scenario software – bounds of
projections, which are very high consistent ones.
The list of consistent projections for each scenario is
presented more in detail in the appendix 8.4 to 8.7.
Based on these lists we developed four scenarios
– ‘The Long Boom’, ‘Ups and Downs’, ‘Handpicked
Innovation’, and ‘Zero Growth’ – which are described
in detail in this chapter.
5.1 Scenario 1: 2020 – The Long Boom
Influence Area Knowledge
If we look forward until 2020, what might drive a
long economic boom? Richard Lipsey – an economist
at Simon Fraser University – notes that economists
distinguish three main sources of growth: increases
in the size of market, capital investment and
technical change. Our ‘The Long Boom’ scenario is
especially characterised by a dramatic increase in
investment in knowledge production which results
in new technologies. The globalisation of knowledge
production is dominated by generating innovation
inside Europe and exporting innovation from the
European Union to other countries. Centres of
Influence Area Market/Economy
The economic development is characterised by
a long economic boom. Companies create new
products and services and new industries emerge.
Already beginning in the first decade of the century,
information technology was transforming the
economy and every other area of technology that it
touched, from genomics to mass customisation in
manufacturing. The investment in knowledge leads
to many lines of development within the technology
revolution. The technology revolution makes
possible, for example, the breakthrough to molecular
nanotechnology, self-replicating molecular-scale
‘assemblers’ able to build other ultra-thin nanomachines and to assemble larger objects.
While Europe is characterised by a ‘Long Boom’
economy, the population in Europe remains stable
or grows through the immigration of people to
Europe. The change of values is characterised by
the so-called ‘Fuzzy Society’. The beat of life has
become faster in a fuzzy society. Societal institutions
like partnerships, networks, groups of interest or
working teams change faster and faster and are no
longer long-term constants in the individual life.
Even partner and working relationships do not last
a lifetime. Life is full of risks, personal behaviour is
spontaneous and not planned. Society is dominated
by individuality, each single creates his or her own
personal network and has to define his or her own
values. Society falls apart into ‘rich’ and ‘poor’,
‘performance-oriented’
and
‘leisure-oriented’
individuals. Society is divided into locally-linked and
thinking people and a global elite, which is at home
in every place in the world, representing a joint
worldwide culture.
Influence Area Technology
MNEs built up their technological competencies
by open innovation, especially outside-in
processes. They enrich their own knowledge base
through the integration of suppliers, customers,
universities, R&D institutes and high-tech SMEs.
The high competencies of the public R&D system
and high-tech SMEs are necessary for this openinnovation model, providing external technological
competencies.
Hyper competition characterises the competitive
environment in that ‘Long Boom’ scenario. All actors
are relatively independent from the various directions
of state regulations and policy interventions at the
EU level. Obviously regulations and interventions
do not have a high importance in this scenario. The
option of a so-called ‘Policy of Balance’ is the most
probable one. That policy method is a policy with
adequate forms of EU regulations and modest policy
intervention at the EU level.
Influence Area MNEs Inside
Innovation has an extremely high relevance and
is completely linked to companies’ strategies.
Companies can be best describes as ‘innovation
machines’, the company culture and climate can be
indicated as modern, very creative and open to the
future.
5.2 Scenario 2: 2020 – Ups and Downs
Influence Area Knowledge
The production of knowledge is globalised, mainly
through centres of excellent innovation abroad
(CoEIs). Technological knowledge and innovation
are generated in these CoEIs and distributed around
the globe, only some of the CoEIs are still located in
Europe. The investment in knowledge production
stagnates. Radical innovations dominate the novelty
of knowledge production and – if successful – cause
a dramatic upswing of the economy and – if not
successful – causes a dramatic economic downswing.
Market/Economy
Economic development is characterised by ups
and downs. Europe is faced by a slowdown of the
population, which is another factor causing the
ups and downs of the economy. The working-age
population has fallen in European countries, like
Italy and Germany. On the other hand the population
outside European countries continues to grow. The
largest gains in population are projected to be in SubSaharan Africa and the Near East. In these regions,
many countries are expected to more than double in
size, with some more than tripling. More moderate
gains are expected for North Africa, North and South
America, Asia and the Pacific. On the opposite end of
the spectrum, a majority of countries in Europe and
the Newly Independent States of the former Soviet
Union are expected to experience a decline in their
populations.
The change of values is characterised like in
scenario 1 by the so-called ‘Fuzzy Society’. The
beat of life has become faster in this society.
Societal institutions like partnerships, networks,
groups of interest or working teams change
faster and faster and are no longer long-term
constants in the individual’s life. Even partner and
working relationships do not last a lifetime. Life
is full of risks, personal behaviour is spontaneous
and not planned. Society is dominated by
individuality, each single creates his or her own
personal network and has to define his/her own
values. Society falls apart into ‘rich’ and ‘poor’,
‘performance-oriented’ and ‘leisure-oriented’
individuals. Society is divided into locally-linked
and thinking people and a global elite, which is at
home in every place in the world, representing a
joint worldwide culture.
Influence Area Technology
Multinational enterprises built up their technological
competencies through open innovation, especially
based on outside-in processes. MNEs enrich their
own knowledge base through the integration of
suppliers, customers, universities, R&D institutes
and high-tech SMEs.
Influence Area Competition/ Regulation
Competition is dominated by co-opetition.
Companies compete in some areas but cooperate
in other areas. Co-opetition means situational
opportunism as a strategic option, cooperation as a
temporally-framed alliance; cooperative competition
and competitive cooperation, and the building up of
‘corporate spheres of influence’.
The actors in this scenario are relatively independent
from the various directions of state regulations
and policy interventions at the EU level. Due to
the fact that the innovation is generated mainly
outside European countries, the influence of policy
interventions at the EU level is limited. Obviously
regulations and interventions do not have a lot
of importance in this scenario. Both, the ‘MNEdominated Policy’ or the ‘Laissez-Faire Policy’ seem
to be probable options. In an ‘MNE-dominated
Policy’, MNEs dominate EU-regulation decisions,
and the EU only sets frame conditions. In a ‘LaissezFaire Policy’ the inefficiency of the market and even
the economy will be best solved without an active
role of the EU. There is no active intervention but
a great trust in the self-regulation potential of all
actors. Both ways of policy intervention are possible
and plausible in an ‘ups and downs’ scenario.
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Influence Area Competition/Regulation
The Future of Key Research Actors in the European Research Area
Influence Area MNEs Inside
Innovation dominates the companies’ strategies and
has an extreme high relevance – but not continuously
so, which reinforces the ups and downs of the
economy. The innovation approach seems not to be
fully transferred into MNE business activities.
5.3 Scenario 3:
2020 – Handpicked Innovation
Influence Area Knowledge
Import of innovation is the dominant mode of the
globalisation of knowledge production. Innovation
is mainly generated outside the European Union
and imported from non-European countries. Leading
innovation-generating and exporting countries are
China, India, South Korea, and Brazil.
162
developed their own research system and excellent
technological competencies in a dramatic catchup process during the last fifteen years. From a
technological and market view, it is much more
interesting to generate high-tech innovations in
these fast growing and developed countries and
to import innovations to Europe.
The change of values forward to a so-called ‘Fuzzy
Society’ is characteristic but not so prevailing
compared with scenario 1 and 2. Since economic
growth is limited, some groups in the society try to
learn to live with this. For these groups, strong values
are a high level of equity to ensure social peace,
political stability, health, and jobs. In scenario 3, the
‘Society of Modesty’ appears together with the ‘Fuzzy
Society’. However, the latter clearly predominates
because the downs in the economy cyclically cause
heavy social crises.
The MNEs in Europe favour only handpicked
investment in knowledge production and random
innovation. The bulk of R&D investment is
performed abroad in countries where excellent
technologies are provided and which can be
considered as lead markets. The innovation
is mainly application-based and incremental,
innovations with low risk are preferred and
existing products are only improved. Technology
plays a minor role for innovation, the degree of
technological novelty is very low.
Influence Area Technology
Market/Economy
Influence Area Competition/Regulation
Ups and downs are characteristic for the economic
development in this scenario. The population
outside European countries grow which has
severe consequences for European demand and
the economy. The largest gains in population
are projected to be in Sub-Saharan Africa and
the Near East. In these regions, many countries
are expected to more than double in size, with
some more than tripling. More moderate gains
are expected for North Africa, North and South
America, Asia and the Pacific. On the opposite
end of the spectrum, the majority of countries in
Europe and the Newly Independent States of the
former Soviet Union are expected to experience
a decline in their population. The shrinking
population and the lack of demand in Europe
leads to less and less innovation from the MNEs
in Europe. From an economic point of view, it is
no longer interesting to innovate, since markets
are small and decreasing in size. Markets abroad
in countries like China, India or Brazil are much
more promising. Further, these countries have
The competition is dominated by cooperation among
MNEs which try to ensure certain gains by verbal
agreements and cooperation. This partly suspends
competition in the European economy and makes
innovation in Europe unattractive.
The innovation process is open, which includes both,
outside-in and inside-out processes. MNEs enrich
their own knowledge base through the integration
of customers, universities, R&D institutes, and
high-tech SME. Since the generation of leading
technology seems to be less attractive, MNEs also
bring their ideas to the market; they sell intellectual
property rights (IPR) and multiply technology by
transferring ideas to the outside.
Two options for EU policy occur in this scenario.
The more prevailing one is the ‘Policy of Balance’
which tries to adjust the economic ups and downs.
There are adequate forms of EU regulations and
modest policy interventions of the European
Union. The second policy option is ‘Laissez-Faire’.
Inefficiencies of the market and economy seem to
be best solved without an active role of the EU.
There is no active intervention of the EU but great
trust is set in the self-regulation potential of all
economic actors.
Influence Area MNEs Inside
Innovation is not a permanent part of the company
strategy and is not at all linked to the company
5.4 Scenario 4: 2020 – Zero Growth
Influence Area Knowledge
The globalisation of knowledge production includes
firstly home-based innovation and secondly the
import of innovation. MNEs in Europe seem no
longer to aim for high competitiveness with their
innovations and just want to serve the European
markets. This is possible because of the strong
cooperation of the MNEs and networks of MNEs and
other companies in Europe among each other. Hightech innovations are mainly generated outside the
European Union and imported from non-European
countries.
There is only handpicked investment in knowledge
production; R&D expenditures are only spent for
selected innovation projects. This results in a
low degree of novelty and incremental innovation
as the dominant mode of innovation, existing
products are improved but no new ones are
created. Even application-oriented innovations
are regarded as irrelevant by MNEs in Europe in
this scenario.
Influence Area Market/Economy
Economic development is characterised by ‘Zero
Growth’ and long-term stagnation. The economic
ups and downs are eliminated; however, the
economy is not growing. Two societal options are
present in this scenario. The ‘Society of Modesty’
seems to be the most likely model. In that model
the society has become much more modest. The
society has to learn to live with zero growth of the
economy. Due to the lack of economic ups and
downs, the difference between ‘rich’ and ‘poor’ is
not very big, a high level of equity is aimed at to
ensure social peace, modest prosperity, health,
jobs and political stability. There is a deceleration
of the speed in private and working life. Working
hours have increased, however working intensity
has decreased. Society has become age-integrated
and realised the finiteness of life. Education, work
and leisure time are integrated into a work life
balance across all the age groups. The second
societal alternative is the ‘Fuzzy Society’, but
this is the less probable one. Through the lack of
upswings in the economy, it is difficult to become
very rich. Furthermore, the values and norms do
not promote individual wealth.
The emigration of people to Europe seems to be more
probable than the growth of the population outside
European countries in scenario four. An explanation
could be that living conditions in countries outside
the EU are worse and that the ‘Society of Modesty’
attracts immigrants.
Influence Area Technology
MNEs enrich their own knowledge base through
the integration of knowledge from customers,
universities, R&D institutes, and high-tech SMEs.
Since the generation of technology seems to be
less attractive, MNEs also bring their ideas to the
market, selling licences or patents and transferring
ideas to the outside. The stock of technological
knowledge within the MNEs is not renewed but
dismantled.
Influence Area Competition/Regulation
Competition in the European market is dominated
by cooperation among MNEs and networks of
MNEs and other companies. As in scenario 3, MNEs
in Europe try to ensure certain profits by mutual
agreements and arrangements. As a consequence,
this partly suspends competition in the European
economy and makes innovation in Europe
unattractive.
EU policy tries to treat the economic problems
and the pathway of the MNEs towards incremental
innovation by supporting MNEs and innovation
activities within MNE. In this scenario, the policy
option of the EU is the MNE-dominated policy. This
again leads more and more towards a limitation
of competition and a downward spiral to less
competitiveness amongst the MNEs in Europe and
less and incremental innovation activities.
Influence Area MNEs Inside
Similar to scenario 3, innovation is not a permanent
part of the company strategy and is not at all linked
to company strategy. This means that MNEs in
Europe consider continuous innovation as irrelevant.
Innovation only occurs by chance or not at all.
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Multinational Enterprises
strategy. This means that MNEs in Europe consider
continuous innovation as irrelevant. Innovation only
occurs by chance or not at all.
The Future of Key Research Actors in the European Research Area
6. Impact Analysis of the
Scenarios of MNEs on
the European Research
Area and the European
Knowledge Society
This chapter analyses the impact of the four
scenarios of MNEs on the European Research Area
and the European knowledge society.
6.1 ‘The Long Boom’ – Impact and Policy
Recommendations
164
Multinational enterprises (MNE) have a strong
focus on their innovation strategy in the ‘The Long
Boom’ scenario. The investment in innovation can be
characterised as dramatic. The internationalisation
strategy includes the export of innovation as well
as centres of excellent innovation abroad (CoEIs).
Furthermore technological competencies are
covered by an open innovation model. Under ‘The
Long Boom’ scenario the public R&D system is very
important and high-tech SMEs have a strong impact
on the European Research Area. These high-tech
SMEs are pushing technological innovation; they are
very competitive and the entrepreneurial spirit is the
basis and stimulus for technological innovation.
In ‘The Long Boom’ scenario, the EU policy may
follow a ‘Policy of Balance’ and find adequate forms
of regulations and intervene only in a modest way.
The policy intervention should be limited to ensure
the frame conditions for competition and a climate
for innovation and entrepreneurial spirit. Regarding
the public R&D system, technological competencies
are very important and should be continuously
built up and cultivated. High-tech SMEs and their
competencies should be heavily supported by the
European Union. Therefore the ‘Policy of Balance’
also means not privileging MNEs over the other
actors in the European Research Area. This type of
policy may try to find a balance between the different
actors and between globalisation and localisation.
internationalisation strategy are centres of excellent
innovation abroad (CoEIs) and an open innovation
model. The public R&D system is very important as a
competent partner for industry. High-tech SMEs have
developed good technological competencies and
are partners in the open innovation process as well.
However, due to the economic up-and-down-swings,
a cyclical ‘birth and death’ of high-tech SMEs arise.
We came to the conclusion that the influence of
policy regulations and even interventions at the
EU level seems to be fairly limited in this ‘Ups and
Downs’ scenario. One main task and challenge of
EU policy is to balance the economic cycle. A further
recommendation for EU policy is to try to increase
investment in knowledge production and to improve
the attractiveness of Europe as the best place for
foreign investment in innovation.
6.3 ‘ Handpicked Innovation’ – Impact and
Policy Recommendations
The ‘Handpicked Innovation’ scenario draws a
picture of a future situation in which MNEs generate
innovations only by chance. The strategy to make
only handpicked investment dominates in MNEs.
They generate innovation abroad and import
innovation to the European market. The innovation
is only application-based with a low degree of
technological novelty. MNEs are characterised by a
strong inside-orientation in the innovation process.
Due to the stronger focus of multinationals on
internal knowledge generation, the importance of
the public R&D system is lower. The same is true for
the importance of SMEs as technology generators
for multinational enterprises. High-tech SMEs are
only one possible option; MNEs prefer their internal
innovation activities.
The main opportunity for EU policy therefore seems
to be a ‘Policy of Balance’, which includes mainly two
tasks. Due to the economic ups and downs, which are
characteristic in this scenario, the EU policy needs to
balance the economic cycle. Another challenge for
EU policy is to establish a fruitful balance between
exports and imports of innovation, permanent and
accidental innovation activities, application- and
technology-oriented and radical innovation.
6.2 ‘Ups and Downs’ – Impact and Policy
Recommendations
6.4 ‘ Zero Growth’ – Impact and Policy
Recommendations
In the second scenario ‘Ups and Downs’, innovation
and especially radical innovation dominates in
multinational enterprises. However, the overall
investment in innovation stagnates. Part of their
In our ‘Zero Growth’ scenario, multinational
enterprises and networks of MNEs and other
companies dominate the economy and restrain
competition. Innovation as the engine for economic
A first but crucial step to come out of this
situation is to provoke a much higher degree of
competition. European policy should leave behind
‘MNE-dominated Policy’ in order to address all
actors of the European research area. The general
recommendation for EU policy could be to follow
a path of deregulation. Furthermore, innovative
products and services could be stimulated by public
procurement.
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Multinational Enterprises
development becomes less and less important
to differentiate in competition. Mutual formal
and informal agreements, cartels, or oligopolies
– either between MNEs or networks – dominate
the economic scenery. This situation is supported
by an MNE-dominated EU policy and leads to a
lack of linkage between innovation and company
strategy, accidental innovation, handpicked
investment in knowledge production, and only
incremental innovation. All in all, multinationals
in Europe are no longer competitive and are the
losers of the innovation race. Due to the described
lack of innovation in multinational enterprises,
there is only a limited demand for technological
competencies in the public R&D system. Joint
R&D projects and contract research have become
less and less in this ‘Zero Growth’ scenario.
The awareness of industry and policy for a
sophisticated and specialised public R&D system
has decreased. As a consequence, investment in
the public R&D system has dropped dramatically.
Finally, the technological competencies of the
European public R&D system are no longer
competitive and are regarded as average or
below-average compared with other nations. As
a consequence of that situation, high-tech SMEs
have nearly disappeared from the marketplace.
It is no longer attractive to found a technologybased start-up firm. The entrepreneurial spirit is
completely non-existent.
The Future of Key Research Actors in the European Research Area
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Roberts, E.B., Benchmarking the Strategic Management of Technology (I),: Research Technology Management, 38, 1, 1995, (pp. 44-56).
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167
Wo rki ng Paper 8
Multinational Enterprises
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The Future of Key Research Actors in the European Research Area
8. Appendix
Appendix 8.1
R&D expenditure by foreign affiliates in selected economies, 1993-2003
(Millions of dollars and per cent of business R&D)
Economy
Argentina
Category
Expenditure
Share (%)
Australia
Brazil
Canada
Chile
China
Czech Republic
Finland
France
Germany
168
Ireland
Israel
Italy
Japan
Korea, Rep.
Mexico
The Netherlands
Poland
Portugal
Singapore
Slovakia
Spain
Sweden
1995
22
1996
42
1997
43
1998
56
1999
26
2000
38
2001
43
2002
24
..
..
..
14.3
12.0
15.1
7.1
11.8
16.5
23.2
2003
..
..
..
..
978
..
..
..
1 090
..
..
..
..
..
..
30.3
..
..
..
41.1
..
..
..
..
Expenditure
..
..
..
..
..
..
..
1 145
..
..
898
Share (%)
..
..
..
..
..
..
..
48.0
..
..
47.9
1 582
1 646
1 732
1 866
2 187
2 168
2 241
2 439
2 650
2 658
3 070
Share (%)
Expenditure
..
..
29.8
31.8
34.6
33.2
32.0
29.3
29.6
33.7
34.8
Expenditure
..
2
15
6
7
6
4
11
8
6
..
Share (%)
..
2.3
14.1
6.7
10.7
9.3
6.2
10.8
8.1
3.6
..
Expenditure
..
..
..
..
..
..
..
..
..
2 098
2 748
Share (%)
..
..
..
..
..
18.0
19.2
21.6
21.7
22.0
23.7
Expenditure
..
..
71
65
85
141
118
152
203
239
325
Share (%)
..
..
20.9
18.0
22.1
30.7
27.4
36.9
45.3
43.4
46.6
Expenditure
..
..
250
..
305
358
449
388
427
476
..
Share (%)
..
..
13.9
..
14.0
14.2
15.9
13.4
14.5
15.0
..
Expenditure
..
2 793
3 721
3 633
..
3 238
..
..
4 006
3 986
..
Share (%)
..
14.2
17.1
16.7
..
16.4
..
..
21.5
19.4
..
4 065
..
4 554
..
4 744
..
5 501
..
7 170
..
..
13.4
..
13.0
..
14.5
..
15.4
..
22.1
..
..
Expenditure
Expenditure
Expenditure
Share (%)
India
1994
21
Expenditure
Share (%)
Hungary
..
Share (%)
Share (%)
Greece
1993
6
..
6
..
5
..
10
..
..
..
..
6.4
..
3.7
..
3.8
..
4.5
..
..
..
..
15
29
31
56
90
65
71
113
141
155
180
12.4
22.6
21.8
44.4
65.3
52.7
53.2
68.4
71.4
65.5
62.5
Expenditure
..
..
..
48
59
84
103
..
..
..
..
Share (%)
..
..
1.7
2.3
2.4
3.2
3.4
..
..
..
..
Expenditure
266
320
407
452
454
504
532
498
521
639
875
Share (%)
67.1
66.8
66.7
65.9
65.4
64.4
63.7
64.2
64.6
68.7
72.1
Expenditure
..
96
97
169
208
141
389
630
726
889
..
Share (%)
..
7.9
6.7
9.7
10.0
6.1
14.3
17.5
20.7
..
..
Expenditure
..
..
..
..
..
..
..
..
1 964
..
..
Share (%)
..
..
..
..
..
..
..
..
33.0
..
..
Expenditure
702
1 319
1 365
862
1 140
1 386
3 666
3 636
3 197
..
..
Share (%)
0.9
1.5
1.4
0.9
1.3
1.7
3.9
3.6
3.4
..
..
Expenditure
..
17
29
34
41
29
101
143
157
167
..
Share (%)
..
0.2
0.3
0.3
0.4
0.5
1.4
1.6
1.7
1.6
..
Expenditure
..
183
58
121
126
191
238
303
248
284
..
Share (%)
..
52.7
29.3
51.3
46.9
38.6
39.9
45.9
32.5
..
..
Expenditure
..
..
..
..
857
885
983
1 071
1 042
..
..
Share (%)
..
..
..
..
20.4
21.2
21.7
26.1
24.7
..
..
Expenditure
..
..
..
..
42
61
97
52
62
43
61
Share (%)
..
..
..
..
10.3
12.7
20.2
13.1
14.6
19.2
19.1
Expenditure
..
..
..
..
..
..
35
..
91
..
..
Share (%)
..
..
..
..
..
..
17.9
..
30.9
..
..
Expenditure
..
..
..
..
..
..
..
..
658
618
715
Share (%)
..
..
..
..
..
..
..
..
57.6
52.9
59.8
Expenditure
..
3
4
5
4
3
3
13
16
19
20
Share (%)
..
4.1
3.9
4.4
2.3
2.9
3.2
15.2
18.1
20.7
19.0
1 371
742
..
673
..
798
..
934
..
981
1 223
Share (%)
Expenditure
39.6
..
30.0
..
35.7
..
33.8
..
33.6
33.1
27.3
Expenditure
582
..
1 193
..
1 225
..
2 508
..
2 957
..
4 032
Share (%)
13.3
..
19.3
..
18.7
..
36.4
..
40.7
..
45.3
Thailand
Turkey
United Kingdom
United States
Expenditure
..
..
..
..
..
..
..
..
..
..
40
Share (%)
..
..
..
..
..
..
..
..
..
..
28.1
Expenditure
..
..
..
..
45
26
32
45
..
..
..
Share (%)
..
..
..
..
14.8
8.4
7.3
10.6
..
..
..
Expenditure
..
3 939
4 258
4 226
5 131
5 104
5 700
5 457
7 205
7 468
10 049
Share (%)
..
29.1
29.6
29.1
32.8
30.4
31.2
31.3
40.6
38.0
45.0
14 199
15 566
17 542
17 984
19 428
25 373
24 027
26 180
26 463
27 508
..
12.3
13.3
13.5
12.6
12.5
15.2
13.3
13.2
13.3
14.1
..
Expenditure
Share (%)
Memorandum items:
Developed countries a
Developing countries
28 973
32 303
36 778
37 704
40 116
47 055
51 304
56 349
59 400
62 342
..
Share (%)
Expenditure
10.6
11.2
11.4
11.3
11.9
13.6
13.6
13.8
14.9
15.7
..
Expenditure
223
223
172
295
321
392
1 649
2 446
4 402
4 135
..
Share (%)
2.3
2.3
1.5
2.3
2.5
4.1
11.8
14.3
18.3
17.7
..
Economies in transition b Expenditure
18
104
106
167
220
269
288
331
422
455
..
9.3
19.0
18.3
16.8
20.0
22.9
25.6
31.1
36.4
41.3
..
29 214
32 630
37 075
38 166
40 657
47 716
53 241
59 125
64 223
66 933
..
10.3
11.0
11.1
11.0
11.6
13.3
13.5
13.9
15.2
15.9
..
Share (%)
Estimated total
Expenditure
Share (%)
Source: UNCTAD, based on national sources and data provided from the OECD AFA database.
a Excluding new EU members.
b Proxied by data for four new EU members: the Czech Republic, Hungary, Poland and Slovakia.
Note: The annual totals have been estimated using the data available for the given year; where no data were available, the data of the preceding, or subsequent year in that order of preference,
have been used.
Appendix 8.2
Key Influence Factors – Projections – Descriptions
Projection
Description of Projections
hyper-competition
Hypercompetition is a key feature of a economy.Not only is there
more competition, there is also tougher and smarter competition.
“Hypercompetition” is a state in which the rate of change in the competitive
rules of the game are in such flux that only the most adaptive, fleet, and
nimble organizations will survive (see D’Aveni, 1994)
Cooperation is the contractual or non-contractual agreement between
legal or economic autonomous companies or other organisations through
the coordination or externalisation of a function or task to the cooperation
partner
Situational opportunism as strategic option, cooperation as temporally
alliance, cooperative competition and competitive cooperation, building up
“corporate spheres of influence” (see e.g. Brandenburger, Brandenburger,
Nalebuff 1998)
In economics, a monopoly (from the Greek monos, one + polein, to sell) is
defined as a persistent market situation where there is only one provider
of a kind of product or service. Monopolies are characterized by a lack of
economic competition for the good or service that they provide and a lack
of viable substitute goods (see http://en.wikipedia.org/wiki/Monopolism,
22.10.2005)
cooperation
co-opetition
monopolies
Economic development
(see Becker-Boost, Fiala
2001, Dent 1998)
The long boom
Zero growth
Ups and downs
Mega recession
Long lasting sustainable, dynamic economic growth
Long-term stagnation, no growth
Wild economic fluctuations
Crisis after crisis, economic slump
Globalisation of knowledge
production
(see Gerybadze, Reger 1999)
Centres of excellent innovation abroad (CoEI) Generation of technological knowledge and innovation in foreign countries
and for foreign markets, R&D investment abroad
Home based innovation
Generation of technological knowledge and innovation in the home country
and for the local market, R&D investment concentrated at home
Export innovation
Generation of technological knowledge and innovation in the home
country and export of the innovation to foreign markets, R&D investment
concentrated at home, adaptation abroad
Import innovation
Generation of technological knowledge and innovation abroad and import of
the innovation into the home country, R&D investment abroad, adaptation
at home market
Innovation in company
strategy
Innovation dominated strategy
Innovation by chance
Innovation rejection strategy
Extreme high relevance, completely linked to company strategy
No clear relevance, not linked at all, innovation occurs only by chance or not
Conscious decision against innovation
169
Wo rki ng Paper 8
Multinational Enterprises
Key factor
Competition
The Future of Key Research Actors in the European Research Area
Investment in knowledge
production
Dramatic increase
Stagnation
Dramatic decline
Handpicked investment
R&D expenditure by MNE increase dramatically
R&D expenditure by MNE remain static
R&D expenditure by MNE decrease dramatically
R&D Expenditure only for selected, “handpicked” innovation projects
Radical innovation
Incremental innovation
Technology-based innovation
Application-based innovation
Novelty of applications and technology is very high
Novelty of applications and technology is low
Novelty of applications is low, novelty of technology is very high
Novelty of technology is low, novelty of applications is very high
Completely outsourced
Technological competencies are completely external and located in
universities, R&D institutes, high-tech SMEs, suppliers, customers
Technological competencies are kept completely within the MNE and are
highly protected by IPR and strict license policy
Enriching the MNEs own knowledge base through the integration of
suppliers, customers, universities, R&D institutes, high-tech SMEs (see
Gassman, Ellen 2004)
Technological knowledge within the MNEs, bringing ideas to the market,
selling IPR and multiplying technology by transferring ideas to the outside
(see Gassman, Ellen 2004)
Novelty of knowledge
production
(see Hauschildt 1997)
Technological competencies
of MNE
Closed innovation
Open innovation: outside-in-process
Open innovation: inside-out-process
Change of the population
Growth of the population outside European
countries
Emigration of nations to Europe
170
Emigration of Europeans
The globes population will growth, however differently according to regions.
The largest gains in population are projected to be in Sub-Saharan Africa
and the Near East. In these regions, many countries are expected to more
than double in size, with some more than tripling. More moderate gains are
expected for North Africa North and South America, Asia and the Pacific. On
the opposite end of the spectrum, a majority of countries in Europe and the
New Independed States of the Soviet Union are expected to experience a
decline in population (see U.S Census Bureau 2002).
Citizens from non-European countries immigrate to Europe. High and long
lasting attractiveness of European countries
Europeans immigrate to countries outside Europe. High and long lasting
attractiveness of countries like USA, India or China.
Change of values
(see Siemens AG 2004)
Society of Modesty
Fuzzy Society
The society has become much more modest. Economic growth is limited
and the society has to learn to live with this. The difference between “rich”
and “poor” is not very big, a high level of equity is aimed at to ensure social
peace, modest prosperity, health, jobs and political stability. Deceleration
of the speed in private and working life. Working hours have increased,
however working intensity has decreased. Society has become age
integrated and realised the finiteness of life. Education, work and leisure
time are integrated in a work life balance across the whole age groups.
The beat of life has become faster. Societal institutions like partnerships,
networks, groups of interest or working teams change faster and faster
and are no longer long-term constants in the individual life. Partner and
working relationships are not lifelong. Life is full of risks, own behaviour is
spontaneous and not planned. Society is dominated by individuality, each
single creates his or her own personal network and has to define his or her
own values. Society falls apart in “rich” and “poor”, “performance oriented”
and “leisure oriented” individuals. Society is divided into locally linked and
thinking people and a global elite, which is at home in every place in the
world, representing a joint worldwide culture.
Regulations and policy
interventions at EU level
Policy of Balance
Policy of Over-Regulation
MNE dominated Policy
Laissez-Faire Policy
Adequate forms of EU regulations and modest policy interventions of the EU
Over-regulation at EU level and active intervention into economic structures
and companies’ strategies
MNEs dominate EU regulation decisions and EU sets frame conditions only
Inefficiencies of the market and economy will be best solved without an
active role of the EU. There is no active intervention of the EU but great trust
is set in the self-regulation potential of all economic actors
Appendix 8.3
Consistency Matrix
Appendix 8.4
The Long Boom – Scenario 1 (Cluster Results)
Wo rki ng Paper 8
Multinational Enterprises
171
Appendix 8.5
Ups and Downs – Scenario 2 (Cluster Results)
The Future of Key Research Actors in the European Research Area
Appendix 8.6
Handpicked Innovation – Scenario 3 (Cluster Results)
Appendix 8.7
Zero Growth – Scenario 4 (Cluster Results)
172
Appendix 8.8
Scenario 3
Handpicked Innovation
Scenario 2
Ups and Downs
Scenario 1
The Long Boom
Impact Analysis and Policy Recommendations
Impact on the European Research Area
Policy Recommendations
• MNEs: innovation dominates, dramatic investment in innovation,
internationalisation strategy includes, firstly, export innovation and,
secondly, CoEIs, open innovation model.
• Public R&D system is very important.
• High-tech SMEs: high technological competencies, pushing
technological innovation, very competitive, entrepreneurial spirit.
The EU should find adequate forms of regulations and intervene only
in a modest way. The intervention should be limited to ensure the
frame conditions for competition and a climate for innovation and
entrepreneurial spirit. The technological competencies of the public
R&D system are very important and should continuously build up and
improved. High-tech SMEs and their competencies should be heavily
supported by the EU. Therefore the policy of balance also means not to
privilege MNEs over the other actors in the R&D system.
The influence of policy regulations and interventions at the EU level
seems to be fairly limited in this scenario. One main task of EU policy
is to balance the economic cycle. The other main task of EU policy is to
try to increase investment in knowledge production and to improve the
attractiveness of Europe for foreign investment in innovation.
• MNEs: innovation and especially radical innovation dominates,
however, investment in innovation stagnates, internationalisation
strategy includes CoEIs abroad, open innovation model.
• Public R&D system is very important.
• High-tech SMEs: high technological competencies, cyclic ‘birth and
death’ of high-tech SMEs according to the economic ups and downs.
• MNEs: innovation by chance and handpicked investment in innovation
dominates; innovation is generated by MNEs abroad and imported to
the EU, application-based innovation with low degree of technological
novelty. MNEs have stronger inside-orientation in the innovation
process than in scenario 1 and 2.
• Importance of public R&D system is lower because MNEs have a
stronger focus on internal knowledge generation.
• Importance of high-tech SMEs as technology generators for MNEs is
lower and only one possible option, MNEs favour internal innovation
activities.
The influence of policy regulations and interventions at EU level seems
to be higher than in scenario 1 and 2. The main alternative hereby
is ‘Policy of Balance’, which includes mainly two tasks. Due to the
economic ups and downs, one main task of EU policy is to balance the
economic cycle. Another challenge for the policymaker is to establish a
fruitful balance between exports and imports of innovation, permanent
and accidental innovation activities and application- and technologyorientated and radical innovation.
Scenario 4
Zero Growth
• MNEs: MNEs dominate the economy and restrain competition.
Innovation becomes less and less important to differentiate in
competition. Mutual formal and informal agreements, cartels, or
oligopolies dominate the economic scenery. This is supported
by an MNE-dominated EU policy. This situation leads to a lack
of linkage between innovation and company strategy, accidental
innovation, handpicked investment in knowledge production, and
only incremental innovation. All in all, European MNEs are no longer
competitive and are the losers of the innovation race.
• The public R&D system: Due to the lack of innovation in MNE, there
is a limited demand for the technological competencies of the public
R&D system. Joint R&D projects and contract research have become
fewer. The awareness of industry and policy for a sophisticated and
specialised public R&D system has decreased. As a consequence,
investment in the public R&D system has dropped dramatically. In
the end, the technological competencies of the European public R&D
system are no longer competitive and are regarded as average or
below average compared with other nations.
• High-tech SMEs: Due to the lack of innovation high-tech SMEs have
nearly completely disappeared. It is no longer attractive to found a
technology-based start-up firm.
In order to provoke a higher degree of competition, EU policy should
leave behind the ‘MNE-dominated Policy’ in order to address all actors
of the European research area. EU policy should be oriented towards
deregulation.
Innovative products and services can be stimulated by public
procurement.
9. Bibliography
Selected Literature on Multinational Enterprises, Foresight and Scenario Technique
Bürgel, H. D., Reger, G., Ackel-Zakour, R., Technology Foresight: Experiences From Companies Operating Worldwide, International
Journal of Services Technology and Management, Vol. 1, No. 4, 2000, (pp. 394-412).
Chen, X., Reger, G., Foreign Direct Investment by Multinational Corporations in China – The Pharmaceutical Sector, in Festel, G.,
Kreimeyer, A., von Zedtwitz, M., The Chemical and Pharmaceutical Industry in China, Springer, Heidelberg, 2005, (pp. 133-148).
Edler, J., Meyer-Krahmer, F., Reger, G., Changes in the Strategic Management of Technology - Results of a Global Benchmarking Study,
R&D Management, Vol. 32, No.2, 2002, (pp. 149-164).
Gerybadze, A., Meyer-Krahmer, F., Reger, G. (Hrsg.), Globales Management von Forschung und Innovation, Schäffer-Poeschel Verlag,
Stuttgart, 1997.
Gerybadze, A., Reger, G., Globalization of R&D: Recent Changes in the Management of Innovation in Transnational Corporations,
Research Policy, Vol. 28, Nos. 2-3, 1999, (pp. 251-274).
Gerybadze, A., Reger, G., Managing Globally-Distributed Competence Centres within Multinational Corporations. A ResourceBased View, in Scandura, T., and Serapio, M. (eds.), Research in International Business and International Relations. Leadership and
Innovation in Emerging Markets, Vol. 7, JAI Press, Stamford/ London, 1998, (pp. 183-217).
Jungmittag, A., Meyer-Krahmer, F., Reger, G., Globalisation of R&D and Technology Markets – Trends, Motives, Consequences, in
Meyer-Krahmer, F. (ed.), Globalisation of R&D and Technology Markets. Consequences for National Innovation Policies, Physica-Verlag,
Heidelberg, 1999, (pp. 37-77).
Jungmittag, A., Reger, G., Reiss, T. (eds.), Changing Innovation in the Pharmaceutical Industry - Globalization and New Ways of Drug
Development, Springer-Verlag, Berlin, New York et al., 2000.
Lizaso, F., Reger, G., Linking Roadmapping and Scenarios as an Approach for Strategic Technology Planning, International Journal of
Technology Intelligence and Planning, Vol. 1, No. 1, 2004, (pp. 68-86).
Meyer-Krahmer, F., Reger, G., New Perspectives on the Innovation Strategies of Multinational Enterprises: Lessons for Technology
Policy in Europe, Research Policy, Vol. 28, 1999, (pp. 751-776).
Mietzner, D., Reger, G., Advantages and Disadvantages of Scenario Approaches for Strategic Foresight, International Journal of
Technology Intelligence and Planning, Vol. 1, No. 2, 2005, (pp. 220-239).
Reger, G., Beise, M., Belitz, H. (Hrsg.), Innovationsstandorte multinationaler Unternehmen. Internationalisierung technologischer
Kompetenzen in der Pharmazeutik, Halbleiter- und Telekommunikationstechnik, Physica-Verlag, Heidelberg, 1999.
Reger, G., Bührer, S., Balthasar, A., Bättig, C., Influence of Non-membership of the European Union on Collaboration in European R&D
Networks: the Case of Switzerland, Science and Public Policy, Vol. 25, No. 3, 1998, (pp. 171-183).
Reger, G., Bührer, S., Balthasar, A., Bättig, C., Switzerland’s Participation in the European RTD Framework Programmes: A Win-Win
Game?, Technovation, Vol. 18, No. 6/7, 1998, (pp. 425-438).
Reger, G., Cuhls, K., von Wichert-Nick, D., Challenges to and Management of R&D Activities, in Reger, G., Schmoch, U. (eds.),
Organisation of Science and Technology at the Watershed, Physica-Verlag, Heidelberg, 1996, (pp. 139-266).
Reger, G., Kuhlmann, S., European Technology Policy in Germany. The Impact of European Community Policies upon Science and
Technology in Germany, Physica-Verlag, Heidelberg, 1995.
Reger, G., Schmoch, U. (eds.), Organisation of Science and Technology at the Watershed, Physica-Verlag, Heidelberg, 1996.
Reger, G., von Wichert-Nick, D., A Learning Organization for R&D Management, International Journal of Technology Management,
Special Issue on R&D Management, Vol. 13, Nos.7/8, 1997, (pp. 796-817).
173
Wo rki ng Paper 8
Multinational Enterprises
Edler, J., Meyer-Krahmer, F., Reger, G., Managing Technology in the Top R&D Spending Companies Worldwide - Results of a Global Study,
Engineering Management Journal – Special Issue on ‘Managing High Technology Research Organizations’, Vol. 13, No. 1, 2001, (pp. 5-11).
The Future of Key Research Actors in the European Research Area
Reger, G., Wikarski, D., Siswanto, J., The Utilization of Intranets as Cooperation Platforms in Global Innovation Processes –
Opportunities and Risks, International Journal of Entrepreneurship and Innovation Management- Special Issue on Entrepreneurship,
Innovation and Globalisation, Vol. 2, No. 2/3, 2002, (pp. 204-223).
Reger, G., Benchmarking the Internationalisation and Co-ordination of R&D of Western European and Japanese Multi-national
Corporations, International Journal of Innovation Management, Vol. 1, No. 3, 1997, (pp. 299-331).
Reger, G., Changes in the R&D Strategies of Transnational Firms: Challenges for National Technology and Innovation Policy. STI
Review, Special Issue on ‘New Rationale and Approaches in Technology and Innovation Policy’ (ed. OECD), No. 22, 1998, (pp. 243-276).
Reger, G., Coordinating Globally Dispersed Research Centres of Excellence – The Case of Philips Electronics, Journal of International
Management – Special Issue on R&D Globalization and International Business, Vol. 10, No.1, 2004, (pp. 51-76).
Reger, G., How R&D is coordinated in Japanese and European Multinationals, R&D Management, Vol. 29, No. 1, 1999, (pp. 71-88).
Reger, G., Internationalisation and Coordination of R&D of Western European and Japanese Multinational Corporations, in Macharzina,
K., Oesterle, M.-J., Wolf, J. (eds.), Global Business in the Information Age, Vol. II, EXTEC, Stuttgart, 1997, (pp. 573-604).
Reger, G., Internationalisation of Research and Development in Western European, Japanese and North American Multinationals,
International Journal of Entrepreneurship and Innovation Management- Special Issue on Entrepreneurship, Innovation and
Globalisation, Vol. 2, No. 2/3, 2002, (pp. 164-185).
Reger, G., Internationalization and Coordination of Research and Development at Large Corporations, International Management,
Vol.3, No. 2, 1999, (pp. 13-32).
Reger, G., Koordination und strategisches Management internationaler Innovations­prozesse, Physica-Verlag, Heidelberg, 1997.
Reger, G., Linking Corporate-wide Global R&D Activities, in Cantwell, J., Molero, J. (eds.), Multinational Enterprises, Innovative
Strategies and Systems of Innovation, Edward Elgar, Cheltenham, 2003, (pp. 81 – 104).
Reger, G., Technology Foresight in Companies: From an Indicator to a Network and Process Perspective, Technology Analysis &
Strategic Management, Vol. 13, No. 4, 2001, (pp. 533-553).
Reger, G., The Importance of European Technology Policy for the German Research Landscape and its Influence on Cooperation, in Hübner,
H., Dunkel, T. (eds.), Recent Essentials in Innovation Management and Research. Networking, Innovation Systems, Instruments, Ecology
in International Perspective, Gabler Edition Wissenschaft/ Deutscher Universitäts-Verlag, Wiesbaden, 1995, (pp. 35-48).
Reger, G., Trends in the Internationalisation of Technological Knowledge and Consequences for National Science and Technology
Policy, in Kuklinski, A., Orlowski, W., The Knowledge-based Economy – The Global Challenges of the 21st Century, State Committee for
Scientific Research, Warsaw, 2000, (pp. 213-238).
174
10. C
urriculum Vitae
Guido Reger is full professor for innovation and entrepreneurship at the University of Potsdam in Germany
and director of the Brandenburg Institute for Entrepreneurship and Small and Medium-Sized Enterprises.
Prior to this, he worked as a senior researcher at the Fraunhofer Institute for Systems and Innovation
Research (ISI) in Karlsruhe. He was member of the board of directors of Fraunhofer ISI from 1996 until 1998.
From 1994-1998, he was coordinator and representative of the Federal Republic of Germany in the committee
of the programme ‘Innovation and SME’ of the Commission of the European Communities.
Prof. Reger acts as a senior adviser to the German Ministry of Education, Science, Research and Technology
(BMBF), the German Ministry of Economic Affairs (BMWi), Swiss Federal Office for Education and Science
(BBW), the OECD, the European Commission, and multinational corporations. He was visiting professor
at the National Institute of Science and Technology Policy (NISTEP) in Tokyo, the Massachusetts Institute
of Technology (MIT) in Cambridge, MA, the Beijing University of Aeronautics & Astronautics, and various
European business schools. In April 2004, he received the research award of the ‘International Association
for Management of Technology (IAMOT)’ for one of the most active researchers in the Technology Innovation
Management field. His research includes projects on industrial innovation strategies, globalisation of
research and technology, evaluation of science and technology policy, regional and national innovation
systems. Guido Reger has published around 100 reports, papers, books, and refereed articles.
9
W o r k in g
Paper
National governments
Jari Romanainen, Helsinki University of Technology
G
overnment organisations have a significant
impact on the production, distribution and use
of knowledge, in the context of the European
Research Area (ERA), mainly through science,
technology, innovation and other policies1, and
the allocation of related resources. In this context,
the actual producers of new knowledge as well
as distributors and users of knowledge, such as
universities, research institutes, private companies,
intermediary organisations, etc., are not considered
as part of government. They are discussed in other
papers. This paper focuses on national governments,
whose role in simple terms could be described as
facilitators.
National governments, however, are not the only
facilitators in the multidimensional European public
governance structure. The European Commission,
regional and local governments and various
multinational collaborative platforms in Europe and
globally also facilitate the production, distribution
and use of knowledge. While these other actors
in the governance system are discussed in other
papers, it is important to understand the interactions
and relationships between national governments
and these other facilitators.
Taking the focus described above, national
governments themselves are mainly users of
knowledge, not producers or distributors as such.
They require and use knowledge for the purpose of
ensuring the nations’ sustainable economic, social
and environmental development and the well-being
of citizens. In order to do this, national governments
set up policies and implement them by allocating
resources, developing institutional structures and
regulations, etc.
1.This list should also include education, industry, competitiveness and all
other policies related to the production, distribution and use of knowledge.
The term STI (science, technology and innovation) is used in this paper to
cover all knowledge-related policies, i.e. it is not limited to narrowly defined
science, technology and innovation policies.
This paper therefore focuses on STI policies and
the changing role of different national government
organisations in designing and implementing these
policies, i.e. their changing role in the STI-policy
processes.
1.1 Types of government organisations and
their role in STI
The key roles of government organisations in science,
technology and innovation are the design and
implementation of related policies. Understanding
the roles different government organisations play
in policy design and implementation, as well as the
changes in these roles over time, one must look into
the related governance structures and processes.
Figure 1 is an illustration of the STI policy cycle.
Figure 1
The STI policy cycle2
Agenda
setting
National
strategy
Strategic
intelligence
Policy
learning
Sector
policies
Policy
evaluation
Implementation
strategies
Performance
evaluation
Design
Evaluation
Instrument
set-up
Impact
evaluation
Implementation
The STI policy cycle consists of three main types of
processes: (1) identifying policy needs; (2) setting
the policy agenda; and (3) implementing the policy.
Furthermore, the processes and structures keep
changing over time. This adds yet another class of
processes, which can be called learning processes.
These include activities such as evaluation,
monitoring, benchmarking, etc.
2.See Governance of innovation systems, Volume 3: Case studies in crosssectoral policy, OECD, 2005.
175
Wo rki ng Paper 9
National governments
1. Introduction
The Future of Key Research Actors in the European Research Area
Processes identifying policy needs typically
include activities such as foresight, different
forms of strategic intelligence, various forms
of stakeholder consultation, etc. Governments
frequently also use various advisory bodies and
sometimes separate agencies and/or specialised
policy research institutes for the production of
the necessary knowledge and understanding for
identifying policy needs.
Once the policy needs are identified, the setting
up of the actual policy agenda is done by the
government and parliament. This process is
typically based on recommendations from advisory
bodies, committees, strategic evaluations or some
other similar activity, which is a continuation of
the process identifying policy needs. Some of
the key features of this process are stakeholder
access and transparency, i.e. who are invited to
participate in formulating the recommendations
and how open is the process.
176
The implementation of STI policies is the
responsibility of relevant ministries and government
agencies. The structure and role of ministries and
agencies vary quite a lot from country to country,
and so do implementation processes. The role of
regional governments and their relationship with
national governments also have an impact on these
processes.
The most typical activities in learning processes are
evaluation and monitoring. Monitoring is normally
embedded into implementation processes, at
least for the part of accountability and good public
management, i.e. monitoring the appropriate use
of public money. Evaluations are typically used for
analysing impacts and/or providing an independent
outside view of the rationale, appropriateness,
objectives, etc., of a policy measure, set of policy
measures or policies themselves. Both monitoring
and evaluations are designed and commissioned by
those bodies that commission the implementation
of policies (typically governments or parliaments) or
policy measures (typically ministries). Evaluations
can be planned and organised and sometimes even
performed by specialised evaluation institutes.
However, as actual policy evaluation is not that
typical, ministries are typically responsible for
evaluations, which focus mainly on selected policy
measures.
The summary of the most relevant government
organisations in STI are:
• Governments and parliaments;
• Ministries;
• Agencies;
• Advisory bodies;
• Other
governmental
organisations
with
specific task to support policymaking and/or
implementation, e.g. specialised policy research
institutes.
Governments allocate significant resources for
universities and public or semi-public research
organisations, some of which focus on research
relevant for STI policy. Governments or government
organisations also commission specific research
for universities, research institutes or private
companies for the purpose of STI policy design,
implementation or learning. Although these
organisations provide valuable knowledge and
insight into STI policy design and implementation,
they are not discussed here. Only those government
organisations whose actual purpose is to plan,
make decisions, implement or analyse STI policies
or related knowledge in STI-policy processes are
discussed in this paper.
1.2 Changes in STI policy
The late 1980s and early 1990s witnessed a major
change in STI policies. Prior to this change, STI
policies, or rather science policy and then later
technology policy, were based on a simple linear
model of innovation. Science policy focused on
universities and public research institutes with the
assumption that research would lead into scientific
discoveries and other useful results which would
eventually be taken up by industries and turned into
economic growth and other benefits.
As industries and markets developed, companies
started to realise that customers had different
needs. Instead of producing and selling the same
standardised products to every customer, there
was an increasing need to identify customer
segments and produce tailored products and
services. Companies and eventually STI policies
recognised that customer needs are a powerful
source of innovation. The earlier science-push
approach was complemented with market-pull
approach. Science policy was complemented with
technology policy and various types of institutional
structures were established to enhance industry
interaction with universities and research
institutes. However, the basic understanding of
the innovation process was still linear.
Post-war changes in STI policy3
3
Theory
2
1
Subsidy
Focus
4
5
Coupling, Complex Systems
Needs Pull
Technology Push
Big Cos, National Champions
Policy
Build up Universities,
RIs; RAs
1950s
1960s
SMEs, Tax Incentives
Foresight
New programme forms
Funding reforms
University reforms
Collaborative
programmes
Economic, military
competition
Commercialise
RIs; RAs
1970s
1980s
1990s
As the understanding of real life innovation
processes increased, it was realised that they were
not at all linear. Scientific discoveries and other
results of academic research could lead into many
applications, some of them quite unexpected. The
processes through which innovations eventually
arrived at the markets were quite complex and
interactive. Increasing knowledge content of
products and services, the ability to produce tailored
products and services, the need to differentiate from
competitors, the need to react faster to changes in
the markets, etc., further increases the complexity
and interactive characteristics of innovation
processes.
The realisation that basic research, applied
research, industrial research, product and service
development, commercialisation, etc. are not
separate consecutive steps in a linear process,
but rather parallel activities in a complex and
interactive process, leads to the focus on industryacademia relationships. At first the focus was on
direct interaction between universities and research
institutes and companies, but gradually this was
extended to cover various intermediary structures
and organisations. Eventually, a systemic approach
was adopted. Like any changes in policy, this did
not happen overnight. Gradual changes started to
appear during the 1980s, but the real awakening
took place during the 1990s after Lundval and
Freeman published their theories of national
innovation systems.
The gradual adoption of the systemic approach,
globalisation, increased market dynamics, etc., has
emphasised the role of government as a facilitator.
3.Erik Arnold and Katalin Balázs, Methods in The Evaluation of Publicly
Funded Basic Research, Technopolis Ltd, 1998.
Market liberalisation and internationalisation
of businesses and ownership, together with
increasing market dynamics and the subsequent
increased competition, require such a degree of
agility that it is not rational or even possible for
the government to take a direct role in the markets.
The only practical approach is to use softer policy
measures to facilitate innovation. With the adoption
of the systemic approach, policy measures such as
tax incentives, competitive public funding in the
form of grants and loans, networking initiatives,
collaborative platforms, attempts to reduce red
tape, etc., have gained momentum instead of direct
investments, government ownership or protective
market regulation.
The strengths of the systemic approach are clearly
in the ability to analyse and identify STI policy needs
in a comprehensive way, and to analyse and identify
key actors and interactions facilitating innovation.
However, the multilevel governance structures
emphasised by globalisation and increasing
networking across regions and nations present a
challenge for the systemic approach. Actors in an
innovation system operate in an environment, which
has the characteristics of a local, regional, national,
European and global innovation system. The
environment also consists of various overlapping
sector- and cluster-specific innovation systems.
The systemic approach has proven to be useful
especially in analysing and identifying bottlenecks.
However, addressing these bottlenecks one-by-one
with targeted policy measures has led to another
problem. Local, regional, national and EU-level
policymakers have identified more or less similar
challenges and, without sufficient coordination,
launched activities addressing these challenges.
Adding the lack of coordination between actors
at the same governance level (e.g. between
ministries or between regional actors) has led to a
rather complex mix of numerous individual policy
measures. This cannot be seen as failure of the
systemic approach as such, rather a consequence of
the lack of coherence.
Addressing the challenge of coherence between
policies and policy measures across policy levels,
across STI and other policies, and over time, is
moving the focus from structures and interactions
between innovation system actors to innovation
system governance and policy processes.4
4.This emerging change of focus or emphasis in STI policy has sometimes
been referred to as ‘third generation innovation policy’ or ‘innovation policy
for the knowledge economy’. See, for example, DG Enterprise, Innovation
tomorrow, Innovation papers No 28, European Communities, 2003.
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National governments
Figure 2
The Future of Key Research Actors in the European Research Area
Innovation processes are dynamic, continuously
changing, increasingly open and seldom
geographically limited. Actors typically participate
in several interlinked innovation processes and
identify and position themselves in relation to
various networks and clusters. From a systemic
point of view, there is no such thing as a national
innovation system, rather a number of overlapping
systems. Furthermore, interactions, systems and
system boundaries are continuously changing.
In order to capture this increasing complexity STI
policies are adopting a more holistic approach.
Instead of approaching innovation as a defined
system with specific structures and interactions,
the holistic approach focuses on processes, their
facilitation and policy coherence. As the role of
innovation increases in all sectors, STI policies also
move closer to the core of all policies. This presents
a further and increasing challenge of coordination
between ministries, departments, directorates, etc.
Policy coherence has many dimensions and
subsequently many challenges and processes
attempting to tackle them.5
178
• Horizontal coherence – the coherence of
policies across sectors, ministries, departments,
directorates, etc;
• Vertical coherence – the coherence of policies
across governance levels, e.g. between EU,
national, regional and local;
• Temporal coherence – coherence of policies over
time, predictability of policy changes.
Adopting a holistic approach does not mean
abandoning the systemic approach. If the move from
the linear approach to the systemic approach could,
in simple terms, be characterised as understanding
the non-linearity and interconnectedness of
innovation processes, and realising the importance of
interactions, then the adoption of a holistic approach
could perhaps be described as understanding the
interconnectedness of policies and realising the
importance of governance processes.
The focus in systemic approach has been on
structures, formal interactions and policy
instruments, and the emphasis in policy learning
and transfer of good practices has been on the
formal benchmarking of structures and specific
policy instruments. The holistic approach takes the
5.See e.g. Governance of innovation systems, Volume 1: Synthesis report,
OECD, 2005.
analysis and hopefully the understanding further
by shifting the focus on informal interactions,
policy processes and sets of policy measures,
and the emphasis in policy learning to adaptive
capabilities, i.e. capabilities of identifying future
challenges and opportunities and adjusting
and implementing policies and policy measures
accordingly.
The holistic approach and policy coherence
emphasise the role of more comprehensive strategies
at all governance levels. The Lisbon strategy and the
related national strategies therefore facilitate the
adoption of more holistic approach in STI policies
across Europe.
2. Major driving forces
shaping government
organisations
2.1 External drivers
Globalisation of businesses
The current era of globalisation has been
characterised by a significant increase in private
sector capital flows, which have more than doubled
since 1975. At the same time, trade flows have risen
from little over 20 per cent to just under 30 per
cent of world GDP. The most important aspects of
globalisation are rapidly increasing foreign direct
investments and continuously growing international
trade, whereas immigration plays a smaller role.
Globalisation is driven by reduced transaction
costs resulting from continued trade liberalisation,
advances and the reduced costs of ICT and logistics,
and global standardisation. Due to reduced
transaction costs, companies are able to access
larger markets. This leads to increased competition.
Increasing competition in enlarging global markets
forces companies to increase their productivity,
i.e. by reducing costs and/or increasing prices.
Increasing competition also means that companies
must be able to improve their productivity faster than
competitors. Since companies can access markets
globally, they can also locate their business activities
globally. Companies can therefore distribute their
business activities to locations which offer the best
environment for any particular activity.
This means that globalisation drives structural
changes both at the company and at the industry
levels. Furthermore, the higher the knowledge
intensity of the industry or the company, the faster
the structural changes are likely to be.
Two aspects of structural changes deserve a closer
look. One is the increasing role of multinational
corporations (MNCs) and the other is networking.
MNCs are large corporations with activities in many
countries and continents. But more importantly,
they are leading companies in their respective
industrial clusters. Therefore, they have a strong
influence on the development of industries and
markets globally. Economic development especially
in smaller countries can be hugely influenced by a
single MNC’s decisions.
Competitiveness in a networked industrial structure
emphasises the need to specialise and provide
unique added value. Individual companies need to
identify the appropriate networks, and their position
and role in these networks. Companies participate
simultaneously in several types of networks.
Business networks are typically structured along
the value chain, whereas R&D networks are often
horizontal. This means that the relationship between
companies (or any actors) is defined by their
particular roles in various overlapping networks.
The fact that another company can simultaneously
be a competitor, partner, customer, etc. adds to the
complexity of relationships between companies.
Globalisation of business activities is led by the
globalisation of production. The globalisation of
more knowledge-intensive business activities such
as R&D seems to follow that of production. The main
drivers of globalisation of production are:
• Access to markets; geographical and cultural
closeness, minimisation of logistics costs, etc;
• Costs of production; low-cost labour, raw
materials and energy, low environmental and
social costs, etc;
• Access to appropriate knowledge and skills;
skilled human resources, world-class research,
partners, etc;
• Access to sophisticated demand; leading or
dynamic markets, leading customers, etc.
The importance of these drivers depends largely
on the knowledge intensity of the business activity.
In the case of standardised production of low-tech
manufacturing products, costs of production and
access to markets are decisive, whereas in the case
of innovative high-tech products and services, access
to appropriate knowledge and skills and access
to sophisticated demand are the most important
drivers.
Globalisation of businesses is likely to continue over
the next 10-15 years. Growing and developing Asian
markets, especially China, India and Russia, are likely
to enhance globalisation, especially in production.
The same applies for large South American countries,
such as Brazil. The BRIC countries (Brazil, Russia,
India and China) are likely to attract an increasing
share of global manufacturing investments to serve
the needs of their growing markets.
179
What is an even more interesting question in relation
to innovation is which are the most dynamic and
leading markets. The US has been able to foster
dynamic markets for many applications in the past,
whereas currently, many of the new applications
especially in the area of ICT are first introduced in
the Asian markets. Europe has been less successful
in creating dynamic markets to enhance the demand
for innovation over recent years.
Wo rki ng Paper 9
National governments
As the knowledge intensity of products, services and
production increases, companies are no longer able
to effectively and efficiently cover all the necessary
knowledge and skills required. Companies therefore
look for strategic partnerships and other forms of
collaboration to enhance their competitive position.
Collaboration offers complementary knowledge and
skills, flexibility of scale (e.g. of production), access
to larger markets, etc. This leads into networking
and clustering within and across industries.
On the one hand, fast-growing large developing
economies are in a better position to create certain
dynamic markets, because they are less hindered
by existing infrastructure. On the other hand,
underdeveloped infrastructures and systems, lower
education levels, possible political instability, etc.,
are less likely to facilitate an environment where
the most sophisticated new products, services and
systems are first introduced. Existing developed
infrastructures and systems such as healthcare
systems, education systems, information and
communication infrastructures, etc., can provide an
advantage for more developed countries. National
STI policies can therefore play a major role in
facilitating the development of dynamic and leading
markets.
Regions and countries have different advantages
in the competition for manufacturing and other
The Future of Key Research Actors in the European Research Area
business activities. Some have more advanced
education and research systems and can therefore
offer skilled labour, high-level research, etc. Others
can provide growing markets or low-cost resources.
As MNCs become increasingly networked, this is
likely to lead to the relocation of different business
activities to different locations. Companies are likely
to locate their standardised manufacturing close to
low-cost resources and large markets, whereas R&D
and related activities are more likely located closer
to global hotspots of scientific research. Financial
activities are increasingly located in large financial
centres. The design and development of innovative
new products, services and systems are likely to
be located close to the most dynamic and leading
markets. This means that smaller countries and
regions especially will in the longer term probably
have to increasingly specialise and compete for
specific business activities rather than industries or
companies as such.
180
European markets are diverse and developing
unevenly. Some countries and regions are quite
dynamic, while others lack competition or are
developing slowly for other reasons. European
markets are also characterised by cultural diversity,
which is a further challenge for some businesses. On
the one hand, this diversity can be an asset, but it
can also be a serious hindrance for competition and
subsequently for economic growth in Europe. The
development of common European markets is likely
to have a significant impact on how competitive
Europe is in the global competition for businesses.
Highly-fragmented markets with differences in
regulatory regimes and business cultures are
less likely to attract businesses to Europe than
a common, open and competitive market with a
unified regulatory regime.
One of the main objectives of international
governance
structures
has
been
market
liberalisation. However, the emphasis on global
environmental and social challenges is increasing.
The fairness of international trade, the economic
stability of countries and regions as private capital
and business activities relocate faster and faster,
the need to control harmful content and criminal
activities on the internet, etc., are also issues raised
at the international level. International governance
is likely to develop and cover a wider range of issues
in the future.
Changing societies and customer markets
Changes in societies and social structures take
place at several levels. Large-scale changes at the
level of the whole society include phenomena such
as an ageing population, the merging of cultural
influences, etc. Social structures change through the
formation of multiple subcultures, virtual societies
and cultural-social divide. Socio-economic changes
include economic and labour market polarisation,
skills and qualifications divide, etc. At the same time
changes also take place at the individual level. Value
systems and attitudes change, e.g. towards science,
technology and innovation, the environment, MNCs,
education, etc. People are increasingly aware of their
several roles as citizens, consumers, users, etc. As
a result, people see themselves more and more as
active participants rather than passive users in the
markets and also in innovation.
One of the major challenges in developed countries
is the ageing of the population. The demographic
change challenges national governments, especially
with respect to healthcare and labour markets.
The demand for healthcare services will increase
dramatically and the share of the labour force in
the total population will decrease. This will create
serious pressure on government budgets and force
governments to search for new and innovative
solutions in organising public services, especially
healthcare.
Increased education levels, globalisation and increased
wealth have changed attitudes and values. Earlier
wealth accumulation and consumerism are being
replaced with quality of life, individual self-expression,
creativity and belief in individual value systems rather
than ideologies. This change in values and attitudes
has an impact on global markets and their structures.
There is an increasing demand for personalised
products and services. The demand of services is
growing much faster than manufactured products.
People select the communities they want to belong
to and create new virtual communities of likeminded
people. Influences from other cultures challenge
the national identity. People travel more, follow
world events, live and work abroad and become
more internationally aware. Global environmental
challenges, solidarity towards developing countries,
etc., gain increasing interest and the membership
and number of non-governmental organisations
(NGOs) is rising.
The change in values and attitudes is also a
source of polarisation and value conflicts, for
example, nationalism vs. internationalisation, or
environmental values vs. wealth creation or personal
wellbeing. These value conflicts are potential
sources of political instability and social unrest.
Cultural diversity is likely to increase within countries
and regions. Multicultural characteristics are likely
to enhance innovation and networking capabilities,
provided that increasing diversity does not lead
towards increasing social polarisation.
Although there are small elites of highly skilled
professionals that already move and work globally,
the majority of skilled human resources are
relatively stable geographically. This will probably
change as new generations born and raised in a
more open and global world occupy the global
labour markets. The high-skilled elite workforce is
likely to become more globally mobile in search for
the most interesting projects and best colleagues
instead of seeking stable long-term employment.
The high-skilled workforce is less likely to commit
to single companies and the competition for the
most talented is likely to increase. Mobility may
also apply for low-skilled workforces, although the
impact on STI is likely to remain smaller. In any case,
the increasing mobility of human resources is likely
to have an impact on STI policies too.
Societies become increasingly active in science,
technology and innovation. Rather than seeing
themselves as passive users and consumers of
available products and services, individuals and
societies become active participants in innovation
processes. This is driven on the one hand by
companies’ interests to better identify true and
more personalised market demand, and on the other
by peoples’ increasing awareness of and interest in
influencing global developments.
Changing societies have a significant impact on
customer markets. Markets become simultaneously
more global and more segmented. For example, the
demand for personal and personalised products
and especially services will increase, and ageing
population will be an increasingly important market
segment in developed countries. Continuous market
re-segmentation is likely to increase the number
of intermediary businesses that serve the needs
of specific customer segments by tailoring and
packaging solutions. On the other hand, low-price
generic products and standardised services become
increasingly available on the internet.
The changing nature of Science, Technology
and Innovation (STI)
Science and technology facilitates much more than
can be turned into innovations. Our ability and
willingness to adopt new products and services has
become the deciding factor in innovation. This has
increased the importance of the user context in STI,
i.e. involving end-users in R&D. It has also brought
ethical, moral, religious and other related topics
onto the table.
Whereas one could call the social acceptance of
technologies social transfer costs, there are also
economic transfer costs. Some technological systems
include high infrastructure costs, i.e. the threshold
of changing to a new technological domain is high. A
good example of this is the transport of people and
goods. The technologies to replace currently-used
fossil fuels are available, but the costs of replacing
the current infrastructures are too high.
Some technological systems also require an initial
investment that any single private actor cannot
economically justify. A good example of this network
factor is the internet. At the beginning, when the
network is small the costs of setting up and running
the network far exceed the benefits. Once the
system reaches a critical size, all present and new
actors joining the network will benefit.
Innovations today originate largely from new
applications of existing or incrementally-developed
technologies. Innovations based on new scientific
discoveries are rare, but they can cause radical
changes in specific industries and markets. ICT
is currently the main technology that leads into
new applications and incremental innovations. It
is likely that ICT will continue to be one of the key
technologies for a long time.
Bio- and nanotechnologies on the other hand are
still emerging technologies. Furthermore, it is not
yet obvious how these technologies will change
businesses and markets. What is certain, however,
is that the development and adoption of these
technologies can eventually lead to significant
changes in many markets, e.g. in healthcare.
Most innovations originate from new applications or
rather new combinations of existing technologies.
This has increased the importance of the
multidisciplinary approach in scientific and industrial
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Polarisation is taking place in all aspects of the
economy and society. Regional development is
polarised in fast growing centres of knowledge and
skills and less developed regions. Labour markets
are characterised by the shortage and mobility of
high-skilled human resources, and at the same time
unemployment among the less-educated workforce.
The lack of knowledge society skills is likely to lead
to an increasing digital divide.
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research. This poses an increasing challenge
especially for universities and research institutes.
on applications rather than on platform technologies
themselves.
Producing systems and solutions rather than standalone equipment, machinery, software or services has
led to convergence. The key enabler of convergence has
been ICT and the increasing intelligence of equipments
and machinery. Standardisation is the other key enabler
of convergence. Convergence produces platforms
and infrastructure which allows the development of
compatible products and services.
Different forms of open innovation and voluntary
standardisation likely to gain ground, especially in
platform and enabling technologies. Constructing
and bringing interesting problems to the public
domain can be an efficient approach to enhance STI.
Setting up open platforms can be an effective way
to reduce costs and speed up the development of
many applications. Open innovation also facilitates
collaboration and shared development.
Convergence and the creation of various platforms
and infrastructure are also changing the nature of
innovation. Individual new products and services
must be compatible with the other products and
services in a specific context of use. This facilitates
the emergence of more systemic innovations, i.e.
new concepts, systems or solutions consisting of
several product, service, marketing and business
innovations. It is obvious that the more systemic
innovations require more extensive networks of
companies, research institutes, universities and
even public sector organisations as well as a
combination of different scientific disciplines and
technologies.
The growing economic importance, increasing
competition and internationalisation of services,
as well as the growth of service activities within
manufacturing, have started to bring service
innovations to the STI policy agenda. R&D in
services is somewhat different from traditional
R&D in manufacturing. One of the key differences
is the emphasis on co-production, i.e. services are
produced together in interaction with the customer.
However, R&D in manufacturing is gradually realising
the importance of co-development with leading
customers and the importance of understanding the
end-user context.
The importance of systematic STI in services is
likely to increase. This is due to globalisation and
increasing competition, as well as the integration of
services into manufacturing. Innovation in branding,
service concepts and business models becomes
increasingly important across industries.
The increasing importance of end-user context
and systemic innovations are also driving open
innovation. New platform technologies are brought
earlier into the public domain to allow for the
development of various applications. New official
and de facto standards are designed in large
consortia including all or most of the leading MNCs.
This means that competition and innovation focuses
As was discussed earlier in the context of
globalisation, business and innovation activities
take place in networks and clusters. Networks and
clusters form systems within which companies and
other actors take different complementary roles. This
leads to specialisation and the division of labour.
It also leads to enhanced interaction between the
closest organisations in the network, which often
locate their activities in close proximity.
STI is likely to become an increasingly collaborative
and networked activity. This will probably lead to the
increasing specialisation of different roles in STI. The
number of companies specialising in R&D is likely
to increase and cover more industries than before.
Different forms of strategic alliances are likely to
increase.
Competitiveness is likely to be based increasingly on
specialisation, applications, segmentation, business
models, etc., rather than on mere technological
leadership. The importance of non-technological
forms of STI is likely to increase.
Dynamic leading research environments are likely to
attract the best brains. US universities have so far
been much more dynamic than European universities.
The ability to experiment and renew institutional
structures is one of the key reasons why US
universities have been able to attract top scientists
and innovative companies all over the world.
Increasingly application- and mission-oriented
research environments demand new combinations
of different disciplinary knowledge and skills.
Education systems and curricula must also provide
better capabilities for multidisciplinary research.
Changing demands and dimensions of
governance
The liberalisation of trade and the internationalisation
of businesses challenges national governments.
Global challenges emphasise the role of international
governance. Climate change, crime and terrorism,
genetic modification, space exploration, etc., are
all issues which require sufficient international
agreements and governance structures.
The increasing importance of international and
regional governance has led to multilevel governance
structures, where the role of national governments
has changed from a direct market actor and regulator
to a more indirect facilitator. At international
forums, national governments try to ensure that
their national interests are taken into account in
international decision-making. On the other hand,
national governments try to help regions develop
attractive and encouraging environments for STI.
However, even though the emphasis has changed
towards international and regional governance,
national governments still have a major role in the
multilevel governance system.
One further aspect of international governance
deserves attention. That is the control of liberalised
markets. There is an increasing emphasis on selfregulation and public-private partnerships. Instead
of heavy public control structures, market regulation
is increasingly based on guidelines and voluntary
self-regulation. Guidelines and standards are
typically prepared in consultative and interactive
processes between public and private actors. Selfregulation also emphasises the awareness and
sophistication of consumers. This is likely to further
increase the role of various consumer-based NGOs.
The increasing importance of STI and its central
role in policy, as well as rising education levels
and awareness of STI among citizens, is increasing
the demand for transparency and accountability
in STI policies. The consistency and predictability
of policies are also increasingly important in a
continuously changing and globalising environment.
Companies and citizens should be able to trust
that the STI policies are able to ensure the quality
and development of their operating and living
environment. Although this is not the same as
trust in government and public institutions, trust
is a definite strength in a knowledge economy and
society.
In Europe, the European Union establishes a
specific framework of international governance.
The European Commission activities, aiming at the
development of common European markets, provide
a basis for economic regulation. The Commission is
also the voice of Europe in many international fora
dealing with competition regulation, environmental
agreements, etc.
It should be recognised that there are significant
differences in national governance structures.
Regional autonomy, especially, varies a lot across
countries. The role of national government is
decidedly stronger in centralised countries with
less regional autonomy, whereas in countries with
strong regional autonomy, the role of the national
government is typically more limited.
Various forms of international governance are likely
to become increasingly important as businesses
become more global. At the same time, local and
regional governance structures gain more importance
in the competition for the best companies and best
brains. Ensuring the coherence of policies within
the multilevel governance structures and processes
becomes increasingly challenging. National
governments have a dual role in coordinating
policies and policy measures and in ensuring
national interests at the international level.
Different processes and structures, facilitating
public-private dialogue in STI policy design and
implementation, are likely to emerge and develop.
How they will develop will depend largely on the
cultural, political, economic and social context. As
NGOs become more important and institutionalised,
the most powerful are likely to be recognised as
potential STI policy actors.
The role of expert knowledge in STI-policy processes
is likely to increase. Governments and ministries will
have to ensure their access to sufficient expertise.
The role of various advisory bodies is likely to
increase. This, however, increases the danger of
legitimatisation and misuse of science to serve
various political purposes. This would subsequently
encourage lobbyist and opportunistic behaviour and
a drive towards old industrial policy.
STI relies increasingly on the actual STI performers,
which can locate their activities globally.
Commitment of STI performers to STI policies and to
the development of the innovation system is likely to
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On the one hand, economic regulation is changing
as more and more decisions must be taken at the
international level. Ensuring fair competition on
global markets by means of competition regulation
is one good example. On the other hand, the role
of regions in developing attractive environments
for innovation is increasing. National governments
must adjust their role and respective governance
structures accordingly.
The Future of Key Research Actors in the European Research Area
become increasingly important. The quality of STIpolicy processes is therefore becoming as important
as STI policies themselves. Continuous renewal
and adaptive capabilities are likely to be the most
important characteristics of innovation systems.
2.2 Internal drivers
The need for a more effective and efficient use
of resources
Simultaneous global competition, leading to (for
example) lower taxes and the spending pressures
of demographic change, means that national
governments must do more with fewer resources.
This requires more effective and efficient public
sector and policies.
One answer is improved policy coherence. Avoiding
conflicting policies improves policy effectiveness
and efficiency. This requires an optimisation of the
mix of policies instead of single policies or policy
measures.
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Another answer is maximising the leverage of public
investment through various forms of public-private
partnerships. The role of private companies in
providing public sector services such as education,
healthcare, welfare and infrastructure is increasing.
Different STI-related incentives and schemes also
aim at leveraging public funding, e.g. in the form of
venture capital.
Pooling resources for strategic purposes is also
becoming increasingly common internationally,
nationally and regionally. Big science efforts are
leading the way internationally. National and regional
foresight and strategy processes are attempting
to identify focus areas for future development and
major investment.
Need for better public management
New public management, with an increasing
demand for transparency, openness and
accountability, is winning ground. The problem
with how new public management has been
implemented with regards to STI is that
accountability has been interpreted as enhanced
operational control over government organisations.
STI policy objectives should basically be based
on strategic long-term systemic impacts, which
can be achieved only through an appropriate mix
of policies and policy measures delivered by a
number of different organisations. If operational
control of single government organisations and
single policy measures cannot be seen in this
wider context, enhanced accountability can easily
lead to sub-optimisation and subsequently to a
reduced policy impact on the systemic level.
Accountability at the systemic level requires
enhanced strategic intelligence capabilities and
a systemic and holistic policy approach. Systemic
accountability also emphasises the focus on policy
(and innovation) processes rather than individual
organisations. Even though productivity and the
impact of individual government organisations and
policy measures is by no means less important,
the real policy impact depends increasingly on
how the complete STI policy mix is designed
and implemented. The role of single government
organisations and policy measures must be
evaluated and developed in the context of the whole
innovation system and STI policy mix.
A further challenge of STI policymaking is the
awareness of STI among citizens. Political debate on
various social, environmental and economic issues
can be and is typically relatively transparent and
open. This is possible because citizens have some
level of awareness, understanding and personal
experiences related to these issues. The level of
awareness, understanding and personal experiences
related to STI, on the other hand, is typically much
more limited. However, the importance of STI also
increases in other policies. It is therefore important
that the awareness of STI among citizens increases.
Otherwise there is an increasing risk that political
discussions and subsequent decisions on STI-related
issues are not based on actual knowledge and
understanding, but based on misconceptions. This
kind of development could lead to the degradation of
the appreciation of scientific and expert knowledge,
and make STI policies a playing ground for lobbyists
and political interest groups.
Need for coherent and understandable
policies
In multilevel governance structures, the coherence
between different-level policies becomes crucial.
National-level policies should make sense of
the combination of international, national and
regional policies and ensure their coherence. This
is vital in avoiding conflicting and ineffective policy
combinations.
Openness, transparency and interaction are important
in ensuring that policies are understandable, and
that the key stakeholders are sufficiently committed
to them.
Need for more knowledge
sophisticated understanding
and
increasingly
Policymaking in a continuously changing global
environment requires increasingly sophisticated
knowledge and understanding of the key drivers
and factors that affect the development of the
environment. This emphasises the need for
better policy processes and more knowledge in
policymaking. It also emphasises the need for
continuous learning.
Governments need to design policy processes
so that they capture the necessary knowledge
and understanding for policymaking. Strategic
intelligence becomes increasingly important as
does the involvement of all major stakeholders.
Systematic processes for collecting and analysing
policy-relevant knowledge, such as policy-relevant
research,
foresight,
evaluation,
technology
assessment as well as the use of various advisory
bodies, etc., are becoming more and more
important.
In the 1980s, technology assessment was very much
the focus of strategic intelligence, whereas evaluation
gained most of the attention in the 1990s. After 2000
the focus has gradually shifted to foresight, which
has to some degree replaced earlier science and
technology-watch activities. Business intelligence is
likely to gain more attention in the future. However,
the real challenge is to establish efficient knowledge
management processes for analysing the knowledge
produced by these strategic intelligence processes,
and extracting the relevant core knowledge for the
design of STI policies.
In order to design, implement and continuously
improve policies and policy processes, a
policymakers themselves require significant skills.
National governments, including parliaments,
ministries and agencies, must acquire sufficient
knowledge and skills and keep them continuously
updated. This requires the availability of skilled
human resources specialised in STI policies.
Need for continuous learning
The international environment is continuously
changing at an increasing speed. Government
organisations must respond to these changes.
This means that their structures and processes
must be adaptable, flexible and agile. Moreover,
these requirements apply to the whole innovation
system.
The importance of adaptive capabilities enhances
the need for strategic intelligence and knowledge,
and the skills of government organisations. It also
emphasises the importance of continuous learning
processes. Some of the potential approaches
are systemic evaluations (policies, mix of policy
measures, etc.), national foresight exercises and
policy experimentation.
One of the key challenges is to integrate the
adaptability to continuous change with the long-term
stability necessary for long-term STI. Stability might
be understood as an attempt to preserve the status
quo of things, which is not realistic in a continuously
changing environment. The key is predictability,
i.e. all stakeholders should be sufficiently able to
predict the direction of future STI policy changes.
This again emphasises transparency, openness and
accessibility of STI-policy processes.
Learning from good practices can be an efficient
and effective way of improving STI policies and the
innovation system. However, the successful adoption
of good practices developed elsewhere requires
a sufficient understanding of the political, social
and business cultures and their differences. Good
practices can rarely be copied, but can often provide
an excellent base for learning and good ideas for
improving policies and policy delivery.
2.3 Key policy implications
Companies and their business activities are
international and mobile. This means that national
governments can have limited possibilities to
influence them. For example, imposing restrictive
regulations or using some other hard policy measures
will most likely cause companies to relocate their
business activities elsewhere, rather than adopting
their activities to the new regulations.6 National
6.This naturally depends on the actual (or predicted) transaction costs. If the
costs of staying and adapting to new regulations (including possible costs
of potential future regulatory reforms) is lower than relocation (including
the likelihood of regulatory reforms in the new host country), staying would
probably be a more likely decision (unless there are other reasons for
relocation).
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National governments must also balance between
different policies. The mix of policies should
be sufficiently balanced to ensure sustainable
economic, social and ecological development. This
means balancing between, for example, creating
new vs. renewing existing industries, ensuring the
availability of high-skilled human resources vs.
creating jobs for low-skilled workers, developing
internationally attractive centres of knowledge vs.
balancing regional development, etc.
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governments should therefore focus on softer policy
measures.7
polarisation, demographic change, etc. have a direct
policy implication.
All countries and regions want to attract the best
companies to ensure economic growth. This leads
to competition between national governments and
regions. Success in this competition relies on a correct
understanding of the relocation drivers of specific
business activities8, and the appropriate policy
measures targeting the respective characteristics in
the business and innovation environment. National
governments will have to find appropriate strategies
for improving the attractiveness of their national
business and innovation environment.
National governments are facing multiple
challenges, which require balanced policies between
facilitating change and controlling polarisation.
Some of the changes impose a serious challenge
on public services, especially an ageing population
on healthcare. National governments must find
policies to cope with increasing demand for services
in the context of limited resources. Knowledgeintensive businesses increasingly require skilled
labour. Governments are faced with the challenge
of matching education, immigration, research and
labour market needs. Social changes, polarisation,
immigration, etc., emphasise the need for coherence
across policies.
Companies do not operate business activities in
isolation. Policies must recognise the appropriate
collaborative linkages, networks and clusters. These
are simultaneously local, regional, national and
international, between small and large companies,
between companies and research institutes and
universities, between the private and public sectors,
etc. Policies cannot be effective if they only target
single companies. National governments must have
coherent STI policies, which build on sufficient
insight into the context, i.e. the various needs of the
economy and society.
Private resources far exceed the resources of
national governments. Increasing private capital
flows can cause significant shocks to the national
economy, especially direct investments in footcloose
business activities. Policies should therefore
encourage long-term commitments and partnerships
rather than focus on attracting short-term foreign
direct investments.9 National governments should
build policies which are based on leveraging public
investments through various forms of public-privatepartnerships and which would encourage companies
to integrate their business activities to the local
(national) environment.
Some of the social changes have a direct impact
on policies, whereas others have more impact on
markets. Individualism, personal self-expression,
new virtual communities have a stronger impact on
market behaviour and market structures, whereas
7.Harder policy measures can basically also be applied, but in most cases
effective implementation requires some form of international agreement.
Standardisation and industry good practices have proven to be effective
approaches in many cases.
8.The actual relocation drivers and their relative importance vary between
industries, types of business activities, etc. as discussed earlier in this
paper.
9.A case can be made for policies attracting footloose FDI using taxschemes, grants, special economic regions or other highly-lucrative
financial measures, as a temporary short-term measure in a catching up
stage. However, this should be complemented with other policy measures
targeting longer-term development.
One of the key policy implications of the changes
in the nature of STI is the need to understand the
dynamics of the complex networked structures of STI
internationally. STI networks are constructed around
key nodes, i.e. stronger centres with the appropriate
characteristics conducive for the specific STI activity.
These characteristics make the centres specifically
interesting for longer-term knowledge building,
introducing and experimenting and entry to leading
markets, or for the localisation of products, services
and concepts. These centres will attract most of
the best companies, researchers and activities.
Other network actors must create good linkages
to these centres. STI policies should support both
the creation and development of these centres as
well as collaboration between other network actors
internationally.10
Another policy implication is the need to facilitate
experimentation and the creation of pilot
environments and test-beds that can be used to
simulate user context. Policies should facilitate
and support the development of various physical
or virtual platforms for experimentation and codevelopment. Some of the potential policy measures
include public procurement and public-private
partnerships in developing public-sector service
systems or infrastructures.
The need for international level collaborative efforts
to overcome the network factor or the infrastructure
transfer costs and the need to raise public awareness
10.Policies for the internationalisation of R&D typically define two main
objectives – attractiveness and absorptive capacity. Attractiveness consists
of measures targeting the development of the national innovation system
so that it would be attractive for leading international companies and their
STI activities, as well as top international researchers. Measures targeting
absorptive capacity consist of incentives and other activities encouraging
international collaboration and the exchange of human resources. The
discussion of networks and centres here covers both of these aspects.
of STI in order to facilitate public discussion are also
important policy implications.
3. Future outlook
The key policy implications related to multilevel
governance structures are the changing role of
government and the need to coordinate between
policies at different governance levels. The main
role of government is to be a facilitator rather than
a regulator or a market actor. This emphasises
the need for softer policy measures as well as
transparent and open policy processes. Especially
since STI requires long-term investments, those
investing in STI must be able to trust that policies
are consistent and predictable in the face of
inevitable future changes.
3.1 Quality of STI-policy processes11
National governments face the challenge of ensuring
that international, national and regional policies
and policy measures are sufficiently coherent.
This is not the sole responsibility of national
governments, but their central role in the multilevel
governance structures emphasises the importance
of coordination specifically at national level, even in
countries with stronger regional autonomy.
Internal drivers emphasise the importance of
developing open and transparent policy processes
with stronger strategic intelligence and accessibility.
Furthermore, policy processes should cover all
relevant aspects of STI, which requires sufficient
horizontality across policies and sufficient verticality
across governance levels.
National governments should put more emphasis
on developing their own STI policy capabilities.
Government organisations should ensure the
availability of skilled human resources for STI
policymaking and the ability to attract them.
There is a need to raise the awareness of STI among
citizens in general and among all policymakers, and
the need to adapt new public management principles
(accountability, transparency, openness, etc.) in the
context of systemic and holistic policies.
Policy processes are becoming more important
than structures in STI policies. The design and
delivery of STI policies is more dependent on proper
processes than structures. This is mainly because
the effectiveness and efficiency of STI policies relies
increasingly on a widespread commitment across
major stakeholders, increasing numbers of which
are non-governmental organisations. STI-policy
processes can ensure commitment through sufficient
transparency and access.
Efficient and effective policies rely on appropriate
in-depth knowledge of the current and future needs
of STI. It is therefore important to benefit from the
collective understanding of all stakeholders, both
public and private. This requires interactive policy
processes, in which the knowledge of various
stakeholders can be transformed into a common and
shared understanding.
Government organisations can have an important
role in creating open or semi-open neutral platforms,
where companies and research organisations can
interact, form alliances and networks, identify
common objectives and engage in joint STI efforts.
These platforms can have a significant role in
enhancing knowledge transfer and subsequently STI
within the innovation system.
Besides the quality of policy processes, agility is
also important. Processes must ensure sufficient
flexibility and continuous learning and renewal.
Policies should be consistent and coherent and leave
room for experimentation and learning. Ensuring
11.The strength of the process approach is that it emphasises various roles,
interactions and functions rather than organisational structures. It allows
for the inevitable variety across national and regional structures, while
providing a basis for more general recommendations.
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Commitment, partnerships and trust can only be built
in open and transparent processes. This emphasises
the need for governments to base policies on a
sufficient understanding of the national needs
and recommendations resulting from interactive
consultation with all key stakeholders.
The requirement for increasingly holistic policies
emphasises the need for better knowledge
management among government organisations.
A holistic approach in STI policy design and
implementation requires a deeper understanding of
the cultural, social, political and economic context in
which policies are delivered. Furthermore, there is a
need to understand and predict changes in the global
and local innovation environments and innovation
processes and the related structures. Strategic
intelligence processes – such as foresight and
assessment – are therefore becoming increasingly
important.
The Future of Key Research Actors in the European Research Area
continuous development of the innovation system
requires sufficient adaptive capabilities.
The efficiency and effectiveness of STI-policy
processes require effective and efficient
structures. Over a decade of innovation systems
research has revealed that there is no single
optimal governance structure, but that the
efficiency and effectiveness of governance
structures and processes is highly dependent
on the cultural, political and social structures
and their historical development. However, some
general trends can be identified.
Holistic approach requires sufficient coordination
mechanisms. These can be structured in different
ways. National policy councils have been set up in
many countries to help improve STI policy coherence.
These councils can either make recommendations or
act as governmental decision bodies. Some countries
have restructured ministries and integrated all or
most STI under one ministry.
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Attempts to improve horizontal coherence at the
implementation level have in many countries led to
the integration of agencies. This has been achieved
either by collecting independent agencies under
one coordinative agency or by merging previously
separate agencies. Sometimes these agencies serve
one ministry, sometimes many ministries.
Vertical coherence in the national context can be
strengthened by enhancing the interaction between
ministries and agencies. Ministries can better
benefit from the knowledge and skills of agencies
and agencies can better access strategic intelligence
and policy design processes.
The increasing need for strategic intelligence
requires sufficient knowledge and skills within
government organisations, in designing and
coordinating these processes, in commissioning
relevant research and studies, and in acquiring
and processing appropriate knowledge. This can
lead to setting up specialised policy research
units or institutes. The benefit of specialised units
or organisations is that they can concentrate on
collecting and analysing policy-relevant knowledge
independently from agencies and ministries, which
are responsible for policy implementation, and thus
increase the transparency and reliability of policy
processes. Specialised units or organisations
can also act as demanding customers for
methodological development, thus enhancing the
development of new and improved methods for STI
policy-relevant research.
Partnering with private companies and NGOs was
already discussed earlier. One particular aspect to
partnerships is the ability to maximise the leverage
of public funds. One approach is to collaborate with
private banks and investors though guarantees,
interest subsidies and shared investments. Another
is to set up special funds or foundations based
on public-private shared investment. In any case,
the capabilities of managing (or orchestrating)
networks of public and private organisations
become increasingly important for government
organisations.
The current trend of new public management
emphasises, for example, accountability and
transparency. The misinterpretation of what
accountability means in STI can cause suboptimisation and subsequent ineffectiveness
and inefficiency in the innovation system. It is
vital that accountability as well as effectiveness
(and efficiency) is defined and enforced first and
foremost at the systemic level. The accountability of
individual organisations and policy measures should
be analysed in the context of the whole system and
STI policy mix.
3.2 Blurring systemic boundaries
Traditional boundaries of the national innovation
systems are gradually changing, blurring and even
disappearing. The production of new knowledge
is not limited to universities and public research
institutes. New knowledge is increasingly produced
in complex networks of universities, research
institutes, companies and other STI performers.
Knowledge production is a collaborative and
interactive process, which challenges traditional
boundaries between knowledge producers and
knowledge users. The same applies to industrial
R&D, where various networks of subcontractors,
customers and competitors collaborate in complex
interlinked processes for delivering innovations.
Higher education is already interlinked with STI
– large numbers of theses are made in connection
with scientific research or industrial R&D. The
growing need for life-long learning will emphasise
this linkage and extend it to cover a larger part
of the whole education system. Issues such as
entrepreneurship and appreciation, awareness and
the potential of STI, are brought earlier into students’
curriculum, thus facilitating the linkage between
education, research and innovation even further.
STI policies are becoming increasingly aware of the
importance of service innovations, organisational
Speed, appropriate timing and systemic fit are
becoming increasingly important in innovation.
Speed is achieved through parallel innovation
processes and networking. This means that basic
research, applied research, industrial research,
product development, marketing, logistics, design,
etc. are all done in parallel. This blurs boundaries
between basic research, applied research,
industrial R&D, etc.
Companies are increasingly networked. Their
competitiveness, position in value chains, access to
various markets, ability to innovate, etc., increasingly
depends on the quality of networks. Networks
and clusters span across regional and national
boundaries. This challenges STI policies, which have
to acknowledge and address complex networked
structures instead of single companies.
Globalisation of businesses and the emphasis on
softer STI policy measures increases the importance
of self-regulation. This can strengthen the role of nongovernmental organisations and industry or clusterwide collaborative and coordinative structures, such
as EFQM, ICRA, IATA and AESGP. Consumer groups,
environmental groups and other special interest
groups also set up NGOs. These can also influence
the attitudes and opinions related to STI. Thus, there
is a need to recognise the appropriate NGOs in STIpolicy processes.
Companies and most of the NGOs are either
international or at least tightly linked to global
networks. This means that the role of international
policies and agreements increases. This emphasises
the role of international governance in issues such
as environmental regulations (e.g. climate change),
fair competition (e.g. WTO rules), etc. At the same
time, innovative environments are still largely
physical although they also contain virtual elements.
This emphasises the role of regional and local
governance. National governments and governance
are challenged by the increasing importance of both
the international and regional level in STI policy
governance, and the need to ensure coherence
between different level policies. From the STI
performers’ point of view, this blurs boundaries
between local, regional, national and international
governance.
Companies are increasingly customer-oriented
and seek longer-term partnerships rather than
mere seller-buyer relationships. Competition
between innovation environments (or innovation
systems) will most likely enhance a similar
interaction between government organisations
and companies. Longer-term partnerships are
preferred over short-term projects. This is likely
to lead to an increasing number and new forms
of public-private partnerships and procurement
arrangements, as well as consultative policy design
and implementation processes. The challenge in
this development is to design partnerships and
other collaborative arrangements which, while
blurring some of the boundaries between public
and private, clearly define the appropriate roles of
public and private actors.
As
government
organisations
focus
on
facilitating innovation and developing the
innovation system, the need for private services
for innovation increases. The role of private
companies and public-private partnerships will
become increasingly important in policy delivery.
Mediation services (e.g. brokering, networking),
expert support services (e.g. mentoring, training,
consulting) and some financial services (e.g.
venture capital, loans, guarantees) are especially
likely to be funded through such schemes, where
the actual implementation relies on private
companies, public-private partnerships or NGOs.
3.3 Attractive environments for innovation
Current trends will eventually lead to a situation
where the markets for manufacturing, services
and STI are global. Private companies will locate
their activities based on the attractiveness of the
environment for any particular activity. Although
national governments can still control the location,
and to some extent the direction, of STI of publiclyfunded STI organisations, such as universities and
public research institutes, students, scientists and
other skilled STI professionals will decide, much like
private companies, where they want to locate.
As the global economy becomes increasingly
knowledge-intensive, economic growth of any
nation or region will eventually depend strongly
on the quality and volume of knowledge-intensive
companies’ activities they can attract, as well as
on the quality and volume of appropriately-skilled
human resources. This leads to an increasing
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innovations and other forms of non-technological
innovations. This emphasises the need for more
multidisciplinary research, which challenges
traditional disciplinary structures at universities.
New platforms and structures are needed to
find better ways to facilitate interdisciplinary
interaction, which blurs traditional disciplinary
boundaries.
The Future of Key Research Actors in the European Research Area
global competition for the best companies and
best brains.
which cannot offer large markets but could possibly
offer more dynamic and sophisticated lead markets.
Systems approach is a powerful tool for
understanding the attractiveness of an innovation
environment. An innovation system can be divided
into 5 main parts:
Emphasis on softer policy measures and
facilitation, holistic approach in policy design and
implementation, building longer-term partnerships,
enhanced networking, etc., all emphasise the
need for coherency across STI policies and policy
measures. This requires sufficient coordination
mechanisms across ministries and agencies. One
approach is to build coordination mechanisms by
integrating them into the design and implementation
of STI-policy processes. Another approach is to build
specific coordination structures across ministries
and/or agencies. A third one would be to collect all
STI-relevant activities into a single ministry or agency.
Most solutions will probably be combinations of the
first and second or the first and third.
• knowledge base;
• market conditions;
• knowledge transfer;
• framework conditions;
• learning.
The attractiveness of an environment for STI depends
on factors such as:
• the availability of appropriately-skilled human
resources;
• the quality of STI;
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• access to dynamic and leading markets;
• access to sophisticated demand;
• access to complementary knowledge and skills;
One key challenge for national governments is to
ensure fair and beneficial competition between
regions. Unfair competition between regions is
likely to lead to an ineffective and inefficient use
of public resources. The same applies to the EU
level, where, for example, European competition
regulation and ongoing attempts to unify corporate
taxation and liberalise service markets are aimed at
developing common European markets and ensuring
fair competition between companies, member states
and regions.
3.4 Weak signals
• access to networks;
of
The knowledge intensity of businesses increases.
Knowledge itself is frequently the product or at
least at the core of the product. Globalisation and
the increasing use of ICT and the internet open the
possibility for virtual knowledge markets. Most of
the businesses on internet are based on tangible
products, software or entertainment. Proprietary
databases, business intelligence services and other
related businesses are still relatively small, but their
importance is likely to increase in the future.
As attractiveness becomes the core element in
STI policy, the facilitating role of government
organisations is emphasised. Policies are focused
on improving the attractiveness of the national
innovation environment. Soft and indirect policy
measures, such as incentives, policies targeting
the improvement of various framework conditions,
mediation, brokering and networking activities, etc.,
increase their importance. Policy measures aimed at
enhancing the demand for STI will also become more
important, especially in small countries and regions
Finding the relevant knowledge from the huge
amount of knowledge and the difficulty of verifying
the reliability of knowledge provides a growing
market and significant business opportunities. How
these knowledge markets will develop, what new
business models and value chains will be created,
how these markets should be regulated (forms
of self-regulation, the need for international or
national regulations), will these markets enhance or
limit knowledge transfer (access), etc., will also be
interesting questions for STI policy and government
organisations.
• supportive regulations, advanced standards;
• specific incentives for STI;
• availability of risk capital;
• attitudes favourable for STI;
• continuous renewal and
government policies; etc.
predictability
The customer interface becomes increasingly
multidimensional, integrating many different forms
of interaction in time and space. Communication
systems (internet, mobile communication), media
(news, entertainment and advertising), sociocultural events and various physical environments
specifically designed for marketing and sales
are used in creating brands. Brands become
increasingly customer-tailored solutions (systems)
rather than single products or services. Presence
and reachability become key factors of customer
satisfaction. A lot can be managed over information
and communication networks, but they cannot
completely replace physical interaction. Global
brands must also be locally present.
Competitive markets encourage innovation and
increase market dynamics. This means that leading
companies, at least, must be increasingly agile and
able to change their product portfolio and production
volumes quickly. Some of the agility and flexibility
can be built in product modularity and design and
some in networks. However, capital intensity remains
a challenge, especially in some traditional industries.
One frequently-used approach in some industries is
to combine the investment and the related funding
arrangement. Instead of making the investment and
arranging the funding separately, the buyer makes
only one deal in which the investment and funding are
integrated. Another approach is to use various types
of leasing and other contract-manufacturing-type
deals where instead of manufacturing equipment
and machinery, the buyer acquires manufacturing
capacity. This way, the ownership of manufacturing
and other business facilities, the actual production
activity and the marketed products and services are
separated, thus increasing the flexibility of all the
actors in the value chain (cluster, network). Making
funding arrangements and leasing are likely to be
growing businesses as this trend continues and
reaches more industries.
4. Scenarios
4.1 Introduction
One approach for building future scenarios is
to recognise and analyse four interconnected
development processes. The first of these is a
market-driven process, a process of globalising
markets and businesses driven mainly by economic
interests and private companies. The second is a
socio-cultural process where increasing cultural and
social interaction changes existing and forms new
social and cultural systems, some of which are partly
local and regional and some more virtual in a global
context. This process is driven by societies and their
more or less formal organisations, such as various
types of NGOs, religious organisations and virtual
communities. The drivers of this process are many, as
are the forms and objectives of various organisations
and communities. The third process is a scientific
and technological process, which produces new
knowledge and understanding and creates new
opportunities and capabilities. This process is driven
by academics and academic organisations. The
fourth process is a political process which is driven
mainly by national governments, but also to some
extent by regional and international governance
systems. The process is driven by economic, social
and environmental sustainability and the wellbeing
of citizens.
While there are evident similarities between the
socio-cultural and the political process, the political
process is typically more complex on a practical
level. This is because socio-cultural communities and
organisations can limit their objectives and activities to
specific areas, such as environmental issues, specific
consumer concerns (e.g. food safety) or specific
moral and ethical concerns. Single citizens can, and
often do, belong to several socio-cultural systems
simultaneously. As globalisation progresses and new
generations are exposed to an increasing number of
different socio-cultural communities, people build
their identities as a combination of these. In any case,
people can make a conscious decision to join or not
to join a community and to what extent they choose
to embrace their value systems. The political process
cannot choose to limit objectives or activities as much
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The need for self-expression and the ability to
personalise products and services increases. At the
same time the number and characteristics of different
cultural and social systems change. Products and
services must be designed to cater to an increasing
multitude of needs and socio-cultural systems.
While this development encourages innovation and
uniqueness, and therefore the possibility to get
higher prices for high-end products and services,
increasing competition pushes for lower prices and
increasing productivity. This leads to increasing
modularity, standardisation, and the development of
shared technological and systemic platforms. Market
differentiation becomes increasingly based on
design and the ability to tailor to specific contexts of
use (branding), rather than on unique technological
features.
The Future of Key Research Actors in the European Research Area
as socio-cultural processes. The key characteristic of
the political process is that it deals with many and
conflicting objectives.
Another important issue deserving to be
recognised is the fact that all processes besides
being interconnected proceed at a different pace
at different times. Changes in belief systems and
cultural behaviour are typically slow, but can
accelerate significantly under specific conditions.
Markets and business systems are typically able
to change much faster than political systems, but
barriers such as existing infrastructure or limited
access to markets can slow changes significantly.
Changes in systems, especially political and sociocultural ones, and also to some extent scientific
and even business ones, are path-dependent. This
means that, even though the reasons for changes
taking place can often be quite widely foreseen, how
changes actually take place in a specific context and
what their impact to the relevant systems are can
differ very much between contexts and can often be
surprising in many ways.
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What this means in practice is that while it is
relatively easy to build long-term overall visions of
the knowledge economy with structures, institutions,
roles of different actors, etc., it is significantly more
difficult to capture the true multiplicity and variation
between real systems, institutions, structures and
interactions at a given time in the future, when these
systems are at different stages in their development
towards their interpretation of a knowledge economy.
Some economies and systems are approaching their
vision of the knowledge economy, whereas others
are simultaneously struggling to get started.
The practical implication of this is that different
countries, regions and industries are going to be at
different stages of development at any given time,
both today and in the future. It is, thus, a rather
challenging task to build scenarios for specific
organisations, because these organisations operate
in different environments in different countries
and industries. National governments in particular
need to design and implement policies and set up
structures and institutions which make sense in their
particular context. This inevitably means a variation
in policies, governance structures and institutions.
One of the objectives of building scenarios is to
try to identify discontinuities and how they could
affect various systems in the future. Discontinuities
typically arise from specific combination of events
and interactions between the different processes
discussed above. While it is difficult to foresee the
actual time and place of discontinuities, scenarios
can help identify conditions and interactions which
could increase the probability for specific types of
discontinuities.
The scenarios discussed in this paper are trying to
picture possible futures for national governments
in the European Research Area in the year 2020.
Due to limited resources available for this work,
it was impossible to fully examine and analyse
the meaning and impact of current and possibly
enforcing or even new trends in the full context of
all four types of interconnected processes described
above. The scenarios are mere snapshots based
on several assumptions, most of which assume
the continuation of current trends or that current
systems remain more or less untouched. For the
same reason, no particular attempt has been made
to identify or analyse potential discontinuities.
However, in case the potential for a discontinuity has
been identified, it is briefly mentioned in the context
of the specific scenario.
Of the four types of processes discussed earlier,
these scenarios concentrate on the impact of changes
arising in the political process and more decisively
on those political processes related to science,
technology and innovation in the general context
of the European Research Area. The scenarios do
not contain any analysis or discussion of any other
aspects of political processes. The discussion and
analysis of the changes arising from the scientific
and market-driven processes is limited to current
and emerging trends and their impact on innovation
systems. The discussion and analysis of the changes
arising from the socio-cultural processes is limited
to the impact they have on market-driven processes
and how that reflects on the policy processes.
These scenarios are built by focusing on STI-policy
governance processes and structures and on the
roles and activities of government organisations.
The rationale for choosing this approach is the fact
that the actual organisational arrangements and
policy measures are and should be tailored to the
particular needs of a specific country. There is no
single optimal innovation system structure or STI
policy mix for all countries. Each must find their
own. However, there are lots of similarities and
common challenges in policy governance processes
and structures as well as in the role of government
and STI policies in the knowledge economy.
It should finally be noted that the real challenge
in many cases is to find the appropriate STI-policy
governance structures and processes which facilitate
4.2 Global context of STI in 2020
Although the market-driven process, as well as
the socio-cultural process, is affected by political
decisions, the main trends can be assumed to
continue globally, regardless of changes in STI
policies and government organisations and their
activities in Europe. It is therefore possible to
make some general predictions of what the STI
environment (and to some extent the related policies
as well) are likely to look like in 2020, and thereby to
set the overall scene for the scenarios, which look
more closely on the role and activities of national
government organisations in the context of the
future European Research Area.
Large multinationals and their networks control global
markets. Networks are multilayered, consisting of
various business and innovation activities. Research,
development, innovation, manufacturing, marketing,
financing and other company activities are located
in dynamic environments which offer particular
competitive advantages for these activities. Industrial
structures consist of clusters and networks rather
than individual companies. Competitive advantages
are built in networks rather than based on the
capabilities of single companies. Single companies’
competitiveness and growth is increasingly dependent
on access to and the success of networks.
Network-based structures enhance specialisation.
The number of companies specialising in R&D,
knowledge production, knowledge transfer and
trading knowledge has increased significantly.
Global competition has enhanced innovation and
productivity growth. Innovation processes are
continuous, global, 24/7 processes. Innovation is
an increasingly systematic, structured and open
activity. Competitors as well as public and private
actors join forces in creating and developing open
technological and systemic platforms. This allows
large number of companies to develop innovative
products and services using the same platform, thus
ensuring compatibility and enhancing collaboration.
Corporate R&D is seen in the context acquisition,
adoption, transfer and utilisation of knowledge
and skills, i.e. in a wider context of knowledge and
skills management. Companies frequently form
collaborative arrangements, and buy and sell options
and ownerships to specialised R&D companies and
projects in their R&D portfolio in the global markets.
Methods and models for valuating knowledge and
skills (intangible assets, intellectual capital) have
consequently been developed.
The role and importance of NGOs has increased
and they can have a significant influence on market
behaviour. Companies have widely recognised the
importance of NGOs and corporate responsibility.
NGOs’ development is partly a result of failure to
establish and strengthen international governance
structures. The area of international governance
that is likely to have strengthened is related to big
science, i.e. joint international scientific efforts.
Socio-cultural diversity has increased and
subsequently so has market segmentation. The
most successful innovation processes have extended
beyond merely surveying user needs to the real
context of use. On one hand, innovation in production,
logistics and technological platforms is very much
open and collaborative between companies and
public research organisations. Innovation in products
and services, on the other hand, is increasingly open
to, and shaped by, user communities.
Universities and public research institutes compete
globally for the best brains and companies. Highlevel STI is increasingly concentrated globally into
leading centres, where new and evolved forms
of public-private partnerships emerge. The best
brains are increasingly mobile, frequently work in
environments where public and private actors have
joined forces and move fluently across public and
private interfaces.
The attractiveness of countries and regions for
STI activities is largely decided on by their ability
to create attractive environments with specific
competitive advantages. This can be, for example,
scientific or technological excellence, innovation
excellence or access to dynamic lead markets and/
or innovative and adaptive user communities.
Market-driven process has an increasingly stronger
influence on STI activities. STI policies focus, on the
one hand, on enhancing and facilitating innovation
capabilities and innovation processes and, on the
other hand, on targeting STI on major social and
environmental challenges. Science and education
remain mainly the responsibility of the public sector,
although new forms of public-private partnerships
start to emerge.
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and drive the desired transition towards a knowledge
economy. Managing the transition and continuously
adapting STI-policy processes and STI policies to
facilitate a balanced, sustainable and predictable
development is the true challenge for government
organisations.
The Future of Key Research Actors in the European Research Area
Government can have many roles in STI. It can
simultaneously be a facilitator (institutional
structures, incentives, etc.), manager (allocation of
public resources, public procurement, education and
science, mediation, coordination, etc.), controller
(regulations, standards, etc.) and partner (publicprivate partnerships, joint university-industry
platforms, etc.). The government can also be a
key player in creating a lead market by acting as a
demanding customer for new products, services and
systems (solutions). On the other hand, governments
also have to protect national interests.
STI policy measures are increasingly soft and indirect;
based more on incentives, facilitative activities and
demand-side measures (e.g. procurement), rather
than on regulation and direct action. The aim is to
build relative competitiveness of the innovation
environment in the global context, and to ensure
the fluent transfer of knowledge and skills widely in
the economy and society in order to maximise the
impact of STI on the society and economy.
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STI policies are increasingly integrated into a wider
policy context to ensure the coherence of different
policies and policy measures. STI policy governance
processes have received increasing attention,
especially strategic intelligence and coordinated
policy implementation.
4.3 Scenario A: Business as usual
This scenario is based on the assumption that
current trends are expected to continue and that
no significant changes in the role and activities of
government organisations are to be expected.
STI policy and measures in the national
context
While the role of STI policies in member countries
varies, it does not gain a very high priority. STI
policies are mainly seen in the context of economic
growth and competitiveness, not in the wider
context of providing solutions for major social and
environmental challenges.
Education policies target scientific careers, attracting
students to science, engineering and natural
sciences, etc. Education systems focus on traditional
disciplines and remain somewhat detached from
life-long learning, which is still formal, separated
from working life, and weak.
Research policies target knowledge production and
especially collaboration and networking. Technology
policies focus on networking, collaboration, the
transfer of knowledge, high technology, etc.
Innovation policies target commercialisation,
internationalisation, etc.
Labour-market policies focus on immigration
and attracting scientific and engineering careers.
Competition policies focus on market access, market
liberalisation, ensuring competition, protection
of IPR, etc. Other policies react to innovations and
technological developments, but do not actively
create demand for innovation or see innovations as
the key resource for solving social and environmental
challenges.
The European Research Area becomes a reality
mainly for scientific research, although even in
that domain national interests are clearly visible.
Research in Europe is highly networked, but
stronger centres of scientific excellence challenging
the leadership of the US and the emerging power of
Chinese research are not likely to emerge.
Protectionism and competition between member
states hinders market development and Europe
looses ground as a dynamic market for innovation.
Internal market development is steady, but slow.
STI policies are characterised by multilayered
governance structures at the European, national,
regional and local levels. The resulting complex mix
of policies and policy measures is partly overlapping
and inefficient.
STI policy governance processes are increasingly
accessible for a wider range of stakeholders,
but mainly through consultation, not actual
participation. Changes in government coalitions lead
to changes in STI policies, not necessarily based on
strategic intelligence and a strong market failure
rationale. The difficulty of developing or eliminating
existing policy measures leads to the establishment
of new policy measures which further increases the
complexity of the STI policy mix.
The resulting complex policy mix includes measures
with outdated rationales, promoting inefficiency
and reducing effectiveness. Pressures to improve
effectiveness and efficiency increase. This leads to
an enhanced focus on the accountability of single
organisations and policy measures, thus failing to
address true systemic failures.
Concerns over globalisation lead to an increasing
focus on measures to attract foreign direct
investments and scientists. Competition for the
STI policies and policy measures are mainly reacting
to already active challenges because of the low quality
of strategic intelligence and learning processes. The
failure to identify emerging challenges soon enough
can also lead to disproportional policy responses,
which promotes unpredictability in STI policies. This
in turn is likely to reduce companies’ willingness to
invest in STI in Europe.
The ability to change policies, policy measures,
governance processes and organisational structures
varies among member states. Institutional rigidities and
resistance to change regardless of attempted reforms
in structures, processes, policies or policy measures
hinder the true development of national government
activities. This is mainly due to the fact that while
many changes can be visible and even quite dramatic,
they usually follow political and cultural tradition and
do not actually address the fundamental governance
problem. What this means in practice is that if there is
a tradition to change structures, the perceived solution
to most problems is to change structures, while the true
problem might be in governance processes. Similarly
if the tradition is to change policy measures, the
perceived solution and subsequent action is typically
to change policy measures, while the true problem
might be in structures.
The failures in strategic intelligence are also easily
displayed in the lack of understanding the time
needed for different types of changes and the ability
to manage transitions. Political decision-making
typically favours visible changes, which can produce
measurable results quickly. STI is unfortunately
an area where most processes are long-term and
changes take a long time. Furthermore, the results
are not easily measurable.
Increasing attention to benchmarking and learning
from good practices will lead to some degree of
convergence in the use of certain types of structures
and policy instruments. Due to the alreadymentioned differences in cultural, political and social
traditions, and due to the strong path dependencies
of innovation systems, national adaptations will
and should differ. However, similarities as well as
national differences provide a good ground for
further benchmarking and collaboration, which
is likely to contribute to the development of the
European Research Area.
STI is likely to concentrate into stronger centres.
Despite the cohesion objectives, the more targeted
and focused allocation of government resources is
likely to support this development. Policy measures
are likely to target the formation and strengthening
of centres of scientific and technological excellence
as a response to the global competition for the best
scientists and engineers.
Commercialisation of R&D results is likely to remain
one of the key policy objectives. New initiatives
supporting start-up companies, risk capital
investments and the transfer of IPR from public
research organisations to industry are likely to
emerge, as the state support regulations concerning
these types of activities develop. The field of
intermediary organisations is likely to experience
significant changes12 resulting from: the evaluation
of their true efficiency; the effectiveness and the
subsequent redesign of policy measures targeting
technology transfer; and the reallocation of public
resources.
Tax incentives are probably going to gain increasing
interest as a possible form of public investment in
R&D. However, they are not likely to replace direct
incentives in the form of grants and loans. In the
longer term tax incentives are likely to be seen
as complementary, rather than alternative, policy
measures compared to direct incentives. To what
extent tax incentives for R&D, innovation, start-ups
and risk capital are going to be effective depends
also on what the structures of corporate taxation
are, and how unified corporate taxation is going to
be within Europe.
Role of government
The government role has already been discussed in
the introduction to the scenarios, so the discussion
here focuses on the relative weights between
different roles of government in this scenario.
Assuming that current trends continue, governments
see themselves mostly as facilitators and controllers.
The role of different forms of partner arrangements
remains less important and the manager role
focuses on specific issues such as universities,
public research institutes and different forms of
technology transfer including start-up companies
and the management of measures targeting the
creation of collaborative platforms for R&D.
12.This does not necessarily mean that existing organisations would be
replaced with new organisations, or that other existing organisations would
take over the activities of current intermediary organisations. What this
means is that, with the exception of a small number of rather successful
ones, intermediary organisations need to redefine, or at least upgrade, their
activities. Several existing evaluations already question the efficiency and
effectiveness of intermediary organisations, but so far only a few have led to
any significant changes.
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best brains and companies increases in Europe and
globally.
The Future of Key Research Actors in the European Research Area
Although efforts to enhance innovation increase,
the focus of government activities remains mainly
on R&D. The role of government as a sophisticated
leading user and demander of innovation remains
small. STI policy mainly targets the supply of
innovation, whereas competition policy aims to
ensure competition which is seen as the key for
ensuring sufficient demand for innovation.
Policy governance
Rather than analysing the role and activities of
different government organisations organisation
by organisation, the approach adopted here is to
analyse the policy governance processes in the STI
policy cycle and use that to identify potential roles
government organisations may have and how various
activities could be organised in different structures.
One of the key problems current trends do not address
sufficiently is the increasing need for understanding
the changes and challenges of the innovation system,
and how these could most efficiently and effectively
be addressed. The focus is on formal evaluation and
foresight processes, and on accountability.
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While evaluation can provide valuable information
and understanding on how the innovation system
functions, and how well policies address various
market and systemic failures, evaluation in practice
typically remains either too focused on single
organisations or policy measures (thus failing to
address true systemic issues), or remains too much
on the overall policy level focusing only on the
narrow STI policy domain (thus neglecting to address
coherence and failing to identify the underlying
and more fundamental failures, which are often
culturally, socially and politically embedded). Too
often evaluations are still used to legitimise existing
organisations or measures, or to justify changes the
need for which has already been identified, but which
are hard to make because of institutional inertia.
Foresight activities can also be powerful processes
to increase understanding and facilitate shared
commitment to STI policies. However, many of these
processes are strictly expert-driven and focus on
scientific and technological prediction, thus failing
to address social and environmental questions and,
more importantly, failing to facilitate the shared
understanding and commitment of a wider range of
stakeholders, including political decision-makers
and NGOs.
Accountability is necessary to provide feedback of
the effectiveness and efficiency of public investments
and other policy measures targeting STI. However,
due to the lack of sufficiently intelligent measurement
systems (partly because measurement of STI is
difficult and partly because no measurement can
provide straightforward simple answers and thus
requires intelligent interpretation), accountability
often focuses on organisations and single measures,
for which it is easy to establish simple metrics.
While these simple metrics can be used to measure
immediate efficiency, they seldom provide any real
measure of effectiveness. Therefore, straightforward
implementation of accountability often leads into
sub-optimisation rather than improvements at the
level of the innovation system.
The functions that are typically missing and that
are also likely to be missing in the future are more
advanced and embedded strategic intelligence
processes. All government organisations should
integrate strategic intelligence activities both
into their normal strategic management systems
and into their specific evaluation and foresight
activities. Furthermore, these organisation-specific
activities should be coordinated so that they feed
into the overall strategic intelligence process at the
government level. One of the fundamental reasons
for this is the limited resources at the relevant
ministries. One approach to solve this problem is to
make the overall process sufficiently transparent,
open and accessible. The other is to set up a specific
and sufficiently independent policy-advice platform
or organisation to coordinate the overall process
and to follow their recommendations.
One of the key problems in many countries is that
policy design is separated from both strategic
intelligence processes and policy implementation.
This is based on the idea of keeping advice,
feedback, consultation, actual political decisionmaking and implementation of policy measures
strictly separate by assigning the responsibilities to
different government organisations. This is likely to
be the approach in many member states in the future
as well, at least in this scenario. While there are no
problems in the basic idea, what this often leads
to in practice is that, without sufficient interaction,
knowledge and understanding do not transfer
from one function to another. The worst outcome
of this is that policy decisions are not based on
carefully-analysed knowledge and understanding
and the advice resulting from strategic intelligence
processes, but on some other less transparent
processes (lobbying) which creates mistrust
towards government. This is likely to make policies
less predictable and therefore the environment
less attractive for those without access to informal
The lack of sufficient interaction between policy
design and implementation, especially when
linked to low quality or insufficient evaluation and
accountability, promotes an undesirable struggle
for survival among implementing agencies and a
lack of predictability both in policy measures and
among government organisations. It also reduces
the credibility of implementing agencies, which is
likely to lead to reduced effectiveness.
The design of actual policy measures is often also
separated from implementation. The same problem
of insufficient interaction between these two
activities is likely to lead to reduced effectiveness.
This can be overcome by establishing sufficiently
open processes for the design of policy measures.
Policy implementation is often assigned to
specific government agencies or sometimes
partly to private companies. While the efficiency
of the organisational arrangement is important,
the effectiveness of it is even more important.
Whatever the organisational arrangement, it is vital
to establish sufficient monitoring and evaluation
processes and systems, and to integrate them into
strategic intelligence processes. This will ensure
effectiveness and the ability to identify potential
needs to change, and to develop the policy measure
accordingly or even eliminate it if the original
rationale is no longer valid.
Policy learning is actually a combination of various
feedback, intelligence and sense-making processes
along the policy cycle at different levels. The quality
of learning is therefore defined largely by the
quality of all policy governance processes. It is also
a function in which all government organisations
should engage in together along with STI
performers. Learning is also a socio-cultural process
and therefore the organisation of these processes
is very much dependent on the cultural, social and
political context. It is therefore difficult to give any
general recommendations as to how and what kinds
of learning processes should be established.
The role and activities of government
organisations
Considering the discussion above, the role of
governments and parliaments is not likely to change
dramatically in this scenario. The role of national
governments in STI remains to large extent similar
to what their role is today. Culturally-, sociallyand politically-embedded barriers and rigidities
are likely to remain, which means that the same
remedies for future challenges can be expected as
typically used in the past. Traditions largely dictate
whether changes in STI policies are initiated with
structural and institutional changes, new incentives
and programmes, assigning shared responsibilities,
changes in governance processes, etc.
STI is likely to remain under one or two ministries.
Concentrating all STI into one ministry may gain
increasing interest. This does not, however, address
the challenge of horizontal policy coherence,
although a single ministry model might facilitate
this slightly better than the two-ministry model. The
true appreciation of STI as a key source of not only
economic growth, but also as the most potential
source of solutions to major social and environmental
challenges, is not achieved by placing STI in a single
ministry.
Agencies are likely to get more responsibilities in
designing policy measures, especially incentive
programmes. This might happen through
empowering existing implementing agencies,
assigning tasks from the ministry to some other
agency or by establishing new agencies for designing
and monitoring policy programmes. In the latter
case, the actual implementation could partly be
outsourced to private companies or to appropriate
public organisations.
Advisory bodies are likely to get more attention
and become stronger, as political decision-makers
more widely recognise the importance of strategic
intelligence processes, the need for enhanced agility,
and the need to be able to identify and react faster to
emerging challenges. The structure of these bodies
varies from country to country because of political,
cultural and social reasons. Some may be a more
established part of institutional structures, some
more temporary and ad hoc; some may be totally
independent, some closer to political decisionmakers. The real challenge is not to set up advisory
bodies (which is relatively easy), but to set up
transparent, open and accessible policy governance
processes in which advisory bodies as well as other
government and private organisations can find their
respective roles.
An increasing need for understanding STI and related
trends, and how well policies currently address
various market and systemic failures emphasises
the need for stronger research of STI. Evaluation,
foresight and other strategic intelligence activities
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and less transparent processes. It also reduces the
motivation to participate in any transparent policy
processes.
The Future of Key Research Actors in the European Research Area
as well as policy design and even implementation
activities require knowledge of how STI changes,
what enhances and hinders STI, and how well
policies target market and systemic failures. It is
not possible to acquire this understanding unless
there is a sufficiently strong research community
developing
new
methods,
methodologies,
approaches, knowledge and skills for addressing
policy-relevant issues.
The scientific community addressing STI policyrelevant issues is multidisciplinary and relatively
young. It is likely that this community will develop
and is able to provide better tools for policymakers
to design better policies and policy measures.
Production, distribution and use of knowledge
198
STI policies are built on the concept of national
innovation systems. The roles of different actors
in knowledge production, transfer and use remain
mostly the same. This means that universities are
mainly seen as producers of scientific knowledge,
research and technology organisations (RTOs)
as producers of applied knowledge, transfer
organisations’ key role is to transfer knowledge, etc.
Although users, citizens and customers are seen
as increasingly important sources of knowledge,
they are not seen as important actors in the actual
knowledge processes.
Knowledge is validated on two platforms: scientific
knowledge is validated by the academic community
(mostly at universities), and applied knowledge is
validated by end-users (markets). Open innovation
is organised and controlled mostly by companies
– sometimes visibly and directly, sometimes
indirectly. National governments and their STI
policies target specific, identified knowledge
processes.
National government organisations see themselves
as users of knowledge and facilitators of specific
knowledge processes. Funding basic education
and science is considered the responsibility of
national governments. What counts as knowledge
is knowledge produced, validated, transferred
and utilised in identified knowledge processes by
identified knowledge actors.
Although the roles of actors as well as most of the
knowledge processes remain the same, this does
not mean that the processes or activities would not
develop and that the roles would remain exactly
the same. However, no radical or even significant
transformation in the roles and established
knowledge processes is assumed. The implication
of this is that the bulk of scientific knowledge is
produced at universities and then transferred to RTOs
and companies through applied research activities.
This does not refer to a linear model, as universities,
RTOs and companies increasingly produce, transfer
and use knowledge in collaborative projects.
However, the underlying roles of these actors
remain the same which is evident in their respective
roles in collaborative activities. Internet and ICT in
general are increasingly used as a tool in knowledge
processes. However, established institutions (e.g.
companies, universities, NGOs) control the access
to and validate the results of knowledge processes.
Customers have an increasing role in shaping the way
knowledge is transformed into products, processes
and services, but the processes are controlled by
established institutions.
Even though the roles of different actors and
knowledge processes themselves vary quite
significantly in some respects, their ‘global’
vs. ‘local’ characteristics are not that different.
Knowledge attracts knowledge and therefore
tends to concentrate. This can take place in the
form of networks, communities or geographical
concentrations. Because of the increasing
importance of customers, users and citizens in
knowledge processes, the ‘localisation’ aspect
becomes stronger. At the same time, productivity,
liberalisation of global markets, increasing
international
interaction
and
collaboration
emphasise the ‘global’ dimension of knowledge
processes.
4.4 Scenario B: Radical transformation
This scenario is based on the assumption that national
governments prioritise STI high on the political
agenda. This means allocating more resources for STI,
adopting STI as a horizontal policy and accordingly
developing the appropriate policy governance
processes. National governments undergo radical
transformation to capture more benefits from STI in
all policy areas targeting sustainable economic, social
and environmental development.
STI policy and measures in the national
context
National governments recognise the importance and
potential of STI widely across all policy areas. STI
is seen as a major contributor not only to economic
growth but also for tackling major social and
environmental challenges. STI is a horizontal policy
extending across all sector policies.
Research policies target interdisciplinary research,
exchange and the mobility of researchers
internationally, and between the public and private
sector and between basic and applied science, big
science targeting global challenges, etc. Technology
policies emphasise the importance of customer and
user participation, user context, social shaping of
technologies, etc. Innovation policies become more
demand-oriented, facilitating the identification and
solution of economic, social and environmental
challenges, emphasising the needs of customers,
users and citizens, attracting private actors to focus
on innovations with wider economic, social and
environmental impact, etc.
Labour market policies emphasise mobility in
Europe and life-long learning. Competition policies
focus increasingly on market dynamics. Other
policies identify innovation as the key solution to
social and environmental challenges. STI policy
objectives are a combination of economic, social
and environmental objectives. Other policies
negotiate with private actors and civil society to set
objectives which create a demand for innovations
(for example, progressive effluent and safety
regulations in the car industry).
The European Research Area becomes the European
Research and Innovation Area, capturing all aspects
of science, R&D and innovation. Both research and
innovation are highly networked across European
countries and regions. European research challenges
other global centres of top scientific research,
especially in its ability to foster wide collaboration
between companies and between companies and
public research organisations.
European internal markets develop fast and
become considerably more dynamic. One of the
key characteristics is that national governments
and the EU encourage innovation through public
procurement, standardisation and other policy
measures targeted at opening new markets and
facilitating the access of new companies to existing
markets.
National government, the EU Commission and
regional and local policies and policy measures
are well coordinated and all actors have identified
their appropriate roles. The Commission focuses on
issues at the European level, such as networks and
centres of global-level scientific research, European
technology platforms, competition and market
regulation (including IPR), the mobility of skilled
human resources, financial markets (especially the
availability of risk capital), etc. National, regional
and local governments target policies and activities
which are most effective and efficient to handle at
the national, regional and local levels respectively.
These include measures targeting SMEs, platforms
for collaboration, networking and clustering,
technology transfer, etc.
STI policy governance processes both at the
European and national levels are transparent, open
and accessible to a wide range of stakeholders.
Processes lead to understandable and predictable
outcomes,
which
enhances
stakeholder
commitment. In addition to research performers,
ministries, agencies and other expert bodies,
politicians and NGOs also participate in governance
processes at all levels.
Participation and commitment is reflected in
predictable STI policies over time, regardless of
political coalitions. Policies and policy measures
are based on clear market and systemic failure
rationales with clear exit plans13. Systematic
evaluation processes continuously analyse the STI
policy mix and changes are made based on emerging
and disappearing needs. An in-depth understanding
of innovation processes and innovation systems
ensures that policy changes are effective and
implemented efficiently.
Concerns over globalisation lead to an increasing
focus on measures to attract foreign direct
investments and scientists. Competition for the
best brains and companies increases in Europe and
globally. This is seen both as a national and European
issue, and solutions are sought at both levels based
on developing the attractiveness of European
innovation systems and European markets.
13.Exit plan refers to a plan which describes how the policy measure attempts
to fix or alleviate the market or system failure in the longer term, what
market actors are going to take over the activity and how, how the progress
of alleviating or fixing the failure is monitored, and under which conditions/
criteria and how the measure can be gradually or entirely eliminated.
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Education policies emphasise life-long learning,
interdisciplinary
capabilities,
engineering,
natural sciences, humanities, etc. integrated into
interdisciplinary curricula rather than a strict
disciplinary approach, learning and collaborative
capabilities across disciplines, etc., as capabilities
to understand and use different knowledge and
participate in various knowledge processes
becomes increasingly important. Education is
more multidisciplinary and takes place throughout
working life at various learning platforms created in
public-private partnerships. Education systems are
international and better linked to research.
The Future of Key Research Actors in the European Research Area
STI policies are based on an in-depth understanding
of the fundamental underlying reasons for market
and systemic failures, and effective and efficient
policy measures. An in-depth understanding is
based on strong strategic intelligence processes,
which reveal emerging policy challenges early.
Policies are pro-active and are able to target
emerging failures. Predictability, the early
identification of emerging failures, and a strong
commitment to innovation and dynamic markets
attracts STI investments into Europe.
There is natural variation in STI policies and policy
measures across Europe at the national, regional
and local levels. Good practices are adopted through
learning processes to fit national, regional and
local cultural, social and political contexts. Through
an understanding of the underlying reasons for
institutional inertia and the barriers created by
traditions and path dependency, transitions are
initiated and managed using specific approaches
that fit the specific context.
200
STI concentrates in stronger centres in Europe,
but these centres are also highly networked to
smaller and specialised national, regional and
local centres. In addition to centres built around
scientific excellence, there are a number of centres
built around technological, market, social or
environmental applications. The latter are especially
effective platforms of interdisciplinary applicationoriented research and platforms for piloting new
innovative applications in simulated-user contexts.
These centres are created in close partnerships
with both public and private stakeholders including
research performers, risk-capital organisations,
public agencies and user organisations.
STI policies are increasingly based on building
different forms of partnerships between public
and private sector. Policies target both the supply
of innovation (incentives, R&D, education, etc.)
and the demand for innovation (market dynamics,
procurement, etc.), as well as better framework
conditions (regulation, availability of innovation
services, etc.). The main approach is to identify
market and system failures, target them early and
effectively, and withdraw as soon as possible.
Various forms of investments gain ground as
forms of public funding, typically in the context of
various types of public-private partnerships. The
rationale is primarily to combine the longer-term
commitment of private actors (companies, funding
organisations) to the ability to maximise the
leverage of public funds.
Role of government
The government role was already discussed in the
introduction to the scenarios, so the discussion here
focuses on the relative weights between different
roles of government in this scenario.
Radical transformation in the wide recognition of the
importance of STI, and subsequently in STI policies,
changes the perceived role of government. This change
emphasises the role of government as a partner and
facilitator. Governments seek to ensure longer-term
sustainable economic, social and environmental
development in the knowledge economy using various
types of public-private partnerships to gain longerterm commitment from companies and other private
actors. Partnerships can also be effective in developing
various collaborative platforms, encouraging private
actors to develop services and products to newlyopened markets, developing welfare and other basic
services for citizens, etc.
National, regional and local governments act as
sophisticated buyers, which encourages innovation.
Innovative public procurement enhances innovation
and produces innovative solutions which increase
productivity in the public sector.
The facilitation role remains important and is
emphasised through the integration of social and
environmental objectives to economic objectives
in STI policies, and through a better integration of
competition and market policies to the expanded
horizontal STI policies. Regulations and standards,
as well as measures to facilitate emerging markets
and competition policies, emphasise predictability
and long-term shared agreements14. This creates a
continuously upgraded incentive for innovation.
Government policies target innovation systems and
market and system failures in a balanced way. Both
R&D and innovation are seen in a wider context of
sustainable economic, social and environmental
development in a knowledge economy.
Policy governance
Strategic intelligence processes are strong,
transparent, open and accessible, providing an
in-depth understanding of innovation processes,
innovation systems and related market and system
failures.
14.This refers to regulations, standards or voluntary agreements which set
increasing and predictable targets for long periods of time. A good example
of this is emission limits set for cars. The industry knows years ahead how
the regulations will change and can prepare and develop new technologies,
products and services to meet these regulations.
Foresight activities are extended to cover not only
scientific and technological issues but also social,
cultural and economic issues. Foresight processes
are open, transparent and accessible for a wider
audience. Foresight processes are integrated
into policy design processes and provide relevant
knowledge for both STI and other policies.
Monitoring systems are designed to address the
accountability of single organisations and individual
policy measures, but also to provide information for
more systemic analyses. Monitoring emphasises
systemic accountability, although organisations and
policy measures are also monitored closely.
Both evaluation and monitoring are based on a
developed set of indicators and metrics, which are
continuously developed through research.
Policy design is based on an in-depth understanding
of the relevant market and system failures. Policy
design processes are interactive, accessible for
a wide range of stakeholders (including NGOs),
transparent and open. Policy rationales are
understandable and based on identified failures and
recommendations.
Policy implementation processes are efficient
and flexible. Implementation is controlled and
coordinated by government organisations, but is
increasingly performed by private actors or publicprivate partnerships.
Policy learning is integrated in all processes at all
levels of the STI policy cycle. Learning capabilities
facilitate the quick adoption of good practices
across Europe. Benchmarking and the exchange
of experiences is a continuous activity between
government organisations.
The role and activities of government
organisations
Governments and parliaments discuss STI-related
issues frequently. While there is a general consensus
across political parties on major policy objectives,
more detailed objectives and policy measures as
well as a particular emphasis on the allocation
of resources to specific economic, social and
environmental objectives is continuously debated.
Awareness of STI among politicians is high, which
reduces the risk of unpredictable policy changes. STI
and other policies are integrated through a political
debate.
All ministries have significantly stronger resources of
STI experts. Horizontal coordination between sector
ministries is efficient and most STI policy measures
are joint efforts between several ministries. Interministerial STI policy coordination platforms have a
strong role in resource allocation and policy design.
The division of labour between ministries and
agencies vary across countries. Sufficient interaction
ensures that information between design and
implementation of policies is fluent.
Agency structures vary across countries, but
agencies are in general more empowered. Interaction
between agencies and research performers is
frequent. Agencies can be either centralised and
perform several activities or they can be more
targeted for specific activities. The key feature is
sufficient interaction between different activities,
whether they are performed by a single agency or by
a number of separate agencies.
Agencies create and manage various platforms
and public-private partnerships. Many activities
are coordinated and controlled by agencies, but
performed by private actors or public-private
partnerships.
Advisory bodies are increasingly institutionalised
and form strong linkages with the research,
evaluation and foresight communities. Advisory
bodies collaborate with ministries and agencies in
coordinating and managing strategic intelligence
processes. Advisory bodies typically coordinate
foresight and systemic evaluation activities. Advisory
bodies are typically politically independent.
The STI research community is strong and
sufficiently independent, with strong linkages to
advisory bodies. In case advisory bodies are more
ad hoc or are not politically independent, this can
be compensated by more independent research
organisations specialising in STI policy research and
evaluation.
Production, distribution and use of knowledge
STI policies are holistic and national government
organisations see themselves more as partners
and facilitators in knowledge production, transfer
and utilisation processes. The role of different
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Evaluations target truly policy-relevant issues and
are integrated in strategic intelligence processes.
Evaluations frequently target policy objectives,
policy mixes and systemic issues, rather than single
organisations or policy measures.
The Future of Key Research Actors in the European Research Area
organisations in the knowledge production, transfer
and utilisation processes varies, as it is no longer
directly linked to the organisation, but rather in
the activities they participate in during the various
knowledge processes.
Knowledge is validated on several platforms; some
are more traditional and with set rules (e.g. academic
community, NGOs, open source), some more diffuse,
temporary and open (e.g. markets, Wikipedia,
internet virtual communities). Access to knowledge
processes is only limited by knowledge capabilities,
which emphasises the importance of life-long
learning. STI policies facilitate a much wider range
of knowledge processes and acknowledge especially
the social importance of knowledge possessed by
citizens and NGOs.
202
National governments see themselves both as
facilitators and as partners in knowledge processes.
Organising and funding education and science
– basic, life-long, applied, etc. – is seen as a
partnership effort, not the sole responsibility of
national governments. What counts as knowledge
is defined in various formal and informal knowledge
processes by those participating in them. National
governments acknowledge all knowledge processes
and respective knowledge which has economic,
social, environmental, etc., policy relevance.
National governments equally facilitate a wide
range of different kinds of knowledge processes
and access to them by all relevant actors,
including citizens and NGOs. The holistic approach
emphasises the importance of continuous renewal
and learning for all actors, processes and structures,
as opposed to renewal only through selected formal
knowledge processes organised and run according
to established rules and institutions.
Boundaries get blurred and the roles of different
actors vary in different knowledge processes.
Knowledge is transferred, transformed and used in
various forms through a wide range of knowledge
processes accessible to a wider range of actors.
Knowledge processes are no longer clearly controlled
by specific institutions, but are more open. Various
user communities have a significant role in shaping,
transforming and transferring, as well as using,
knowledge. ICT and especially open internet platforms
are the main tools in used knowledge processes. STI
policies facilitate openness of knowledge processes,
and new knowledge is increasingly made available
to a wider set of actors. The role of established
institutions is no longer as dominant as it used to
be. While expertise is still valued, the exchange
of different types of knowledge and interaction
between experts and users – individuals as well as
communities – becomes increasingly important.
Knowledge possessed by users and citizens is valued
much higher than today.
The role of virtual communities becomes increasingly
important. This indicates that what is currently
understood as ‘global’ and ‘local’ characteristics of
knowledge is complemented with a new characteristic
which might be called the ‘community’ character
of knowledge. This refers to knowledge being
shaped and transformed not ‘globally’ or ‘locally’,
but by a virtual networked community. This might
also be seen as a new form of ‘local’ knowledge.
However, since it is built on quite different forms
of shared cultural and social experiences (mostly
communicated through networks and the internet),
is not geographically-defined and does not represent
users in a wider global context, it might make sense
to identify is as separate from ‘global’ and ‘local’ and
entailing some characteristics of both.
Both structural boundaries and the roles of actors
in knowledge processes get blurred. The identity
of actors is defined separately in each knowledge
process by their respective activities. Government
organisations can be equal partners, facilitators,
knowledge producers, knowledge users, transferring
knowledge, etc., in other words they have different
roles in various knowledge processes. One reason
is that more processes are identified as knowledge
processes than just formal institutionalised
processes. Another reason is that government
organisations increasingly need to rely on a much
wider set of knowledge which is produced not just
by universities, RTOs and companies, but also by
users, citizens and their communities (e.g. NGOs).
4.5 Scenario C: Europe of regions
This scenario is based on the assumption that
the role of national governments diminishes and
is taken over, on the one hand, by the European
Commission and, on the other hand, by regional and
local governments.
One of the key questions related to this scenario is
how Europe is divided into regions. How many regions
would there be? Would the regions be defined based
on the current definition of regions within member
states? Would regionalisation be limited to larger
member states, while smaller member states would
be identified as regions? Would regionalisation be a
top-down process (political decisions at European
level) or would regions emerge as a result of cultural
and social process bottom-up?
STI policy and measures in the national context
European-level policies and their coordinated
implementation at the regional level.
Role of government
The role of the public sector in various public-private
partnerships is taken over by regional governments
and their respective organisations. The overall
policy framework facilitating STI is designed at the
European level and the actual facilitation is done at
regional and local levels.
The European Commission takes a strong role in
coordinating STI policies and regional governments
have a strong role in implementing STI policies.
The role of national governments is reduced to
coordination across policies and regulatory control.
Most STI-policy processes are managed at regional
and local levels, although some may still remain
at national level. As a result management of STI is
mainly done at the regional level.
Regions develop their own education, research and
innovation systems. Competition for the best brains
and companies takes place mainly between regions.
The role of national governments is focused on
regulatory control, administrative issues and
cohesion in regional development.
STI policies depend largely on the regions’ ability
and competence in embracing modern innovation
policies and policy processes. Variation between
regions increases in this respect despite attempts
to enhance cohesion. Regions with specific STI
strengths can develop global excellence supported
by national and European policies.
Policy governance
The strong regional policy emphasis offers a good
environment for collaboration, networking and
clustering. Public-private partnerships are likely to
be more common in strong regions. Weaker regions
focus more on SMEs and traditional sectors, while
most large and innovative firms are more likely to be
located in stronger regions with good environments
for STI, making stronger regions even more attractive
for STI.
Stronger regions are likely to develop according to
scenario B, while the development of weaker regions
is more likely to follow scenario A. Governments in
countries with stronger regions are able to manage
transitions and tackle polarisation better than those
with weaker regions.
National governments’ role in STI is reduced to
coordination and regulatory control. Policy measures
are mainly focusing, on the one hand, on developing
regulatory controls and balancing national
development by supporting weaker regions, and, on
the other hand, on coordinating policy measure at
the national level.
National activities related to labour markets,
education, competition and STI are built on
Most STI-policy processes are designed and
managed at the regional level. National governments
only coordinate these processes at the national
level. Some of the strategic intelligence processes
might be organised at the national level. These might
include foresight and systemic policy evaluation as
well as STI policy research.
National government organisations are likely to be
quite detached from actual policy implementation,
which reduces their ability to participate in STI-policy
processes. National governments do participate
in the policy processes at the European level, but
strong regions are likely to have more influence
on European STI policies than most national
governments.
The role and activities of government
organisations
Parliaments and governments are mostly concerned
with transition management, polarisation and
cohesion, and sustainable economic, social and
environmental development. STI is likely to have a
lower political priority, although this does not mean
that STI would be less favoured by governments and
parliaments.
Ministries are focused on coordinating policies
across regions and on policy measures that enhance
cohesion. Regulatory issues are high on ministries’
agendas. Ministries participate in STI-policy
processes at the European level.
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This scenario assumes that regionalisation
takes place via a bottom-up process by national
governments assigning increased autonomy to
existing regions. This might lead to the restructuring
of regions through regional collaboration in the
longer term, but this is not assumed to change
the respective roles of national, regional and local
governments in STI.
The Future of Key Research Actors in the European Research Area
National agencies are mainly dealing with
coordination, foresight and evaluation activities.
Public funding is allocated partly at the European
level, but mainly at the regional level. There are only
a few national funding agencies, and even those
mainly allocate funding to regional agencies.
to the formation of separate ‘local’ and ‘global’
knowledge networks which are tightly interlinked,
however, through networks of universities, RTOs
and companies.
Advisory bodies still have a strong role at the national
level to facilitate national government participation
in European-level policy design processes. However,
these bodies have strong regional representation.
Some may even be organised in the form of networks
of regional advisory bodies.
5. Evaluation:
The policy goals
perspective
STI research is likely to remain at the national level,
partly for the same reason as for advisory bodies,
i.e. to help national governments’ participation in
policy processes at the European level, and partly
because national governments are in a position to
house independent activities better than regional
governments, which have tighter linkages and
partnerships with research performers and policy
implementation.
This section briefly discusses the scenarios
described in the previous section from the point of
view of how they are likely to contribute to more
investments in STI, stronger performance in STI,
providing competitiveness and solutions to social
and environmental challenges.
Production, distribution and use of knowledge
204
STI policies target, on the one hand, formal
knowledge processes and established institutions,
while on the other hand they are more sensitive
to the views and opinions of users and citizens
and the needs of companies. While partnering
is quite likely, the roles of different actors are
likely to remain fixed. What counts as knowledge
is mostly defined in formal and institutionalised
processes, but with more actors participating in
these processes. Established institutions are likely
to have a dominant role in knowledge processes.
Knowledge is mostly validated by traditional
institutions and markets, although the views and
opinions of customers, users, citizens and NGOs
have a significantly stronger role in validation.
Users, customers and citizens and their various
communities become stronger and increasingly
important in shaping and transforming processes,
as well as transferring knowledge.
The ‘local’ characteristics of knowledge processes
become emphasised. This does not mean that they
would replace or challenge the ‘global’ dimension,
which is increasingly important. ‘Local’ knowledge
processes, structures and institutions (or local
representatives of more global institutions)
are at the core of STI policies and related
initiatives, thus emphasising the importance
of establishing geographical concentrations of
knowledge structures and processes. This leads
Comparing the scenarios A and B it is obvious that
the latter provides far better ground for STI in the
future Europe. The possible impact of regionalisation
(scenario C) on the other hand, can go either way
depending on to what degree regions would follow
scenario A or B. However, there are more concerns
with scenario C compared with scenario B.
The strengths of Europe in R&D are eventually
decided largely by private companies. This does not
mean that publicly-funded scientific research would
not be important. Its quality and focus have a vital
role in the attractiveness of Europe as a location for
STI. However, sustainable economic development
is possible only if companies see Europe as a good
location for STI and European markets are dynamic
enough to attract companies to locate and engage in
STI in Europe.
So far Europe has been falling behind the US
and Japan in R&D and competitiveness. Fastgrowing and dynamic Asian markets are likely to
challenge Europe, the US and Japan even more in
the future, in STI as well. As scenario B suggests,
this development can only be turned through a
radical transformation of STI policies and related
governance structures and processes in Europe.
While regions can play a major role in this
transformation, national governments are most
likely to be the decisive force.
Europe has specific strengths in STI as well as in
social and environmental development. Combining
these strengths with a real political commitment to
make Europe a leading knowledge-based economy
can turn the current development and create a
dynamic and innovative market in Europe. This
requires the recognition of the importance of STI
and more importantly, true political commitment
and decisive action at the national level.
Scenario B offers some insight into what the
necessary transformation could be and how it
could be achieved. The purpose is not to suggest
that it is the only viable path to create a dynamic
knowledge-based economy, nor that the proposed
transformation would be sufficient to ensure it.
However, as scenario A discusses, there are several
concerns related to current developments, which
would indicate that continuing on this current path
is not likely to yield the desired result.
While increasing regional autonomy and the
regions’ role in designing and delivering STI
policies could probably address some economic,
social and environmental issues more effectively
and efficiently, its ability to address others raises
some concerns. At least this kind of development
would most likely require significantly stronger
governance at the European level.
Wo rki ng Paper 9
National governments
205
The three scenarios present only three possible
approaches national governments can take in facing
future challenges. The actual path chosen is likely
to contain some aspects of all of these scenarios.
Furthermore, the progress in different European
countries is likely to vary and cultural, social and
political diversity is likely to remain a characteristic
of Europe in the future.
The Future of Key Research Actors in the European Research Area
6. Bibliography
Arnold, E. and Balázs, K., Methods in The Evaluation of Publicly Funded Basic Research, Technopolis Ltd, 1998.
Arnold, E., et al., Research and Innovation Governance in Eight Countries, Technopolis Ltd, 2003.
Boekholt, P., Ensuring policy coherence by improving the governance of innovation policy, background paper for a Trend Chart policy
workshop in Brussels, 2004.
DG Enterprise, Innovation tomorrow, Innovation papers no 28, European Communities, 2003.
Edler, J., et al., New governance for innovation. The need for horizontal and systemic policy coordination, report on a workshop,
Fraunhofer ISI discussion paper, 2003.
Eurobarometer, Special edition, Nr. 225, Social values, Science and Technology, EU, 2005.
European Union, Innovation policy in Europe 2004, Trend Chart, EU, 2004.
Freeman, C., Japan: a new national system of innovation?, in Dosi, G. et al. (eds.), Technical Change and Economic Theory, Pinter
Publishers, London, 1988, (pp. 330-348).
Kuhlman, S., Future governance of innovation policy in Europe – three scenarios, Research policy, vol. 30, 2001 (pp. 953-976).
Lundval, B.A., Innovation as an interactive process: from user-producer interaction to the national system of innovation, in Dosi, G. et
al. (eds.), Technical Change and Economic Theory, Pinter Publishers, London, 1988, (pp. 349-369).
Lundvall, B.A. (ed.), National Systems of Innovation. Towards a Theory of Innovation and Interactive Learning, Pinter Publishers,
London, 1992.
Managing Uncertainty, R&D in a global world, report for phase 1, 2004.
OECD, Governance of innovation systems, Volume 1: Synthesis report, OECD, 2005.
OECD, Governance of innovation systems, Volume 2: Case studies in innovation policy, OECD, 2005.
OECD, Governance of innovation systems, Volume 3: Case studies in cross-sectoral policy, OECD, 2005.
OECD, Dynamising national innovation systems, OECD, 2002.
206
OECD, Internationalisation of industrial R&D. Patterns and trends, OECD, 1998.
OECD, Science and innovation policy. Key challenges and opportunities, OECD, 2004.
Pickavance, L., Public sector innovation in the knowledge economy, Prisma strategic guideline 7, EU IST programme,
(www.prisma-eu.net), 2003.
Romanainen, J., The cluster approach in Finnish technology policy, in Innovative clusters. Drivers of national innovation systems, OECD, 2001.
Smits, R., and Kuhlman, S., The rise of systemic instruments in innovation policy, Int. J. Foresight and Innovation policy, vol. 1, Nos. 1/2, 2004.
7. Curriculum Vitae
Dr Romanainen graduated from Helsinki University of Technology with an M.Sc. and Lic.Tech., and earned
his Dr.Tech. in Chemical Engineering from Åbo Akademi University. After working both in industry and
academia, Dr Romanainen joined Tekes in 1992 and has since had responsibilities in strategic planning
and evaluation as well as the design and implementation of technology and innovation policy and related
policy measures at many levels of the organisation. He has participated in many national, EU, OECD and
other international activities related to the design, implementation and evaluation of technology and
innovation policies. Recently, Dr Romanainen has also been assisting the Enterprise Strategy Group in
Ireland, the Innovation Platform in the Netherlands and the Prime Minister’s Office in Finland in formulating
future innovation policy.
10
W o r k in g
Paper
Regional Governments
Luis Sanz-Menéndez (with the collaboration of Laura Cruz-Castro), CSIC-UPC-SPRITTE
T
he aim of this paper is to analyse the current
role and functions of the European Regional
governments in science, technology and innovation
and their different possible futures with respect to the
development of the European Research Area (ERA).
In this paper, we try to combine insights emerging
from diverse literatures. Important sources are
studies on the federalisation of Europe in the context
of European integration, as well as the analyses of
the regionalisation and decentralisation of different
countries. Additionally, we also have reviewed some
of the studies about the rationales for government
intervention in support of science, technology
and innovation and the developments of regional
systems of innovation.
We have to state clearly the existence of a deficit
of real comparative literature on the regional
governments’ involvement on Science and
technologies (S&T) issues. There is no general
analytical framework that could help us in
understanding why and under which circumstances
regional governments become actively involved in
S&T policy and how they intervene when they do.
There are various reports describing the situation in
different countries or some of the initiatives taken by
regions, but most of the knowledge accumulated in
this field is mainly constructed on case studies from
which strong normative statements are extracted
and very little on comparative cases even at national
level (Sanz-Menéndez & Cruz-Castro, 2005).
Given the limits and focus set up for the paper we
would firstly like to link the two elements proposed
(regional governments and ERA) primarily to
two main interacting forces: Regionalisation and
Europeanisation. Therefore, we will start with
the most general literature on Europeanisation
and Regionalisation and then move to that more
specifically related to knowledge production support
by regional governments, that is the transformation
of the S&T policy domain in Europe and the possible
emergence of a multilevel governance system (MLG)
of S&T and innovation.
The European Research Area (ERA) is at the same
time a normative concept, a label for describing
a set of objectives defined by the European
Union, and also an empirical concept describing
the increasing integration of the research and
innovation systems at European level. There are
different labels for describing that integration
process and the dominant one is ‘multilevel
governance’ (MLG). If the hypothesis we set up
with respect to the MLG system is true, we should
expect a significant change in authority allocation
in the S&T policy domain. The increasing of the role
and functions of regional and European authorities
could only be the result of a national governments
losing ground in this field.
However, a first analysis presents a very diverse
situation in the degree and forms of regional
governments involvement in S&T; even if there
are European influences, it appears that the
reconstruction of the policy field is very different in
the European countries.
1. Introduction:
The Europe of Regions?
The purpose of this chapter is to introduce a set
of actors (regional governments) and to describe
briefly their diverse situation in Europe.
Regional Governments are, as stated by Campbell
& Lindberg (1990), simultaneously ‘arenas’ and
‘actors’. ‘Regions are political arenas in which
various political, social and economic actors meet
and where important issues such as economic
development are debated and decisions taken.
Simultaneously, they have become actors in the
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W o r k i n g P a p e r 10
Regional Governments
Presentation
The Future of Key Research Actors in the European Research Area
national and Community arenas, pursuing their own
specific interests’ (Keating 1998, p. 575).
The region is not a natural creation but a social
construct in a given space and Europe does not
possess a uniform or homogeneous level of
regional governments in the judicial, political or
administrative sense (Keating 1998).
However, apart from regional governments, we will
mention some other forms of regional authorities,
even if they are decentralised extensions of the
central government, or specific arrangements like
the metropolitan governments.
208
We also found various forms of regions and regional
action, and what we have today is in one way the
result of top-down regionalism (Keating, 1998). After
the Second World War, and particularly in the 1960s,
regions were recognised as an important element for
the modernisation of states. In Germany, federalism
was imposed due to the pressure of the Allies and the
German desire to avoid excesses of national-socialist
centralisation. In many states, notably France, Italy
and the UK, regions emerged in the 1960s as a space
of action of the state, etc. States, including the UK
and Belgium, also used regional frameworks for
concessions to cultural minorities. But on the other
hand, mobilisation within the regions or bottom-up
regionalism has been also identified. Whatever the
origins, after the economic crisis of the 1970s, we
have witnessed new impulses to the regionalisms
(France, UK, Italy, etc.) and in the 1980s and 1990s
new impetus was given to regionalism in Europe by
economic restructuring, state reforms, globalisation
and especially by European integration. There is
a general agreement that European integration
has had very important effects on regions and
regionalism.
Corresponding to the variety of regionalism, we
witnessed different modes of regional governments,
ranging to the extremes. In certain cases, regional
institutions are simply decentralised arms of the
state. This was the case in the pre-devolution UK,
where the administrations of Scotland, Wales and
Northern Ireland were part of the central government
and were governed by national ministers; it was
also the case of other EU countries like Greece.
Regional administrations have also been constituted
as ad hoc agencies whose directors are named by
the state, the unions and employers, and the local
community, as it is often the case in the UK/England
Regional Development Agencies (Jones, 2001). In
France, a system of state administration coexists
with the administration of the regional councils in
the regions (Heraud & Crespy, 2005). However, we
have to consider that if we are talking about regional
governments, we should restrict the analysis to
autonomous institutions elected by universal
suffrage. Here as well there are different models. The
most advanced model is federalism, which is found
in Germany, Austria, Belgium and Switzerland. It is
also possible to consider that Spain is in this group.
However, there are other countries, such as France
or Italy, in which the regions have limited powers
and a limited degree of autonomy.
Since regional governments are very diverse all over
Europe, their possibilities to act depend on elements
that have been codified in different ways:
To account for the diversity of power of regional
governments, Keating (1998), proposes to analyse
the power of regions through seven dimensions:
1.Institutions include not only political or
administrative institutions but also those
belonging to civil society and economy;
2.Policy-making capacity. There are some regions
which have a political system, a decision-making
capability and which can legitimately establish
a ‘regional interest’, and there are others which
lack this unity of action and are reduced to being
simple relayers of other systems of action (e.g.
national governments);
3.Powers attributed to the regions are important
factors, especially in cases where they have
real decision-making autonomy. If shared with
a national government (as in France and Italy)
regions normally have a secondary role;
4.The power of integration. Regions are intermediary
institutions (territorially and functionally). Their
power depends on the capacity for integration
that ensures that regions can position themselves
strategically in these roles;
5. F inancial resources. To implement public
policies regions need resources but also a
degree of freedom in their allocation. Having an
independent tax system or something to play
within the intergovernmental system is relevant;
6. T
he intergovernmental system refers to the
relationship between the regions and the state
and the EU authorities. In some cases this
relationship is one of dependence, while other
regions can influence national and EU policies.
There are institutional relations (Germany),
7. R
elations with the market. For economic
development, which is one of the main tasks of
regional governments, the regions depend also
on the markets. They cannot control the market,
but they can sometimes manage the specific
conditions of their place in national, European
or world markets. Of course some regions, being
in a favourable market position, find this easier
than others.
In the specific domain of S&T policy, Cooke et al.
(1997) have summarised the critical dimensions that
regional governments should have.
Considering the specific dimension of regional
government capabilities for innovation policy, it
varies a lot among the different European regional
governments. Some scholars have analysed the ability
of regional authorities to intervene in steering their
regional systems of innovation (Cooke, Gómez Uranga
& Etxebarria, 1997) arguing that regional government
capabilities in field are somehow constrained by
the formal competences attributed to the regional
authorities in the constitutional arrangements,
but also by the financial resources available for
implementation and by the organisational resources
that the regional government has in the policy domain.
The political configuration of regional authorities
and its relation with direct popular elections and the
existence of assemblies with legislative powers are
also relevant issues when analysing the resources
available for the action of regional authorities in this
policy domain.
As a consequence of the mainly national role in the
‘attribution’ of competencies and, in most cases,
socio-economic and financial resources, what really
characterises the situation of Europe with respect to
its regional authorities’ capability to become actively
involved in S&T and innovation systems governance
is diversity.
2. The role of Regional
Governments in the
Knowledge Production
and Research Systems
The purpose of this chapter is twofold: on the one
hand, to explore the different rationales which
motivate regional intervention in research and
technology systems, describing how these rationales
have evolved over time. On the other hand, we will
analyse the diversity of research and innovation
policies that we find at the regional level across
Europe, paying attention to whether these policies
focus on science and knowledge production, or on
technology and innovation approaches. We will try
to explore the theoretical justifications related to
the questions of why regional governments enter
the knowledge and innovation policy domain and
what different instruments they commonly use.
2.1 R
ationales for science and technology
policy at the regional level
The neo-classical rationale for public intervention in
science and technology is rooted in the belief that
public support for science produces social benefits
and that scientists themselves are the ones to control
how scientific development and priorities evolve.
In this model, the generation of knowledge and
technology takes place through a linear process in
which basic research turns into applied research that
is then diffused. In this view, scientific knowledge
is regarded as ‘information’ and considered to be a
public good subject to market failures.
How does this rationale apply to the regional
sphere? Within this neo-classical framework,
science and technology is information that actors
transmit; territory is important as far as the relative
location of actors increases or reduces the costs of
communicating scientific or technological knowledge
understood as information assets. One of the policy
approaches coherent with this view is to try to
reduce communication costs by building supplyside infrastructures such as science and technology
parks. But in general, financial instruments
providing public funds to compensate for insufficient
private investments in R&D are the classical tools
that correspond to this rationale. The inadequate
amount of private resources as a justification for
public investment is a causal explanation as valid for
nations as it is for regions.
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W o r k i n g P a p e r 10
Regional Governments
personal relationships (southern Europe),
partisan relationships (Spain, UK, Belgium), etc.;
The Future of Key Research Actors in the European Research Area
The underlying idea in this regional linear model
is that science and technology production and
economic gains will occur in the same territory, and
that if enough resources are devoted to research
and knowledge production, for instance through
investment in their own regional public research
centres and basic research at universities, this will
turn into innovation and economic growth for the
region at later stages of the process. Information
failures are also important rationales for public
intervention in neo-classical frameworks. Therefore,
in order to increase certainty, regional governments
often create regional development agencies, not only
to channel financial resources but also to manage
the diffusion of information about knowledge,
technology and business opportunities. In any case,
regional policies under this framework are aimed
to provide actors with tangible resources: funds,
physical infrastructure or information.
210
We know from science policy analysis that
rationales have been changing over the last
decades, both at the national and regional levels.
In the 1970s and 1980s, the increasing costs of
research programmes and projects led to economic
and social accountability requests and the
structuring of research evaluation systems (more
or less strong) all over Europe. We have witnessed
a shift from rationales that emphasise insufficient
incentives to invest or information failures to ones
that emphasise institutions, learning capabilities,
and systemic relations between actors. Here,
the notions of ‘clusters’, ‘industrial districts’ or
‘innovative environments’ became examples of how
economic and social gains (or positive externalities)
can emerge from territorial agglomeration,
evidencing the relevance of proximity for collective
learning or of the richness and frequency of the
relationships between the different actors for
innovation outputs. Building regional networks
or clusters involves costs of various types beyond
the capacity of any single actor, although all actors
gain once the network has been established, hence
there is a rationale for public intervention. Despite
these differences in underlying rationales, policy
instruments coherent with this view are only slightly
different from the kind of supply-side measures or
interface mechanisms already mentioned. These
changes in the rationales, with more emphasis in
relational assets, actors’ networks etc. favoured
the entrance of regional governments into this
policy domain as important actors.
However, in these types of socio-economic
explanations of policy, regional governance structures
are largely missing from these perspectives. More
attention is paid to this issue by the innovation
systems approach, which has also been applied to
the regional sphere and recognises the importance
of public institutions for co-ordination, regulations,
laws, the educational subsystem, etc. Interactions
between public institutions, industry and local
universities are central in this view and thus there is
a rationale for regional governments to intervene in
the system in order to ‘organise’ these interactions
in a certain way.
It has become common in the policy analysis
literature to contrast neo-classical approaches
to S&T policies with evolutionary-institutionalist
ones. To put it briefly, the main difference is that the
latter does not consider science and technology as
information but as knowledge, only partly codified,
and thus often difficult to transmit without being
transformed. From this assumption it follows
that it is the capacity to learn what is important
and learning failures that trap actors in wrong
trajectories that take the place of market failures
as rationales for policy intervention. An important
argument in this perspective is that a minimum
diversity in the system (of firms, public centres,
types of knowledge) is needed to allow for learning,
hence the importance of the context and of having
policies that are tailored to the local environment.
Accordingly, there is a rationale for regional
governments to ‘guide’ or ‘steer’ the system and not
only to provide input or financial resources. At the
same time, another important issue is that regional
trajectories might be path-dependent. Here, a
contradiction can be faced, because the extent to
which these path dependent trajectories can be
influenced by policies or the degree in which policy
choices are constrained by them are interesting yet
complex questions. Where is the room for regional
policy if cumulative processes of path dependent
feedback operate?
From an institutionalist point of view, policy choices
are not only limited by economic, cognitive, or
previous trajectories constraints but also by
‘appropriateness’ expectations, and by limits
which are socially constructed by actors and
institutionalised in explicit and implicit norms. For
example, the legitimate model of what university
or public research is or should be might be very
influential in the dynamic of the allocation of
resources between the different actors in the system
and their legitimisation. If consensus-building,
shared values and participation are important, there
might be an additional rationale for intervention at
the regional level, if one assumes that proximity
enhances the building of policy communities.
The constitutional or legal powers of regional
governments is an important factor to consider. In
some cases it is almost the condition of possibility
for regional policies, but this should not be
overestimated: sometimes there are top-down
intergovernmental dynamics by which regional
governments become active in the knowledge
production field as a result of the national policies
that have a regional dimension, or EU regional
policies. Finally, national or EU science policies, by
their very nature, are not designed to fit specific types
of regions or local contexts. Therefore in many cases,
regional governments design policies precisely to
compensate for this and address regional needs and
to try to make the most of regional capacities.
2.2 The diversity of regional intervention
in the science and technology domain
Regional S&T policies are the realm of direct measures
much more than of indirect ones (fiscal being the
prime example) often because regional authorities
do not have jurisdiction over the latter. However,
in their policies to leverage private expenditure in
innovation, some regional governments have applied
indirect measures such as risk capital or equity loans.
When regional governments intervene in the science
and technology domain, the range of policies usually
varies along two lines: promoting the knowledge
and science base, or rather fostering innovation and
technological development, producing very diverse
policy mixes. Regional intervention in S&T can also
be divided according to the supply-demand side
distinction. Some of them are designed to target
the producers of knowledge (universities, research
centres, technological centres) while others target
the users (firms, the public sector) and a third
type is directed to connecting supply and demand
(intermediaries, clusters, networks, parks, centres
of excellence, etc.).
When regional governments target their policy
measures to the supply side of the knowledge
system, the main instrument is often finance,
which then is directed to a variety of objectives
such as: support for public sector research in the
region, support for research training and mobility
(from the region or returning to the region) or
grants and subsidies for industrial R&D. Apart from
financing, regional governments can also provide
services such as information support or networking
measures. Regional policies may also be targeted to
the demand side and be instrumented to systemic
measures or regulation.
The S&T policies of regional governments are in
some cases a complement to national or European
ones and they are directed to those areas or actors
not easily covered by the national or European
R&D programmes. But it is also often the case that
regional intervention uses instruments that replicate
the policies of other governmental levels, and
represent an additional pool of resources but also
a source of regulation. The latter is more likely to
occur in regions or federal states with broad powers
over the policy field and which are willing to invest
large financial resources.
There are also other types of regional policies in
areas that strongly affect the framework conditions
of scientific and technological development. These
include higher and technical education policy,
industrial policy, development and infrastructure
policies, among others.
2.2.1 Supply side measures
R&D supply side measures at the regional level
include a variety of instruments such as the support
of research at local universities, the construction
of public or semi-public technological and research
centres, the support of private technology centres,
and measures to train a highly qualified research
workforce.
Policies targeted to public sector research:
enlarging the knowledge base
Although public universities have traditionally been
financed and managed by ministries of education
and/or research at the national level, in the last
two decades, many EU countries have introduced
reforms to increase decentralisation and autonomy
in the governance of universities. In Belgium,
Germany and Spain, public universities depend
on the regional governments and not the national
ones. But the trend of decentralisation has also
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W o r k i n g P a p e r 10
Regional Governments
All these rationales are mainly of an economic
nature. Political rationales however, should not
be ignored in any account of why some regional
governments intervene in the S&T domain and
others do not. These might be related to the political
preferences of regional government to empower
the regional administration vis a vis the national.
They can be related as well to the degree to which
regional administrative capacities are large or small.
Regional political parties might also decide to enter
this domain, bearing in mind the political gains
derived from successful policies or the salience
of particular actors or interest groups in their
constituencies. In this sense, legitimisation might
be another important rationale.
The Future of Key Research Actors in the European Research Area
been visible in many non-federal EU countries in the
last two decades. These dynamics have provided
opportunities for the involvement of regional
governments in the funding of higher education
and university research. Regional governments
have combined grant block funding for education
and research activities with competitive funding for
research in the form of research projects or grants to
individuals, research groups, or using performancebased funding formulas to institutions (for example
in Scotland and some German Landers).
Technological centres
212
Some regional governments have adopted a
supply-side approach to research and innovation
policies focusing on applied research. Within this
perspective, support for technological centres (TCs)
that work as service providers for regional firms has
been a strong focus. In these cases, the strategy of
the regional government has been to improve the
technological capabilities of their industrial sectors
in a collective way. Two interesting examples are
the Basque and Valencia regions in Spain where
TCs have become the basic tool of the S&T policy,
through strong financial support.
These two cases are of special interest. They
exemplify how regional government strategies
in the S&T domain can affect the landscape of
organisations that produce knowledge in the region
and contribute to the consolidation of new modes
of knowledge production and organisation (notfor-profit and with a strong focus on the provision
of science and technological knowledge to private
firms) which then diffuse nationally and become
legitimised. Later on, other regional governments
have followed a pattern of creating their own
research centres. Imitation among regions promoted
isomorphism within this population of research
centres and the number of technological centres
has increased enormously in Spain in the last two
decades. This bottom-up convergence process
contributed, in the second half of the 1980s, to
official national government recognition of the TCs
(strongly regionally-rooted) as key players of the
national system of innovation.
Research training and mobility policies
Ensuring a highly qualified workforce with the
necessary skills to work and live in the knowledge
economy and society has been an important driver
of many regional initiatives. Regional governments
have invested in human capital creation mainly
through instruments directed at graduates. That
include research training fellowships to part-finance
their PhDs in the universities of the region, and also
thorough mobility schemes to promote the training
of their regional graduates and PhD in international
research organisations with the expectation that
they would return and deploy their quality and
capacities back in the regional system.
2.2.2 D
emand side policies and systemic
instruments
Regional Clusters
One of the clearest applications of the systemic
approach to regional S&T policies has been
cluster policies. The policy focus is slightly
different among them: whereas the regional
system of innovation approaches emphasises the
ability of the system to generate innovations and
propose integrated general policies in interrelated
domains, cluster policies are usually targeted
to generating a regional market competitive
advantage in some particular area. Basically,
a cluster is a concentration of industries that
support each other. The construction of relational
assets (both horizontal and vertical) is the main
policy focus. Cluster policy might include various
policy instruments and it is used to design
policy mixes, and sometimes even to integrate
different horizontal policies (industrial, economic,
employment, innovation...). The underlying idea
is the specialisation of the region in productive
activities where competitive advantage can be
constructed and preserved, but the policy goal may
also be to increase the collaboration of local users
and producers of knowledge and technology.
The cluster approach has been adopted in various
forms in regional S&T policies across Europe (the
Basque region in Spain, Flanders in Belgium and
Scotland in the UK, are some examples). In some
cases the approach has been adopted at the macro
level and the policy context has been industrial
policy, development policy, and more recently
innovation policy. At the micro level, policies have
aimed to identify firm level networks and promote
their competitiveness, often with a strong emphasis
on SMEs. Whenever regional governments have
intervened in the S&T domain with the objectives of
promoting clusters they have pursued some or all of
the following objectives (OECD, 2005), depending
on how comprehensive the policy has been:
• Create favourable framework conditions: ensuring
a qualified labour supply by supporting local
universities and technical schools, supporting
• Increase the awareness of the benefits of networking
and facilitate the exchange of knowledge through
regional platforms, forums, etc.;
• Provide financial support (in the form of grants,
projects) for cooperation among the actors in the
region;
• Create or support intermediary, brokerage
organisations or network agencies operating in
the region.
Despite being an initiative of the Federal
Government, probably one of the best known
European examples of regional cluster policy is the
Bio-Regio Programme launched by the BMF in the
mid-1990s, an initiative which allowed regions to
build their cluster infrastructures in biotechnology.
The objectives of the programme were several: to
support start-ups in the biotechnology sector, to
improve the competitiveness of the region and to
increase knowledge and technology transfer among
regions. Three regions were chosen (Rhineland,
Rhine-Neckar and Munich) mainly on the basis of
the existing infrastructure and their capacity in all
the stages of the innovation process including the
production of basic knowledge. The success of the
policy was revealed by the employment increases
and by the growth in the biotech firms in the area.
One of the premises of the clusters policy is that
financial support must go the stronger areas in
regions where there is endogenous potential.
Lessons learnt since the start of the Bio-Regio
include that public financial support is more
effective in regions where there is mobility between
research, education and industry, and where large
companies are integrated into the processes of
developing start-ups (EC, 2003).
Another interesting example is Scotland. More
than a decade ago, Scottish Enterprise was one
of the first economic development agencies to
apply the cluster approach, and the approach was
supported with significant funding and resources
(€ 360 million over six years). Designing ways in
which regional public policy could create links
among firms and between them and other actors
took a long time, large resources and effort. The
results have been positive; now Scotland has many
enterprise clusters and others are emerging. These
and other examples show that although cluster
policies are not very costly in capital terms, they
are very intensive in human capital terms, demand
a lot of administrative capacitiy, and require
specialised intermediaries. Therefore, the costs
implied suggest that this is a regional strategy that
requires an in-depth ex ante evaluation of the real
endogenous potential (OECD, 2005). An additional
example is the policy approach to innovation of the
Basque Regional Government, which traditionally
focused on supply-side technological policies and
turned into a more systemic cluster approach from
the mid-1990s.
Technological Parks
Science and technological parks are the policy
translation of the rationale that proximity matters.
These instruments have in common the fact that
they have a strong spatial dimension. They are
spaces designed to ease knowledge transfer,
cooperation and networking through co-location.
One of the oldest policy instruments to promote
regional research and innovation has been the
creation of technological industrial spaces.
Following the success of Silicon Valley, this best
practice led to a series of imitations, some of them
in Europe. Regional governments have developed
high expectations about science and technological
parks as boosters of local employment and regional
regeneration.
Some science parks promoted by regional
governments have evolved linked to a university,
with the main objective to foster spin-offs from
the public sector (for example Cambridge in the
UK or Barcelona in Catalonia). But there are also
examples across Europe of technological parks that
stand alone, developed by regional governments
as incubators for SMEs or to attract large firms
(for example Zamudio in the Basque region, or – if
considered as TP – Sophia Antipolis). Whatever the
case, this instrument requires a significant and
long-term investment from the regional government
and involves coordination with other policies such
as infrastructure, transport and communication
that often require the involvement of the national
or federal government.
2.2.3 The regional policies of national
governments: programme contracts and
other instruments
So far we have described some of the ways in which
regional governments develop their own S&T policies
based more or less on autonomous decisions to
develop initiatives in this area. However, in many
countries, the entry of regions into this policy
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the mobility and return of S&T human resources,
building regional infrastructure, or providing
strategic information through foresight studies;
The Future of Key Research Actors in the European Research Area
domain has been the result of national policies
with a very strong regional focus. Sometimes
regional governments have to develop their policies
in the context of seeking or competing to receive
or integrate funds or programmes at the national
or EU level. In these cases, it is not autonomous
regional policies, but rather bottom-up strategies to
accommodate top-down programmes and funds into
their policy frameworks.
The instruments by which central governments
have developed their regional research and
innovation policies vary across Europe. Programme
contracts, by which the central government and
the region jointly finance the programmes and
policies in the contract, have been common in
various countries in Europe.
214
One interesting example has been the Regional
Centres of Expertise (CoEs) programme in Finland.
The number of CoEs has risen from eight to
twenty-two since the beginning of the programme,
contributing to the creation of 10 000 new jobs and
850 new enterprises. CoEs compete annually for
government funding and this basic fund is matched
by a contribution from the region’s partners. In the
first programme, for example, cities, municipalities
and regional councils all together contributed to
24 per cent of funding.
Another example of regionalised national policy is the
Higher Education Innovation Fund (HEIF) in the UK.
This operates as a joint fund from the Department of
Education and Skills, the higher education funding
council for England and the Department for Trade
and Industry, and its objective is to facilitate the
interface between universities and business, and
in general, the regional community and economy.
Also in the UK, a very recent example of the role of
universities in regional science development has
been the “Science Cities Programme” launched
in September 2005 from the Chancellor of the
Exchequer for six major UK cities to prepare and
deliver science and technology based strategies for
economic growth based on the strengths offered by
various cityregions (Cunningham, 2005).
In any case, these examples show that the
absorptive capacity of regions in institutional,
organisational and structural sense is important
when analysing the differential impact of the same
national or EU policies in the involvement of regional
governments as a response to other governmental
levels programmes and funds.
3. Recent key trends
affecting the role of
regional government
The purpose of this chapter is to provide an overview
and analysis of the forces and general trends that
condition regional governments’ involvement in
knowledge production and research system support
activities.
3.1 Europeanisation and Regionalisation
There are two central trends that affect the roles
and functions of regional governments in science,
technology and innovation, as in many other
policy fields: Regionalisation and Europeanisation.
The result of the interactions between the two
forces is conditioning the involvement of regional
governments in the governance of the ST&I systems
as much as the rationales for interventions presented
in section 2.
Regionalisation
In the last decades in Europe we have witnessed a
shift towards a more significant role for regional
governments in policy-making, specifically in science
and technology policy related issues. Sub-national
authorities (SNAs) have gained competences and
functions in policy-making but the trends vary
between countries. Within this general move to
reinforce the role of the SNAs in policy-making, there
are, however, diverse converging trends in different
countries.
Before the Second World War, the dominant pattern
of political systems in Europe was a fairly unitary and
centralised States model. Since then we have slowly
moved into a world in which some countries have
become politically reorganised into federations or
quasy-federal countries (Germany, Austria, Belgium,
Spain, etc.), even if the dominant pattern of emerging
federalism has been one related to ‘holdingtogether’ more than ‘coming-together’, as was the
classical US federal model (Stepan, 1999). Under
these dynamics, the key element usually relates to a
political dynamic associated to mobilisation.
In fact, experts in federalism insist that in the present
situation the basic feature of the new generation of
federal arrangements is the recognition of the de
jure asymmetry in terms of the competences of the
members of the federations, that is additional to the
We have also witnessed a strong movement
of ‘decentralisation’, or transfer of some
implementation competences to different types
of regional authorities, in some of the traditional
unitary states. France is probably the most significant
case, in which two different laws of ‘decentralisation’
(1983 and 2004) have contributed to the emergence
of regional and local authorities as players in more
and more policy fields (Herauld & Crespy, 2005).
Finally, in some countries, like in the UK, in the context
of the ‘devolution’ processes (Keating, 2002) we
observe a significant combination of federalisation,
particularly with respect to Scotland and Wales, and
decentralisation of the implementation of policies in
the case of England.
Europeanisation
Over the years, along with regionalisation, an
overlapping trend has been identified in the
European countries involved in the construction of
the EU and other European cooperation mechanisms:
the dynamic of European Integration.
An examination of the literature theorising
about the EU could also make a contribution to
our understanding of the dynamics of regional
government involvement in different policy fields
and their interaction with national governments.
Research on Europeanisation has focused, over
time, on different issues that are of relevance for our
understanding of the dynamics of the interaction
between regional governments and ERA.
A recent review (Pollack, 2005) presents the early
work on Europeanisation (neofunctionalist theories
of regional integration, intergovernmentalism,
historical, institutional and rational choice
approaches, constructivism, etc.). It focuses mainly
on the ‘integration process’ that has been explained
either as a functional spill-over of the first decision
to cooperate, mainly based on the expectation that
a kind of diffusion patterns from the way in which
policy domains influence one another, or as a result
of the interaction between the national preferences
and intergovernmental bargaining. In most recent
research, the effects of EU institutions are assumed
to influence not only the incentives confronting the
various public and private actors, and thus their
behaviour, but also the preferences and identities of
individual and member governments. The impact of
Europeanisation is pervasive, not only in the policy
areas affected but also in the way in which national
and regional actors construct their preferences and
identities.
However the main problem with these approaches is
that they have conceptualised the EU as a process
of integration. In doing so, they have neglected the
politics of the EU, as well as its characteristics as
political system.
Some other approaches, that have mainly applied
the traditional tools of comparative politics,
have been trying to cope with those limitations
to understand the construction of the European
political system. A significant concern has been
on the vertical separation of powers between the
Council, the Parliament and the EC and its change
over time, and a reflection on the motives that EU
governments have in delegating specific powers and
functions to the Commission and other supranational
actors. With respect to the role of the regions in the
European political system, the EU has recognised
this role through the Committee of Regions (CoR).
The Committee of the Regions (CoR) is the political
assembly that provides local and regional authorities
with a voice at the heart of the EU. It was established
in 1994 and was set up to address two main issues.
Firstly, about three quarters of EU legislation is
implemented at local or regional levels, so it makes
sense for local and regional representatives to have
a say in the development of new EU laws. Secondly,
there were concerns that the public was being left
behind as the EU steamed ahead. Involving the
elected level of government closest to the citizens
was one way of closing the gap.
The Treaties oblige the Commission and Council
to consult with the CoR whenever new proposals
are made that will have repercussions at regional
or local levels. The Maastricht Treaty set out five
such areas – economic and social cohesion, transEuropean infrastructure networks, health, education
and culture. The Amsterdam Treaty added another
five areas to the list – employment policy, social
policy, the environment, vocational training and
transport – which now covers much of the scope of
the EU’s activity.
Outside these areas, the Commission, Council and
European Parliament have the option to consult the
CoR on issues if they see important regional or local
implications to a proposal. The CoR can also draw up
an opinion on its own initiative, which enables it to
put issues on the EU agenda.
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traditional de facto asymmetry in socio-economic
resources that also existed in the classical model of
federal countries.
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There are three main principles at the heart of the
CoR’s work:
Subsidiarity. This principle, written into the Treaties
at the same time as the creation of the CoR, means
that decisions within the EU should be taken at
the closest practical level to the citizen. The EU,
therefore, should not take on tasks that are better
suited to national, regional or local administrations.
Proximity. All levels of government should aim to
be ‘close to the citizens’, in particular by organising
their work in a transparent fashion, so people know
who is in charge of what and how to make their
views heard.
Partnership. Sound European governance means
European, national, regional and local government
working together – all four are indispensable
and should be involved throughout the decision
making-process.
However, one relevant issue is that among the six
Commissions in which the CoR is working none
refers to R&D and innovation in its titles.
216
Another stream of work on Europeanisation has
concentrated on the horizontal separation of powers,
thinking of the EU as a federal system. From this
analysis, Wallace (2000) has pointed out that the
choice of a given level of government – federal/EU
versus national/state – could be theorised through the
metaphor of a pendulum, where the choice of policy
arena varies depending on a number of contextual,
functional, motivational and institutional factors.
Multilevel Governance?
Finally, it is worth mentioning that there is an area
of convergence of both streams of literature on
regionalisation and Europeanisation. In the last 15
years, we have witnessed an intense debate over
the role of regional authorities in the European
integration (for instance Hooghe, 1996a; Jeffery,
1997a; Keating, 1998). In fact a label has been
established – ‘sub-national mobilisation’ – (Hooghe,
1995) to account for the growing engagement
of sub-national authorities (SNAs) (Bloberg and
Peterson, 1998), a term referring to all sub-national
governmental authorities at local, intermediate
or regional levels, with EU institutions and policymaking (Jeffery, 2000). The general features of this
increasing involvement have been documented.
However in some of the approaches there is a claim
that a new pattern of ‘multilevel governance’ in the
EU which stretches not only above, but also below
the level of nation-state, has emerged. Labels such
as “the Europe of the regions” express the existence
of a third regional level emerging to provide input
into the EU policy-making process.
The governance approach could be taken as
a ‘framework for analysis’. They insist that EU
issues, and especially policy-making, cannot be
treated as an international organisation or as a
domestic political system, but rather as a new
and emerging system of ‘governance without
government’. The MLG concept contained both
vertical and horizontal dimensions: ‘Multi-level’
referred to the increased interdependence of
governments operating at different territorial
levels, while ‘governance’ signalled the growing
interdependence between governments and
non-governmental actors at various territorial
levels (Pollack, 2005, p.383, quoting Bache &
Flinders, 2004).
The governance approach can be traced to Gary Marks’
work (1993) on the making and implementation of
the EU’s Structural Funds. Marks originally argued
that the Structural Funds of the 1980s and 1990s
provided evidence that central governments were
losing control to both the Commission (which played
a key part in designing and implementing the funds)
and to local and regional governments inside each
Member State (which were granted a partnership
role in planning and implementation by the 1988
Reforms of Structural Funds).
Consistent with the approach, it is regularly
reported that the implementation mechanisms
of the EU Structural Funds have created the
conditions for a more relevant role of regional
authorities, either alone or in ‘cooperation’
with the national authorities, in the definition
of the objectives. Greece, a strong unitary and
centralised state, is always mentioned as a case
in which EU regional policy has helped to set up
regional authorities for implementation of some
EU policies. The influence of the EU level is also
present in the case of the new members from
Eastern Europe so that they even shape their new
political and territorial administration in a way to
cope with the ‘federal’ expectations apparently
emerging from Brussels (Brusis, 2002; Hughes,
Sasse & Gordon, 2004).
However, later studies of the EU Structural Funds
questioned Marks’ far-reaching empirical claims,
noting in particular that EU member governments
continued to play central roles in the successive
Hooghe (1996) qualified the far-reaching claims
of earlier studies, demonstrating that in some
cases, new and existing regional authorities were
able to draw upon EU resources and on their place
in emerging policy networks to enhance regional
autonomy, whereas in other states, such as the UK
and Greece, central governments were able to retain
a substantial gate-keeping role between the EU and
sub-national governments. In fact Hooghe, Marks
and others have aimed to explain the substantial
variation in the empowerment of supra and sub
national actors in the various Member States by the
EU Structural Funds.
Despite this cross-national variation in outcomes,
Hooghe & Marks (2001) find and purport to explain
what they call ‘an immense shift of authority’, from
national governments to the European arena and
to sub national and regional governments, in many
states including France, Italy, Spain, Belgium and the
UK. Although it remains controversial whether such
devolution was driven wholly or in part by European
integration or by purely national considerations,
we cannot forget the increased role of regional
authorities in EU policymaking, particularly in some
policy areas.
However, even if considering that the main roles
of SNAs and central government institutions in
the context of the EU policy making should be reassessed, the ‘real transformation in the relative
roles of SNAs and the central state in EU policymaking has taken place in the intra-state arenas,
in which sub-national mobilisation has served
primarily to undermine the capacity of central state
institutions to maintain a monopoly competence
over the integration policy’ (Pollack, 2005).
The MLG approach has serious theoretical limitations,
because it neglects the intra-state environment in
which SNAs are embedded. As a result, the MLG
model overestimates the significance of central
state-EU interactions in catalysing sub-national
mobilisation. Some scholars argue that we need a
wider concept of MLG which is capable of presenting
an additional domestic politics perspective, focused
on those more significant intra-state factors, which
support and catalyse sub-national mobilisation
(Jeffery, 2000, pp. 2-3). In fact, there is evidence that
the Europeanisation process has produced different
structures and consequences in different federal
countries (Kovziridze, 2002).
Some lessons
From the literature analysed here there are some
lessons that could be taken on board and they
deserve to be elaborated for future analyses.
For the purpose of our analysis about the future of
regional governments as key actors, it is relevant to
extract a long-term historical lesson, that refers to
the permanent movements and tensions, in the last
century, from unitary to decentralised countries and
back again (Rokkan, 1980). Therefore, we should not
think in terms of any kind of historical and irreversible
trajectory of regionalisation, decentralisation and
Europeanisation that will drive the states’ model we
know to extinction. Moreover, we should probably
expect radical points of departure in present trends.
The history of the EU, in this case the ERA, can be
viewed as a series of centralising initiatives (giving
power to the EU authorities) followed by periods of
retrenchments or devolution.
The second lesson we could draw from the literature
is that the main driver of empowering the regions
in the European context is much more related to
national or state-level dynamics. Understanding
why in some countries there are pressures and
movements for federalisation, devolution or
decentralisation is something that should be framed
at country level.
Of course this second lesson does not preclude us
from mentioning that, for some specific purposes,
the implementation of European policies has played
a significant role or contribution in supporting the
empowerment of regions, and that some of the
policies taken are heavily related with the S&T and
innovation policy domain through development
strategies.
Fourth, the impact of Europeanisation is pervasive,
not only in the policy areas affected but also in the
way in wich national and regional actors construct
their preferences and identities.
Finally, the present situation characterised by
strong diversity among regions does not give any
indication of convergence in their actions related
to the development of ERA. The diverse conditions
of departure, plus the diverse degree of implication
could produce an increase of inequalities among
European regions with respect to their roles and
function in S&T and innovation.
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reforms of the funds, and that these Member States
remained effective ‘gatekeepers’, containing the
inroads of both the Commission and sub-national
governments in the traditional preserve of state
sovereignty (P, 1995, Blache).
The Future of Key Research Actors in the European Research Area
218
3.2 Increased involvement of regional
governments in science and innovation
issues and the role of Structural Funds
capacities in terms of equipment and laboratories
in order facilitate the move towards a knowledgebased economy.
We now turn to the more specific trend of the
involvement of regional governments in research
and innovation policies in particular. As already
pointed out, regions have emerged as very important
players for the development and structuring of the
ERA (EC, 2001). Regionalisation of research policies
has responded to two driving forces. On the one
hand, regional governments have been more and
more aware of national and EU research policies
and have tried to tune them to better fit their social
and economic needs. On the other hand, they
have acknowledged the very strong relationship of
building their own research and innovation capacity
with their regional economic and employment
development.
One could say that the European Social Fund
and the European Development Fund have both
been funding activities that are relevant to the
knowledge-based society and economy. These
Structural Funds have supported, above all, research
capacity-building, with a strong focus in the material
and physical conditions. In a complementary but
different direction, the RTD Framework Programmes
have supported cross-national research projects
and networks based on scientific and technological
excellence, and on socio-economic general impact.
The nature of the policy and politics involved in both
types of funding is very different. Whereas the former
have a strong redistributive nature, the latter might
be framed in the distributive type of policy. Future
developments in these funds will have a strong
interaction with the role of regional governments in
the ERA.
Undoubtedly, the recent trend in the involvement of
regional governments in knowledge and innovation
policies has been an increasing one. Behind this
generalised trend however, strong differences persist
in orientations and approaches. In many occasions
the policy mix has depended on the different degree
of development of the regions: whereas in less
developed regions resources have been targeted
at improving the framework conditions that are
related to physical infrastructures and human
capital and R&D capabilities, more developed
regions have invested in services, intermediary
and other types of networks, and institutions to
promote cooperation and innovation. In this second
case, the instruments go beyond the classical
support for basic research and training schemes
and deal mostly with incentives. But both types of
conditions are necessary for knowledge production
and diffusion and it has been a common path that
regional governments have applied the approaches
sequentially.
Structural Funds have had an impressive role in the
socio-economic transformation of many regions in
Europe. Structural funds have allowed, in many less
developed regions, the development of policies to
improve those framework conditions referred to
above, mainly physical infrastructure, not specifically
for research but rather for communication, transport,
energy networks etc. Expenditure in these types of
public goods have for long enjoyed a high degree
of legitimisation, and almost nobody questions
the rationale for public intervention at the EU,
national or regional level. Initially, Structural Funds
activities in less favoured regions concentrated on
physical infrastructure, which was essential to build
We know that priorities have been changing, even
for the Structural Funds, which have been placing
priority on more intangible regional assets, such
as the promotion of research, innovation and
information society, on building partnerships
between universities and industry (especially
SMEs) and on training human resources with RTDI
skills. The programming of the Structural Funds for
the period 2000-2006 for Objective 1 regions gave
a strong weight to those issues. The question is
whether this approach can be maintained for new
accession countries which have not yet developed
the necessary infrastructure conditions.
The classical Structural Funds approach has
been complemented more recently with new
policy developments at the EU level, and
intangible investments in education, institutional
assets, training and research are now widely
acknowledged. Worth mentioning are the Regional
Innovation Strategies action (RIS), the Regional
Information Society Initiatives (RISI), and the
Regional Innovation and Technology Transfer
Strategies (RITTS). These pilot programmes,
started by the Commission in the mid-1990s, are
now being implemented in around 100 regions
in Europe, and they represent an example of the
policy translation of the rationales grounded in
the regional innovation systems approach. The
main objective of these actions has been to provide
regional authorities with some instruments to
create a proper institutional environment in order
to promote cooperation among the actors in the
At the beginning of 2001, the EC issued a Call to all
regions in the EU (160) to apply for grants to develop
a ‘regional program of innovative actions’ for a period
of two years to fund 50 per cent of eligible costs.
The European Regional Development Fund, with a
budget of € 400 million for 2001-2006, managed
this. Proposals were expected to be submitted
directly by the competent regional authorities. The
initiative had the explicit aim of helping less favoured
regions to design regional policies that prevent
regional disparities to grow/to reduce the gap in
relation to the knowledge society and economy.
It was established as a criteria that each proposal
should have a strategy for envisaging innovative
actions agreed among different regional actors, and
should focus on developing ‘intangible competitive
factors’. The three strategic themes were proposed
by the Commission. The first was called ‘Regional
economies based on knowledge and technological
innovation’. To achieve this, regions were encouraged
to formulate regional programmes with the objective
of increasing cooperation and interaction between
the research and business communities. The other
two were: ‘eEurope Regio: the information society at
the service of regional development’ and ‘Regional
identity and sustainable development’.
The applications to this Call can be analysed in order
to draw some conclusions about the recent trends in
how regional governments envisage their policies in
the knowledge and innovation domain. The majority
of the proposals, almost 70 per cent, focused fully or
partly on the first issue and were innovation-related.
Less developed regions were strongly represented
within this group and although only a proportion
within this group (16 regions) proposed specifically
cluster-type actions (firm to firm cooperation), almost
all of them (60) focused on some type of networking
actions, particularly trying to connect the demand of
local firms to the supply or regional knowledge base
(Bellini and Landabaso, 2005). It is very interesting
to note that in the group of regions which proposed
cluster-type actions, the regional governments were
meant to act as ‘facilitators’ or ‘brokers’ providing,
most of all, institutional assets and information
services rather than directly financing the firms.
It has also been seen that the type of cluster
proposed varied across regions depending on their
development level. Objective 1 regions proposed
traditional business networks based on sectors.
More advanced regions proposed actions to integrate
information and communication technologies
in SMEs as a way to facilitate networking and
cooperation via these technologies. A third cluster
category, closer to the traditional cluster based on
vertical integration was also proposed by some
regions, where the automobile sector was strongly
present.
These EU policy initiatives have had a strong policy
impact in the formulation of the programming of
the Structural Funds for the period 2000-2006
(EC, 2001).
3.3 Other trends
Interregional cooperation networks
Cross-national regional cooperation has also been
a major theme of EU structural policies through the
INTERREG part of Community initiatives. The scheme
has continued over the years and the INTERREG III
(2000-2006) has three parts, two of them addressing
RTDI activities.
Regional disparities persist
A less positive trend has to do with the persistence
of strong regional inequalities. Data and analyses
indicate that the technology gaps between the
less and more advanced regions and those in
which the expenditures on research, development
and innovation is higher has widened rather
that narrowed, and that this gap is reflected at
the regional level (Howells, 2005). Disparities in
economic performance and innovation capacities
in Europe remain between central and peripheral
regions, as the EC statistics show. These differences
are reflected in the many indicators both of public
and private investments that are also mediated by
the limited technological absorptive capacities of
predominant firms in some regions, and the level of
qualification of the human resources in their labour
markets.
Increased financial contribution of regional
governments in funding research
Regional governments are politically committed
to research and innovation policies. SNAs have
developed an increasing rhetoric related to the
role of research and innovation in the context of
their strategies to cope with economic growth and
development. In many cases, regions with limited
government capabilities and financial resources kept
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innovation system. Consensus building among
the actors is seen as essential. However, some
analyses have pointed out the difficulties in getting
success in regions where there was not a previous
innovation system (Bellini and Landabaso, 2005).
The Future of Key Research Actors in the European Research Area
their policies in the rhetorical domain with no real
effective action. However, more and more, regional
authorities, specially those included in federal and
quasi-federal arrangements, define research and
innovation as central elements in their political
agendas and allocate their own financial resources
from their regional budgets. For example, in Spain,
the overall contribution to competitive funding made
by all regional governments is increasing every year
and it is now around 50 per cent of the national
government (Sanz-Menéndez, 2005). In Germany
too, the regional governments play a critical role in
funding research in universities and, in 2003, 83 per
cent of the overall funding of Landers was directed
to universities and university hospitals (BMBF 2005,
p.20; Koschatzky, 2005).
4. Driving forces for
change and future
trends
220
The purpose of this chapter is to calibrate how the
existing forces (both internal and external) that drive
the involvement of regional governments, may change
in direction or magnitude over the next ten to fifteen
years and to discuss which new forces may arise.
To identify the forces for change and the future
trends we should first have a set of middle-range
theories or analytical frames that could predict the
developments and estimate the disruptive forces.
Understanding the driving forces requires having
an underling theory about the dynamic and about
the question of why national governments ‘transfer’
competences up-and-down-stream.
We could just
explanations:
comment
on
two
types
of
a)there are economic explanations that assume
the rationality of actors and the purposive
nature of their actions, related to two main
rationales: increasing the efficiency of public
policies and reducing the transaction cost.
Increasing the efficiency of public policies is
always used as main criteria for decisions.
Recently, Fritsch and Stephan (2005) have
summarised some of the arguments related to
the more efficient implementation of innovation
policies at regional level.
There is a second economic approach to the
issue of ‘responsibility transfer’ that relates
to the idea of reducing transaction costs. It
is interesting to note that the literature on
Europeanisation has placed a lot of efforts into
understanding the motivations that national
governments have in delegating specific
powers or functions to the Commission and
to other actors related with the reduction
of transaction costs of policy-making, in
particular allowing national governments to
commit themselves credibly to international
agreements and to benefit from the policyrelevant expertise provided by supranational
actors. This explanation has not been used
to account for regionalisation, but it should
be taken into account because it could
explain the trend of creating European
instruments, such the European Research
Council, to implement research policy aiming
at excellence, which compete with the trend in
favour of regionalisation. Both explanations,
and additional ones related to principal agent
models of delegation, are associated with an
underlying idea of power asymmetries between
different governance levels and decisions and
initiatives taken by national governments.
b)There are also explanations more associated
with political elements and reflect bottomup approaches such as the mobilisation of
regional governments to reinforce or reassert
their power position with respect to the national
governments.
As mentioned, we should develop parallel
approaches to regional governments as actors
and as arenas.
4.1 R
egional Governments as actors in the
ERA governance
SNAs are differently constituted thought the EU,
and they display wide variations both between and
within Member States, either becoming involved
with EU matters or with S&T policy issues: a) in their
capacity and commitment to mobilise b) in their
ability to transform mobilisation into influence.
An important issue relates to the fact that in research
and technological development and innovation
(RTDI), the EU has a subsidiary role with respect to
the national governments. However, to cope with
the diversity of situations and ‘à la carte’ approach,
new procedures have been established such as the
so-called ‘Open Method of Coordination’ (OMC).
To explain the relative influence of SNAs on ‘EU
policy making’ or on S&T and Innovation policies, we
should first take into account the following realities:
A. The constitutional factors vary between the
countries. We could re-elaborate the typology
suggested by Loughlin (1997): 1) Federal or quasifederal states (Austria, Belgium, Germany and
Spain). 2) Regionalised unitary states (France, Italy,
the UK and arguably Portugal and most of the new
EU Member States and new accession countries).
3) Decentralised unitary states (Denmark, Finland,
The Netherlands, Sweden). 4) Centralised unitary
states (Greece, Ireland, Luxemburg, and predevolution UK).
SNAs constitutionally endowed with more internal
competences (in federal or quasi-federal countries)
are likely to exert stronger influence over European
policy or S&T policy than their more weakly endowed
counterparts. A continuum of stronger to weaker
SNAs influence in EU policy-making policy or S&T
policy can therefore be expected to exist in relation
to differences in the internal structure of Member
States (MS).
From this point of view, the constitutional situation
of SNAs, within their own countries, is logically
the variable with the most predictive power in
pinpointing the level of influence SNAs have in
European policy or S&T policy. The argument is
simple: a German Lander versus the local authority
in Ireland. For example, German Landers, Spanish
Regions and Belgium Regions and Communities
have full responsibilities over the higher education
institutions in their regions, while in other countries,
universities are under the authority of the national
government, independent of their diverse level
of autonomy. In the domain of ‘innovation policy’
taken as general support of the regions’ innovation
capabilities, we could mention that almost all
regions, either with strong or weak government
capabilities, have implemented some actions of the
type mention in section 2.
However some caveats or considerations should
be stated. Firstly, there are internal asymmetries
in the scope of SNAs competencies – for instance
the Spanish asymmetric federalism. Secondly,
the existence of multiple SNAs with competing
interests in the EU (for instance, big metropolitan
governments and regional authorities, or French
departments and regions; Spanish regions and
provincial governments, etc.). And finally, the
existence of processes of constitutional change in
some countries, which directly or indirectly affect the
capacity for EU policy (or S&T policy) engagement
by SNAs (Belgium, Germany, UK devolution, recent
Spanish debate on redefinition of the Regional
Constitutions, etc.).
But we should consider that constitutional factors
are not the sole variables in predicting and
explaining the different levels of influence (or
involvement in S&T policy of regional government).
It is possible to expect or it is quite conceivable
that a constitutionally stronger SNA in one Member
State could exert less influence in EU policy that a
constitutionally weaker SNA in another (for example,
La Rioja in Spain versus the Birmingham City Council
in regional policy issues). In summary, intra-state
differentiation is, in other words, just as marked a
phenomenon as inter-state differentiation, but the
explanation of that diversity should be based on
different grounds. Therefore, we should take into
consideration a set of variables beyond that of
simple constitutional position intervening to modify
the likely levels of influence exerted by SNAs both
across and within particular constitutional orders.
These are the following:
B1. The quality of intergovernmental relations
between SNAs and central states. Formal structures
are more likely to provide effective channels for
policy influence than more informal interactions.
Learning and interacting in S&T policy-making issues
is a critical factor.
B2. The level of entrepreneurship applied in
sub-national mobilisation. Effective administrative
adaptation, leadership and coalition building
strategies in response to the challenges posed
by European integration are likely to improve the
prospects for influencing European decision-making.
In areas like the Knowledge Economy – related with
economic development – the level of entrepreneurship
of the regional authorities, even without strong
constitutional competences, is a relevant variable to
explain the degree of involvement. Of course there
are limitations emerging from the strength of the
financial base of regional authorities to implement
their policy agenda, even if knowledge is strongly
associated with regional development. The more
regional economic development is considered to
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W o r k i n g P a p e r 10
Regional Governments
From a macro level of analysis we suggest a general
account model of the influence of the SNAs on the
S&T governance in Europe, and thus the influences
on the ERA dynamics (based on Jeffery, 2000). What
basic forces could explain the diversity of SNAs
influence either on S&T & Innovation and EU policymaking in this field?
The Future of Key Research Actors in the European Research Area
depend on innovation, the stronger the rationale for
regional intervention.
B3. Legitimacy and social capital. The credibility
of SNA claims for influence in EU decision-making
is likely to be enhanced by the perceived legitimacy
which SNAs bring with them into the European policy
process. SNAs representing strong sub-national civil
societies have more opportunities to influence this
process.
Finally we should bear in mind that regionalisation
‘is not a wave sweeping across Europe and
transforming the architecture of politics in a uniform
manner’ (Keating, 1996).
4.2 R
egional governments as arenas in
which other S&T actors play political
games
222
It has already been pointed out that there are
simultaneous trends of regionalisation and
decentralisation in Europe, and this has also
affected the science and technology policy domain,
with an open debate on the functioning of the
multilevel governance system. Regional authorities
have become directly involved in the design and
implementation of regional S&T policies, however
the interventions of sub-national governments
are much more diverse than the prevailing view
about the convergence of regional policies towards
innovation policies might imply. In this section,
we turn to internal dynamics, in order analyse
the factors and reach conclusions about the
circumstances under which regional governments
are able to implement policies of a scientificacademic approach or, on the contrary, others
more oriented to innovation and technological
development. Despite the influence of some
structural factors, especially as regards initial
political preferences, one should not underestimate
the relevance of the mobilised interests
concentrated in the region, because changes in
policy orientation are particularly difficult when
those interests play a role in the administration
of such policies. Once a regional government has
adopted a particular approach, preferences towards
a policy re-orientation or change are more likely to
succeed with the aid of appropriate administrative
arrangements, especially along with significant
budget increases.
Traditionally, only the regional authorities of some
federal states were involved in science, technology
and/or innovation policies. For instance in Germany
and Switzerland, the constitutional arrangements
for governing the research system and even some
basic research institutions, such as the German
Research Council (DFG) or the Swiss National
Science Foundation, were designed for cooperation
(Wilson and Souitaris, 2002) between the Federal
Government and the Landers or Cantons a long time
ago. But today centralised states, such as France,
Sweden or The Netherlands have involved regional
and local authorities in development and innovation
policies (Kaiser and Prange, 2004b).
A pervasive explanation of the increasing
regionalism and regionalisation in Europe has
been the impact of EU Structural Funds (Benz and
Eberlein, 1999; Adshead and Quinn, 1998) and
also the EC’s role in ‘awaking’ or enlightening subnational governments, that has contributed more to
promote strategic thinking among regional players
than to measured outcomes in terms of RTD and
innovation objectives (Kuitunen, 2002), scholars
insist on a variant of the arguments related to the
‘power of policy ideas’ (Hall, 1989) or policy diffusion
(Majone, 1991; Dolowitz and Marsh, 2000), this is the
case for the UK (Martin, 1998), even in the context
of devolution (Keating, 2002), and France (Smith,
1997), but also for other federal countries, like
Austria in which their Länders entered in innovation
policies mostly as result of policy diffusion processes
from the EU (Sturn, 2000). This influence of the EU
level is also accepted for Germany, even if Länders
implemented innovation policies and regional
development in the mid-1970s as a way to ‘respond’
to the industrial crisis and economic recession of the
time (Scherzinger, 1998).
Apparently there is an underlying agreement
that, at the European level, regional authorities
had intervened in the S&T policy domain
mainly regarding innovation and economic
development policies, even if in some federal
countries like Germany or Belgium regions have
also responsibilities on public higher education
institutions. A step further in the process of
involvement of the regional authorities in RTD
policies has been reported in the literature:
some German Länders, like Bavaria or BadenWurtenberg, started interventions with or without
the Federal government involvement in issues
of their regional interest such as the creation or
promotion of regional research capabilities, for
instance the bio regions (Doshe, 2000; Kaiser,
2003; Kaiser and Prange 2004a), or intervention
instruments such the Bavarian Research
Foundation (Bayerische Forschungsstiftung).
More recently Scottish authorities are entering
into regional science strategies (Lyall and Tait,
2004), anticipating a trend of intervention of subnational governments on science policy matters
(Cooke, 2004b).
dense industrial and business structure could be
seen as a pre-requisite for the development of a
business-oriented R&D strategy.
In the last years, European regions have become
increasingly involved in activities of regional
development, with more emphasis in innovation
policy approaches. However, what is less explored
is the ‘policy-mix’ that dominates the regional
interventions in this policy domain. The region
and the regional authorities are becoming more
and more arenas and actors of science, technology
and innovation policies and as European regional
governments become more involved in S&T and
innovation a better understanding of the forces and
dynamics that explain regional governments’ choices
is needed.
The material basis could explain the initial orientation
of the preferences of those regions’ ruling parties
in the mid-1980s. However, while structural factors
can help to understand initial preferences, other
elements of political factors are required to explain
the continuity and change, the attempts to transform
and the evolution of policies.
The existing material conditions of the regional
R&D environments has been traditionally used
as a key factor of policy adoption of one type or
another. Socioeconomic conditions, their relative
level of development and, above all, the weight of
the different R&D actors in the region are essential
factors when it comes to explaining why some
regional policies have been oriented to scientific
knowledge while others are more oriented to
technological development. The structure of
resources has traditionally been regarded rather
determinant, so that one might view the dominance
of public sector researchers as a prerequisite for
regional governments to adopt academicallyoriented policies. Furthermore, the existence of a
One initial hypothesis could be that governments
have preferences as to which policies they
implement, and that the reason for the choice of
specific policies lays in their political preferences
(Druckman and Lupia, 2000). However, one should
not take such preferences for granted or derived from
partisan ideologies, because it is important to know
where they originate, how they are transformed
and how they are related to the evolution of policy
paradigms (Heclo, 1974; Hall, 1993) or actors’ ideas
(Hall, 1989; Hass, 1992). An alternative hypothesis
would be that the actors with interests in such
policies mobilise to develop alternative models
and to put pressure on governments’ choices (Moe,
1980; Walker, 1991). Of course, the organisation
of the policy domain, the science, technology and
innovation policy administration model, and the
institutional arrangements all matters, and are
important aspects for characterising politics and
political dynamics around policies.
Generally speaking, there are two sets of explanatory
factors or independent variables: on the one hand the
regional government’s policy preferences and ideas,
and on the other hand the interests surrounding this
policy domain and the design of institutions.
An important factor traditionally used to explain
the policies adopted by governments are the
political and policy preferences (Brooks, 1999).
Some literature has associated preference-forming
with the ruling parties’ ideological orientation
(Hibbs, 1977; Boix, 1998). If we apply the model to
S&T policies, one would expect left-wing parties
to orient policies towards the public sector, while
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W o r k i n g P a p e r 10
Regional Governments
We will not enter into the discussion about the
connection of the two ideal policy approaches
(academic versus innovation oriented) with the
linear and systemic models of innovation. However,
it is just fair to mention that some have argued
that the best policies for fostering economic
growth and competitiveness are more closely tied
to the ‘business approach’ (Soete and Arundel,
1993). In general, governments have recently been
placing more emphasis on innovation (EC, 1993;
EC, 1995) and specific objectives that lead them
to implement more business-oriented models,
and this is especially true when the R&D policies
have been tied to regional development policies
(Landabaso, 1995). However, some sectors have
also questioned whether the businessoriented
model should be applied to public S&T policies,
stressing the economic value of basic research
(Pavitt, 1991; Pavitt, 2000; Salter and Martin, 2001)
and calling for a greater balance, within innovation
policies, for the public funding of this type of
research (OECD, 2004).
The institutionalist approach to policy (March and
Olsen, 1984; Steinmo, Thelen and Longstreth, 1992)
regards the institutions as the rules of the game and
the incentive structure that actors have to confront
(HALL, 1986). The variables underlying both the
policy choices and the extent to which it varies from
one region to another may be summarised as: ideas,
interests and institutions.
The Future of Key Research Actors in the European Research Area
the conservative parties would favour business
(Dickson, 1984/1988).
In S&T policies, as in other public policies, the way in
which problems facing the government are identified
and defined (Schön and Rein, 1994) is relevant to
understand choices, and usually has an associated
causal sequence of solutions (Weir, 1992). In our
cases there were countless problems associated to
R&D, yet the result was heavily influenced by the
way in which the governments coded them, selected
them as priorities or placed them on the agenda
(Kingdon, 1984/1995).
224
Imitation and policy transfer are processes of policy
learning (Hall, 1993). We have mentioned that the
influence of the EU level as an explanatory factor was
not very relevant for the Spanish regions selected.
Spain only joined the EU in 1986 but the S&T policy
initiatives taken by the regional authorities started
before the authorities had the opportunity to
access Structural Funds, and much earlier than the
development of the specific EU initiatives, in the mid1990s, like RIS (Regional Innovation Strategies) and
RITTS (Regional Innovation and Technology Transfer
Strategies). In fact stronger forms of policy transfer
are more likely to occur in highly institutionalised
governance regimes (Bulmer and Padgett, 2004) and
this might not be the case yet for S&T policy.
The dependence of the R&D system’s actors on
public funds, together with the limited alternative
sources of finance, may partly explain the different
degrees of mobilisation of the actors who directly
benefit from the policies.
when describing policy learning one important fact
is who brings the ideas or models and who learns
(Heclo, 1974). Weak bureaucracies – such as the
regional governments’ bureaucracies in these fields –
are normally regarded as being prone to greater
external influences, both from the individuals who
take up positions of responsibility and mobilised
interests (Sabatier, 1988; 1998). The emergence of
new actors transforms the policy domain structures
(Baumgartner and Jones, 1993).
5. Scenarios for regional
governments’
functions in knowledge
production and
research systems
This chapter presents the three scenarios commonly
agreed by the expert group. First of all, it should
be pointed out that given the nature of regional
governments as actors in the knowledge and
innovation systems, scenarios will not result from
the application of normative principles but rather will
be the result of negotiation. Regional governments,
as actors, are probably the ones who depend more
on other actors’ dynamics.
5.1 Business as usual
According to the institutionalist literature, the
way in which a policy domain is organised affects
the dominant orientation, because it facilitates or
hampers the influence and expression of the system’s
forces (Sckocpol and Finegold, 1982). Nearly all
the regional governments have interdepartmental
bodies to coordinate the work of the departments
responsible for S&T policies, yet the fact is that there
is a considerable degree of institutional separation,
and even isolation of the science and technology
areas of these policies, which in most cases have had
different bureaucracies and clienteles, and whose
global characterisation depends on one department
having a bigger say in the R&D policy. The degree of
institutional separation or integration of the two main
areas of the regional S&T technology policies is not
directly related with one policy approach or another.
The first scenario that can be envisaged is one of
marginal or incremental change in the present
dynamics we have been analysing.
Imitation of what is done at other policy levels could
be taken as a part of the ‘rational’ policy making, but
Due to non-symmetrical intergovernmental relations,
the main arena would continue to be defined at the
Probably one of the most defining features of this
scenario would be the maintenance of diversity
among the regional governments in Europe as
regards their constitutional powers, their political
and policy capabilities and powers and resources
vis a vis their national government. In this case,
internal dynamics would determine the power of
regional governments to continue to play a very
diverse role in knowledge production and diffusion
policies and processes. The relative weight of
central government transfers in regional financing
would continue to be high in some countries while
small in others.
Strong and more favoured regions would continue
to establish inter-regional cross-border informal
coalitions but it is doubtful whether or not they
might start to pressure for innovation policies to
match their needs and strengths. On the contrary,
many other regions in Europe will continue to have
a passive role in what would be kept as top-down
policies. The endogenous dynamics of European
regions would continue to play a significant role in
economic development and innovation. Therefore,
significant differences in innovative capacities
would still remain in Europe and there is little
evidence of any substantive narrowing of gaps in
recent years.
5.2 Radical transformation
In this second scenario, we would find that strong
decentralisation and regionalisation processes
spread all over Europe and that a third layer of
governance consolidates in the EU. The relative
weight of central government transfers in regional
financing would be very high.
Regional governments would increase their
functions and competences in knowledge production
and research systems with respect to the national
government and EU level. The regional governments
would become key players in European R&D policy
and its orientation towards ERA and not only in the
regional development policies.
Knowledge and innovation policy would witness
an increasing heterogeneity of regional interests
and strategies, but at the same time RTD policies
would become more Europeanised, at least
as regards funding, which would probably be
channelled directly to regions. Correspondingly,
the role of national governments in funding
these policies would decrease. This increase in
resources and capabilities would allow regional
governments to strengthen the links with the rest
of the actors in their regional innovation system
(universities, firms, research and technological
centres, and civil society).
In this scenario, the European polity might
suffer from the absence of coordination and the
dismantling of the already existing soft crossnational coordination in the field. As a consequence
of the national governments seeing their position
weakened, an outcome could also be an increasing
degree of competition, and even the construction of
interregional strategic coalitions among regions that
share the same interests in competition with other
groups of regions to advocate their position at the
EU policy arena.
However, this scenario is unlikely in the absence of
an EU Constitutional reform regarding the current
role of regions in the decision-making structures
of European institutions. This reform would have
to include a clear and stronger institutional role of
regional governments.
5.3 Reduction in the role of regional
governments
In this third scenario, concentration and integration
would be the major dynamics. Regional governments
as a political layer would not disappear, especially
in countries with federal arrangements, but regional
governments would radically reduce their functions
related to knowledge production and research
systems, because Member States define R&D and
innovation as core EU common policies.
This scenario assumes that the European political
system would develop a strong transnational
governance structure based on pan-European
institutions. The European Commission would
be highly strengthened as a government body,
probably having its budget for knowledge and
innovation policies enlarged. The political
autonomy of national R&D policies could decrease
along with the regional one.
Actors in the system would stop considering the
regional environment as relevant both in terms of
funding and markets. Large supranational European
institutions in support of knowledge production and
R&D would be constructed, to compete with the US
and Japanese institutions in the field. The outcome
would be that sub-national levels of government
become marginalised.
Regulatory and investment decisions would be
negotiated and taken at transnational arenas
and it is likely that they are in the hands of
supranational organisations, such as the European
Science Foundation or the European Research
Council, which would be very much strengthened
225
W o r k i n g P a p e r 10
Regional Governments
national level, under European soft coordination
(for instance the Open Methods of Coordination
(OMC)). Some regional governments, those with
more constitutional capabilities, leadership and
coalition building resources would continue to play
a significant role in European policy-making. This
role would probably be marginal in R&D policies, as
has often been the case up to now, but relevant in
regional policies (especially those concerned with
development policies for regions).
The Future of Key Research Actors in the European Research Area
in comparison with the present. It might also be
the case that research centres with industrial
orientation might merge across countries.
Investments in R&D excellence would concentrate
exclusively on ‘large projects’ in order to achieve
competitiveness, that in principle would promote a
‘picking the winners’ type of politics in the belief
that large-scale innovation and research projects
are beyond the scale of capacities of any regional
government and even any national one.
The relative weight of central government transfers
in regional financing would decrease. The vision
that knowledge production, transfer or exchange
structures with competitive advantage cannot be
created by regional political action would succeed.
226
6. Impact analysis of
scenarios on ERA
and the European
Knowledge Society:
The policy goals
perspective
This final chapter looks back at the scenarios from a
policy goals perspective and gives a first evaluation
or assessment of the impact of each of the three.
Attention will be paid to the effects of the different
scenarios on the following dynamics, among others,
such as their impact on cohesion, fragmentation,
cooperation or competition.
• Contributing to competitiveness.
• Increase of investments in R&D.
• Increasing impact of investments in R&D.
• Contributions to speeding up solutions of social
problems.
6.1 Business as usual
Probably the most likely outcome of this first
scenario would be that disparities among regions
would be maintained. Without transformations,
the path-dependent trajectories of regions, and the
cumulative feedback processes would consolidate
and would only be condition by the dynamics and
changes of intergovernmental relations within each
country.
Strong regions would remain strong in EU regional
development policies, and those regions which enjoy
a high degree of political autonomy might even align
their interests with maybe smaller nations with high
investments in science, innovation and education.
However, R&D expenditure would continue to
depend on the strategies of national governments
in unitary and decentralised countries, and on the
negotiated strategies of regional (or federal) and
central governments in decentralised ones. The
resulting trend would probably be one of cumulative,
slow increase in R&D expenditure. Likewise,
solutions to social problems would probably only
speed up provided that this corresponds to the
political will of strong actors in European arenas.
Regions would not have any formal powers in the
design of knowledge and innovation policies at the
EU level, which would allow for a relatively clear
EU perspective to be kept. But sometimes it has
been pointed out that EU policies might become
too inflexible or centralised to take into account
regional diversity, more so in the context of the
EU 25, with the corresponding negative effects
for competitiveness. Within this scenario and in
relation to competitiveness, a careful balance would
have to be made between the appropriateness of
classical Structural Funds approaches (targeted to
the necessary conditions), and more ‘fashionable’
innovation approaches (focused in investment on
intangibles).
6.2 Radical transformation
What could be the impact of this second scenario
in the European institution in charge of knowledge
and innovation policies? The answer is not clearcut. On the one hand, the competition of too many
contradictory regional interests might weaken
European knowledge and innovation institutions
and their related DGs, and this could impact on the
Framework Programmes, that might suffer from a lack
of a clear focus, coherence, and over-fragmentation.
In short, a strong bottom-up approach in the
design of policies would risk losing the European
perspective on knowledge policies. However, there
is no determinism underlying this dynamic, because
on the other hand, European institutions might be
reformed in order to anticipate and avoid these
potential drawbacks, the risk of clashes between
the existing arrangements for the EU and this new
role for regions.
Despite that probably this scenario would
encompass an increase in the overall European
R&D expenditure, and an increase in the local and
social impact of investments in R&D, it seems clear
that without the appropriate balancing mechanisms
and institutional reforms, this second scenario
poses a risk of fragmentation, with negative
consequences for European competitiveness and
unclear consequences for the aggregate impact of
R&D investments.
The answer to the question of whether stronger
regions lead to more cohesion depends on
whether or not more favoured and richer regions
take the place of more favoured nations and
replicate the dynamics of the maintenance of
disparities that we have seen in the past. In such
a case, this scenario would be a transitional one
finally leading to a business as usual scenario but
with different actors.
6.3 Reduction in the role of regional
government
The difficult question is whether or not a Europe
with weaker regional governments would be
well equipped to face the challenges of global
competitiveness. It is our belief that it would not.
The impact of this scenario on global investment
in R&D in Europe is not clear, but surely
investments are unlikely to increase in the case of
a significant reduction of the number of relevant
actors involved. In addition, the evolution of
this expenditure would be too dependent on the
dynamics of large corporations and of networks of
powerful research centres. As regards the impact
of R&D investments in this scenario, the question
is not so much whether this impact will increase or
decrease but how the benefits will bedistributed
and what will be the cumulative consequences in
the long-term.
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W o r k i n g P a p e r 10
Regional Governments
Probably one of the most visible outcomes of this
third scenario would be the definition of knowledge
and innovation policies as common EU policies. It
is thus likely that, within a process of integration
and concentration, regional internal disparities
become less visible and thus face the risk of going
out of the political agenda while the concerns about
competitors external to the EU take become higher
in this agenda. Underlying this scenario is somehow
the assumption that classical redistributive regional
policies are not fully compatible with the goal of
European competitiveness. It is very difficult to see
how this scenario would speed up the solution of
social problems.
The Future of Key Research Actors in the European Research Area
7. Bibliography
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