Journal of Competitiveness

Transcription

Journal of
Competitiveness
January 2011, Volume 1, Issue 1
A Comparative Analysis of the Competitiveness of the
Readymade Garment Industry Clusters in Delhi, Dhaka and
Colombo
Choe, KyeongAe; Nazem, Nurul Islam; Roberts, Brian H.; Samarappuli, Nihal;
Singh, Rajveer
Determinants of Competitiveness: A Study of the Indian
Auto-component Industry
Joshi, Deepikaa; Rathore, Ajay Pal Singh; Sharma, Dipti
Multidimensional Networks: The Changing Character and
Framework of Inter-firm Collaboration
Ploder, Michael; Steiner, Michael
When Policy Goes Cluster: Reflecting the European way(s)
Rehfeld, Dieter
From Industrial Clusters to Global Knowledge Hubs
Reve, Torger
Also featuring
Articles from the IFC India City Competitiveness Report 2010
Papers and ideas presented at the
13th TCI Global Competitiveness Conference 2010
Editorial Board
Advisory Board, Institute
for Competitiveness
Arturo, Condo
Professor of Competitiveness and
Strategy
INCAE, Costa Rica
Lall, Ashish
Associate Professor
Lee Kuan Yew School of Public Policy,
Singapore
Dharwadkar, Ravi
Professor of Management
Martin J. Whitman School of Management, USA
Mishra, Abhishek
Professor of Business Policy and
Strategy
Indian Institute of ManagementAhmedabad, India
Doyle, Eleanor
Senior Lecturer in Economics
University College Cork, Ireland
Duffill, David
Deputy Dean
Robert Kennedy College, Switzerland
Prasad, Ajit
Professor of Strategy
International Management Institute,
India
Balaji, G.
Senior Director, Fidelity Business
Services India
Batra, Anurag
MD and Editor-in-Chief, Exchange4Media Group
Doyle, Christopher
MD, Dynamic Results India
Former Country Manager, India,
Economist Intelligence Unit
Ffowcs-Williams, Ifor
CEO, Cluster Navigators
Rolfe, Robert
Professor of International Business
Moore School of Business, USA
Jakhu, Ram S.
Associate Professor, Institute of Air
and Space Law, McGill University
Hergnyan, Manuk
Professor, Strategic Management
Yerevan State University, Armenia
Steinbock, Dan
Research Director of International
Research
India, China & America Institute,
USA
Kapoor, Amit
Honorary Chairman, Institute for
Competitiveness
Professor of Strategy and Industrial
Economics, MDI
Kapoor, Amit
Professor of Strategy and Industrial
Economics
Management Development Institute,
India
Unger, Michael
Associate professor of management
and international business
Sellinger School of Business and
Management
Ketels, Christian
Principal Associate, Institute for Strategy and Competitiveness, Harvard
Business School
Elazar, Berkovitch
Dean
Arison School of Business, Israel
Kini, Ramesh
Professor of Automation and Computer Science Department
Kazakh British Technical University,
Kazakhstan
Muneer, M.
Leading management consultant and
author
Verma, Sanjay
Executive Managing Director, South
Asia, Cushman & Wakefield
enhancing
prosperity
January 2011
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January 2011
Editor’s note
Dear Readers,
Competitiveness is a very important word, especially for countries like India that are transforming
rapidly and have the immense opportunity to prioritize productivity and inclusiveness in their growth
strategy.
But the truth is that it’s not a very well-known word. Outside of the lecture halls and academic journals
and perhaps select boardrooms, it’s an alien term for—not just the ‘lay’ person—but even entrepreneurs,
policy makers and senior executives.
The Journal of Competitiveness brought out by the Institute for Competitiveness is an attempt to address various aspects of the subject, from both academic and non-academic perspectives.
This issue gives you the best of the 13th TCI Global Competitiveness Conference 2010, presenting
five papers in their entirety. The papers, from researchers and cluster experts across the world, focus on
the scenario in South Asia and the priorities for India’s clusters—particularly in the readymade garment
and automobile industry. Additionally, the papers look at developing knowledge hubs, the framework of
inter-firm collaboration, and lessons for shaping policies for clusters. Excerpts from the papers and ideas
presented at the 13th TCI Global Competitiveness Conference 2010 are also included.
The journal also includes articles from the India City Competitiveness Report 2010, which is being
released by the Institute for Competitiveness during this conference. These articles look at various aspects
of how cities in India could improve their competitiveness in areas like governance, transportation, branding and attracting investment.
It is our sincere hope that the ideas presented in the Journal of Competitiveness reach a wide and
relevant audience of decision makers in corporations, as well as policy makers.
To submit your papers for double-blind review, email [email protected].
January 2011
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January 2011
A Comparative Analysis of the Competitiveness of the
Readymade Garment Industry Clusters in Delhi, Dhaka
and Colombo1
Choe, KyeongAe2
Nazem, Nurul Islam3
Roberts, Brian H.4
Samarappuli, Nihal5
Singh, Rajveer6
ABSTRACT
The Asian Development Bank has recently completed a project on City Cluster Economic Development (CCED) in South Asia, which examined
the competitiveness of cities and industry clusters
in Bangladesh, India and Sri Lanka. Part of the
research involved an analysis of readymade garment industry clusters in Delhi, Dhaka and Colombo. This paper describes new methodology
techniques for analyzing the competitiveness of
clusters, using a modification of the Porter Diamond Model. The study measures 39 attributes
of competitiveness affecting the performance and
development of three RMG industry clusters. The
paper, which is a part of the CCED research project, has involved one of the most in-depth analyses
conducted in the competitiveness industry clusters
in South Asia. The analytical methodology proved
to be useful for strategizing identified strategic
opportunities for interventions by the government
and cluster stakeholders to enhance the competitiveness of the readymade garment industries in
the three countries.
Keywords: Readymade garment industry, Competitiveness, Industry clusters, Bangladesh, India, Sri
Lanka
1 The views expressed in this paper are those of the authors and do not reflect a position or are binding on the ADB and AusAID that
supported the CCED project in South Asia
2 Urban Development Division, South Asia Department Asian Development Bank, Manila
3 Centre for Urban Studies, Dhaka, Bangladesh
4 University of Canberra, Australia
5 Board of Investment of Sri Lanka, Colombo
6 Apex Clusters, Delhi, India
January 2011
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INTRODUCTION
The readymade garment (RMG) industry is one of
the world’s largest industries. Global production of
garments in 2009 exceeded 17 million tons, with
exports worth more than US$ 300 billion. The
RMG industry is labor-intensive and a very large
generator of employment globally. Most of the labor force is women, who work in large factories
or micro enterprises for very low wages. Asian
countries dominate the production of textiles and
RMGs. The industry is a major source of export
income for countries like Bangladesh, China, India,
Indonesia and Sri Lanka. It is a highly competitive
industry, driven by keeping labor, transportation,
materials and utility costs low. Industry margins at
the factory floor production level are low; so that
firms engaged in manufacturing and retail of clothing and apparel products are constantly seeking
ways to keep costs down to maintain a competitive
business edge.
The high dependence countries like Bangladesh
and Sri Lanka have on textile and RMG exports
makes them especially vulnerable to changes in exchange rates, raw material costs, technology improvements and buyer markets. The recent global
financial crisis has had a significant impact on the
RMG industry, causing cut backs in production and
the loss of a large number of jobs in many countries. There is growing concern by western consumers also about the environmental impacts and
labor conditions in footwear, clothing and textile
factories in developing countries. These factors are
putting pressure on manufacturers of garments and
textiles to change the way RMG products are produced to tailor for the changing demands of export
markets in the future.
The growing pressure on firms and small businesses in the RMG industry to enhance their Competitiveness to maintain market share is leading
many countries to explore ways that governments
and business can work more closely together to reduce transaction costs. Business, in particular, is
looking constantly for ways to reduce transactions
costs. Most do this by focusing on achieving greater
efficiencies within internal production and distribution systems—especially along internal supply
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chains. However, firms are less able to reduce external transaction costs of commonly-shared facilities and services, such as water and transport
facilities.
For more than two decades governments and
business have been focused on ways to improve
competitive advantage in cities and regions. Much
of Michael Porter’s work since the Competitiveness of Nations (Porter, 1990) was published has
focused on ways to enhance the competitiveness
of business in cities and regions (Porter, 2000).
This has led to a growing interest by governments
and business on ways to foster the development of
industry clusters, which are seen as a way to enhance the Competitiveness of local economies and
increase production. Clusters developed by rival
firms and suppliers collocating and collaborating
on ways to reduce external transaction costs, innovate and develop new business opportunities and
markets that support the development of new business and investment in local economies and the
growth of exports.
The initial focus on the development of clusters
sought to examine ways firms can pursue and create competitive advantage. However, over time,
there has been a significant shift from the initial
focus on competitive advantage (which focused on
improving organizational efficiencies) to collaborative advantage (Tapscott and Williams, 2006). This
development of industry clusters as a way to enhance the competitiveness of local economies lead
to an interest and new ideas on how to use clustering as a means of reducing external transaction
costs to business and government. The new focus on
clusters involves rival firms and suppliers and governments cooperating and collaborating on ways
to reduce external rather than internal transaction
costs, innovate, and develop new business opportunities and markets.
The Asian Development Bank has recently completed a project on City Cluster Economic Development (CCED) in South Asia (Roberts and Choe,
(forthcoming 2010)). CCED involves a seven step
process that is used to evaluate the competitiveness
of cities and industry clusters, and to develop plans
for investment in projects and programs to develop
January 2011
a plan to build-up strategic architecture (Hamel
and Prahalad, 1994, Roberts and Stimson, 1998),
which is used to support the development and more
efficient operation of local economies. Part of the
CCED research project involved an analysis of the
RMG industry clusters in Delhi, Dhaka and Colombo. Strategic architecture includes endowed
resources, human capital, business dynamics and
enabling environments. The competitiveness of
these things is important to the development of local economies and clusters.
An important element of strategic architecture
is the creation of catalysts. These take different
forms including networks, civic entrepreneurs, facilities and incentives. Catalysts are responsible for
driving business effort, innovation and investment
attraction in local economies and clusters. Once
projects and programs needed to develop strategic
architecture to support clusters have been identified, there is need to establish a cluster development pathway and mechanisms to build critical
elements of strategic architecture. This includes
the financial mechanisms and organizational governance arrangements to deliver on these.
The paper commences with a brief description
of the methodology used for cluster analysis developed by the CCED project, and provides some
insights on the policy implications this has had on
the development of clusters. A comparative analysis of 13 key Competitiveness indicators derived
from a measure of the 39 competitiveness attributes in the RMG industry clusters in Colombo,
Delhi and Dhaka is presented. The results show
significant differences between the competitive attributes for each cluster. An explanation is given
for some of these differences. The findings have
enabled the identification of strategic opportunities for interventions by government and cluster
stakeholders to improve the competitiveness and
performance of the readymade garment industries
in each country. The research has involved one
of the most in-depth analyses ever undertaken to
compare the competitiveness of three RMG industry clusters in South Asia. Some of the insights
gained from the comparison study are presented
in the conclusion to the paper.
January 2011
METHODOLOGY USED TO EVALUATE THE COMPETITIVENESS
OF RGM CLUSTERS
Many techniques have been developed to study and
analyze the structure of clusters. Marshall (1929,
1920) and Weber (1929) studied spatial agglomeration of economic activities in national economies during the early 20th century. One of the earliest studies on clusters was of the New York hotel
industry in the 1890s, which demonstrated the
benefits and spin-offs of competitive businesses
co-locating (Baum and Haveman, 1997, Weber,
1929). Co-location of hotels led to the local development of smaller service businesses, restaurants,
bars and shops that serviced hotel customers. The
synergy created by the mix of land-use activities
enhanced competition between suppliers, and expanded the range and choice of accommodation
services.
Porter Model of Cluster Analysis
Michael Porter (1980) began to explore techniques
to map and analyze industrial structures and competitors, and using the information derived from
his research on strategies firms use to achieve
a competitive advantage. This research revealed
four forces driving industrial competitiveness—
potential entrants, buyers, suppliers and industry
competitors. This resulted in the concept of internal and external environmental analysis. In Porter’s model, environment dealt exclusively with
the economic and business environment given his
realization that the study of firms and industries
was insufficient to explain competitive advantage.
This led to further research on the competitiveness
of global industries (Porter 1985) and of nations
(Porter 1990).
Porter’s Competitive Advantage of Nations
(1990) introduces his diamond model of competitiveness. The model has the following four broad
drivers that shape the environment in which firms
and regions compete for business:
n factor conditions, which include the skills, resources, technology, and infrastructure necessary to
create competition in a given industry or cluster;
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n demand conditions, which include the nature of
local and overseas demand for industry products
and services;
n related and supporting industries, where the
presence or absence of suppliers and distributors
in support of industry sectors or clusters will determine competitiveness;
n firm strategy, structure, and rivalry, which relate to conditions in a nation governing how companies are created, organized, and managed and
the nature of domestic rivalry.
Porter identified two other important factors
that affect competitive advantage of firms: chance
and the role of government. Chance relates to
events or occurrences that have little to do with
a country’s circumstances, but can be influenced
by individuals, such as the decision by Bill gates
to locate Microsoft’s in Seattle. Governments can
have significant role in aiding competitive advantage, especially through public policies which are
favorable to investment and profit performance.
Porter identifies the importance of clustering competitive industries to create rivalry and stimulate
innovation.
Porter (1990) has had an important influence
on strategic thinking for business and economic
development. While his early work was extensively concerned with the competitiveness of nations,
many of the case studies provide an insight into the
competitiveness of regions. Other researchers have
used Porter’s model to analyze the competitive
advantage of regions for manufacturing (O’malley
and Egeraa, 2000), trade services (Daly and Roberts, 1998), film (Assmo, 2005), food (Neven and
Dröge, 2001), and education (Curran, 2001). Still
other researchers have developed new qualitative
and quantitative methods for exploring and evaluating the competitiveness of clusters in cities and
regions (Enright et al, 1996, Brown, 1996). Indeed, the study of industry clusters has become a
discipline in itself.
Cluster Structure and Supply Chain Mapping
Cluster mapping, seeks to translate statistical data
and information gained from the above types of
analysis into a map the structure and supply chains
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of a cluster. These cluster maps can be very complex. The intent of cluster mapping is to identify
significant spatial concentrations of employment
and business activities, financial and related transactions that occur between businesses and support
industries in the same locality. The process begins
by assessing the spatial concentration of industries
by SIC category input-output (I/O) analysis. A good
example of this technique was used by Feser and
Bergman’s (2000) to study clusters in the North
Carolina economy. Cluster mapping also uses location quotient (LQ) analysis to identify the level of
concentration or intensity of business activities in
a location. I/O tables help define the transaction
relationships between different types of industries
in a cluster supply chain.
Certain types of firms make up the core of a
cluster. Core industries might include several food
processing factories which form the core of a food
cluster or a steel mill for a metals cluster. LQs for
these industries are likely to be high. Other firms locate close to and service the cluster’s core firms. In
Porter’s (1990) model, these are the suppliers or related supporting industries. Where LQs for non-core
industries are relatively high, greater than 5, this
could indicate a relatively mature and large cluster.
Cluster maps also provide useful spatial planning information about the scale and the magnitude of agglomeration occurring in a cluster.
Spatial plans can be designed to encourage the
co-location of supporting industries and improve
logistics facilities needed to transport goods and
services and other products to and from the cluster,
or within a metropolitan region where a cluster is
poly-centered; that is, not confined to one area of
the city. The mapping provides important information for more detailed analysis of how the cluster
functions, and the competitiveness of the different
factors that support its operation and development.
Once analysts have mapped a cluster, the next step
is to analyze the competitiveness of pertinent cluster elements.
Cluster Attribute Competitive Analysis
Porter’s (1990) Diamond Model is one of the most
widely used techniques for cluster analysis. It inJournal of Competitiveness
January 2011
volves analysts working with industry focus groups
to score the relative strengths of the attributes
of competitiveness within a cluster. The Diamond
Model has its weaknesses in that it does not provide
a spatial dimension to cluster analysis, but it has
provided a useful framework for strategic thinking
about local economic development and has been
widely applied in many countries to analyze clusters. The model can be used to identify and analyze
the interaction of factors that underlie local competitiveness and to formulate strategy for regional
economic and industry cluster development based
on identified elements of competitive advantage.
The CCED methodology used to conduct the
cluster analysis of the RMG industry in Colombo,
Delhi and Dhaka, seeks to measure 39 attributes
of competitiveness that are grouped under the five
driving factors in the Porter model: factor conditions; demand conditions; related and supporting
industries; firm strategy, structure, and rivalry;
and the role of government. The chance factor is
removed as it is not easy to measure as a factor of
competitiveness. Table 1 shows 13 primary attributes of cluster competitiveness related to the five
driver factors measured as part of the research.
These are an aggregation of the 39 indicators undertaken for simplicity of presentation in the paper. The 39 attributes of competitiveness are associated with six elements of strategic architecture
explained earlier that support the development of
regional economies and clusters. Using an ordinal
ranking semi-qualitative scoring method based on
numeral scale of 0–5 (see Table 1) it is possible
to measure the relative competitiveness of each attribute. The scoring of attributes is done using a
modified Delhi technique (Bordecki, 1984) where
an industry focus group comprising 10-15 business
leaders and other knowledgeable experts (all together known as a cluster working group) score the
current and estimated future level of competitiveness needed for each of the 39 attributes to make a
cluster competitive.
The scores recorded for each attribute by the
industry cluster focus group assessors are summed
and averaged. Following discussion by the group
members, scores may be adjusted until a final
January 2011
agreed score for the Competitiveness attribute is
agreed upon. The scores for all the attributes are
averaged to arrive at an overall Competitiveness
score for the cluster. An average attribute competitiveness score greater than 3.75 suggests combined
attributes supporting the cluster are very strong,
well-developed and internationally competitive; a
score around 3.00 suggests a relatively strong, nationally competitive cluster; while a score between
2.5 indicates a small, emerging, sub-national
strength cluster. A score of 2 or less suggests that
the cluster is relatively weak and only competing
for business in local markets or is a newly emerging cluster.
Cluster Competitiveness Deficiency (Gap)
Analysis
The second part of the competitiveness analysis is
to assess competitiveness gaps of attributes; that
is, the difference between the current and future
level of competitiveness attributes necessary to
develop the elements of strategic architecture supporting the development of the cluster competitive.
Where there are significant differences or gaps, for
Table 1: Attributes Of Competitiveness Related To
Five Factors In The Porter Diamond Model
Competitiveness Elements
Of Cluster
Indicators
Competitiveness
Score 0-5
Factor Conditions
Labor
4
3.1
Infrastructure
4
3.75
Resources
3
2
Social Environment
2
2.75
Demand Conditions
Markets
2
3.2
New Products
2
3.8
Business Environment
4
2.3
Firm Strategy Structure
And
Rivalry
Structure
2
4
Collaboration
5
4.1
Technology Orientation
1
4
Related Supporting
Industries
Supply Chains
3
3.5
Value Adding
2
3.8
Government
Enabling Environment
5
3.9
Source: Roberts And Choe, (Forthcoming 2010)
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example a factor of 2, this suggests there may be
need for strong intervention by government and industry stakeholders to lift the level of the selected
attributes of competitiveness to raise the overall
competitiveness and economic performance of the
cluster.
Table 2 shows an example of how two primary
competitive attributes of the cluster might be assessed. For example, a growing cluster seeking
to expand into national or international markets
might score 2.75 on overall current competitiveness, but it would need to lift its overall index score
to 3.00 to succeed nationally and 3.75 internationally. The cluster’s competitiveness index would need
to improve by 0.25, or 9%, to become a successful
national cluster, and 1 or 36% to be internationally
competitive. Actions to strengthen weak competitiveness attributes would need to be identified. Possible actions for enhancing the competitiveness of
marketing and new products attributes are shown
in the final column of the table. The analysis may
also include references to other sources of information that may be relevant to the analysis.
The competitiveness deficiency-gap analysis
provides a qualitative measure of the strengths and
weaknesses of attributes of strategic architecture,
as well as potential threats and opportunities facing the development of a cluster. The value of the
analysis is that it enables a cluster working group
responsible for preparing a plan to develop a clus-
ter to identify possible projects and programs that
should be considered in a cluster development business plan and action plan.
Analysis Of Rmg Industries
In Colombo, Delhi And
Dhaka
Using the above techniques, the CCED investigation teams in each country began a detailed analysis of nine industry clusters in Colombo, Delhi and
Dhaka. The RMG industry was a common cluster
investigated in each country. The following presents a summary of the competitiveness analysis
conducted for the three RMG clusters.
Colombo RMG Clusters
RMG and textiles is Sri Lanka’s largest export sector
generating US$3.2 billion in exports in 2009, equivalent to 46% of the country’s total export earnings.
Most RMG are exported to Europe and the United
States. The Colombo Metropolitan Region (CMR) is
the centre of the RMG industry in Sri Lanka and is a
world-class RMG manufacturing cluster. The cluster
provides direct employment for more than 300,000
people (33% of manufacturing sector employment)
and indirect employment for a 1 million people. Direct foreign investment in the RMG industry at the
end of 2007 exceeded US$ 700 million, of which the
CMR accounted for US$ 280 million.
Table 2 Sample of Competitive Attributes of Clusters Using Porter’s Diamond Model
Current Status
Future Competitiveness
Requirements
Gap
Actions
2.75
3.75
-1
Sufficient Market Intelligence
2
4
-2
Collaborative Marketing
Demand Expansion Capacity For
New Products
2
4
-2
New Technologies
Responsiveness To Change And
Innovativeness
2
3
-1
Change Anagement
Demand Conditions
Markets
Expanding Domestic And Local
Markets
Expanding Export Markets
New Products
Source: Roberts And Choe, (Forthcoming 2010)
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January 2011
Current Conditions
The RMG cluster in the CMR has a significant
presence of manufacturing units engaged in core
industries. The core of the cluster has more than
500 apparel manufacturers. The cluster is backed
by a proactive industry association, the Joint Apparel Association Forum, made up of representatives from key stakeholders in the industry. The
CMR also has a good network of transportation infrastructure supported by export and logistics companies. The CMR RMG cluster has well established
forward and horizontal supplier firms producing
textiles and garment accessories such as buttons,
elastic, labels and packaging materials. However,
the highest value-added components, including
equipment suppliers, designers and retailers, are
largely absent. Figure 1 presents the apparel cluster map constructed by the RMG industry focus
group for the CCED project.
Mapping the RMG supply chain was undertaken and provide an important understanding of the
clusters production systems, the value-adding elements associated with this and the linkages to other
supporting industries and services. The textile and
apparel industry’s supply chain shows that the industry cluster has extensive backward linkages that
have a strong multiplier effect on employment and
production. Figure 2 presents the apparel cluster
Fig 1 Apparel Industry Cluster Map, CMR
Industry
A
i ti
Source: (ADB, 2010) January 2011
map constructed by the RMG industry focus group
for the CCED project.
The emerging IT cluster in the CMR has improved the supply chain management and local
financial institutional capacity supporting the cluster. Much of the equipment necessary for producing garments is imported mostly from Germany
and Italy. The demand for this equipment is not
sufficient to encourage manufacturing of machinery under license to replace the need for imports
of machinery. The cluster is supported by a small
number of exporting and logistics companies along
with relatively good supporting infrastructure such
as transportation and utility firms. Universities and
vocational schools with design and production curricula support the cluster, but as foreign retailers
design most products, and more than 85% of output is exported, Sri Lanka has few designers and
retailers. As a result, the cluster has not been able
to gain access to international media, promotion
and advertising, including fashion shows. This has
a significant negative impact on the cluster’s ability to move toward higher value-added activities.
Competitiveness Analysis of the Apparel Cluster in Colombo
Figure 2 shows the analysis of the competitiveness factors in the apparel industry cluster using
the Porter Diamond Model and scaling systems
described above. These factors
were identified by a cluster focus
group for the five driving factors (See Figure 3). The cluster
is positioned in the right market,
including high-end products, but
many of the activities associated
with the cluster are low valueadded activities such as cut-andmake garments. Thus, the cluster
effectively participates in only
10% of the value chain process.
The challenge is to shift into high
value-added activities such as
design, marketing and sales. This
is difficult because of the global
structure of the RMG industry
IT = information technology.
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where these activities tend to be dominated by design houses and global corporation.
Figure 3 shows the assessment of the five drivers of competitiveness in the Colombo RMG cluster. Factor and demand conditions are relatively
strong, as is firm strategy and rivalry and related
supporting industries; however, government support
is weak. The overall competitiveness of the cluster is
2.68, which is below 3.25 considered necessary to
remain competitive in international markets. While
the RMG industry is growing, it appears to be losing market share to its competitors especially from
China and other SE Asian countries.
Delhi RMG Cluster
More than 600,000 people are employed in the
Delhi garment and textile industries. The New Delhi
National Capital Region (NCR) has one of the largest concentrations of RMG industry employment
in India. The NCR produces 40% of India’s readymade garment exports and is the leading RMG
cluster in the country. Most of the garment firms in
the NCR are located in the Okhla Industrial Area,
in the southeast part of New Delhi. The industrial
area is responsible for 40% of RMG manufactured
goods in the NCR. More than 4,000 factories are
located in this industrial area, which is one of the
largest in the country. The other major production
center in NCR is in Gurgaon, in the southwest.
Current Conditions
The RMG cluster is very dependent on export orders for its development. The cluster accounts for
16% of total apparel exports from India. There are
about 50 large export houses situated in Okhla that
are responsible for most of the clusters exports.
With the presence of international brands, exports
go primarily to the European Union countries, Canada and the United States. Exports are mainly focused on clothing and discount chain markets, and
not high-priced garments. The key features of the
cluster include the following: (i) firms face difficulties in accessing supplier services, education and
training facilities, and product improvement services and in building brands; (ii) stakeholders have
low levels of awareness of policy matters, government issues, and export procedures; and (iii) firms
tend to use traditional, outdated practices and have
low social capital and a lack of expertise that could
help units solve production-related problems.
Fig 2 Apparel Industry Cluster Analyses
Highly competent
workforce
Good quality
telecommunication
services
Good Quality of raw
materials
Good workplace conditions
Ĭ High cost of Electricity
Ĭ Poor quality of
infrastructure logistics
Ĭ Poor education/training
facilities
Ĭ Poor quality of living
conditions for workforce
350 + existing firms competing without
Government protection
Presence of reputed international firms
Presence of strong business associations
(JAAF)
Proactive at National / International level
Involvement in CSR activities
Ĭ Low level of knowledge sharing
Ĭ Low level of Technology application in firms
International repute as a
reliable supplier of quality
products
High level of business ethics
(‘Garments without Guilt’)
Emphasis on change
Ĭ Small domestic market
Ĭ Narrow Export base
Ĭ Undue competition due to lack
of preferential market access
Ĭ Slow responsiveness and
innovativeness to change
Ĭ Lack of demand expansion
capacity for new products
Ĭ Lack of readiness to face risks
Ĭ Less emphasis/success on
product branding (brand
management)
Usage of automated design / software
Emerging accessories cluster
Ĭ Lack of business development
services
Ĭ Low response time and low quality of
local support services
Ĭ Firms inability to exploit value
adding potential
R&D = research and development.
Source: ADB, 2010
12
Government – Policy &
Support
Ĭ Lack of long-term plans for apparel
industry development
Ĭ Lack of government support for
industry development (eg. R&D)
Ĭ Lack of enforcement of business
regulations (VAT refunds)
Ĭ Relatively rigid labour regulations
Ĭ Not enough marketing of the
industry
January 2011
Competitiveness Analysis of
the Delhi RMG Cluster
Fig 3: Analysis of the Competitiveness of the RMG Cluster, Colombo
An assessment of the competitiveness of the cluster was undertaken by an industry focus group
using the CCED techniques described earlier. The following
briefly describes the analysis of
the drivers of competitiveness using the Porter model. The results
of the analysis are shown in figure 4. The strengths of the cluster include a trained workforce,
good supporting clusters and
preferential access to the European Union market. Weaknesses
include the low levels of branding
and marketing. Significant entrepreneurial activity is apparent in this small but rapidly growing sector, but moving the whole cluster
in this direction will require higher levels of coordination between education institutions, firms and
the government. The conditions prevailing in this
cluster are poor and their competitiveness scores
range from 1.25 to 3.66. Of the 39 competitiveness
attributes, 72% have an average score of less than
2.5 (scores of 3 are necessary for a driver or attribute to be considered nationally competitive). To
compete at the international level, the conditions in
RMG cluster needs to be improved to at least 3.75
to make the cluster more competitive.
The following describes briefly the analysis of the
drivers of Competitiveness using the Porter model.
Factor Conditions
Production resources for the RMG industry include
raw materials suppliers, machinery tools suppliers,
fabric processors, and packing materials suppliers.
Suppliers in the cluster are close to their markets
and the SMEs in the cluster have easy and costeffective access to a wide range of services. Critical to the growth and development of the cluster
has been the availability of cheap labor due to the
migrant population from Bihar and Uttar Pradesh.
These workers gain entry to the trade by working
in factories with little formal training. The NCR
January 2011
Source: ADB, 2010
has a number of established education and ICT institutions that act as a catalyst for enriching the
cluster’s human capital base. This has had a positive spin-off to the region, but the impact on the
RMG industry has been less than other sectors of
the economy.
The cluster firms have access to railways, roads
and airports, including an international container
at the Okhla industrial area; however, the condition
of infrastructure and reliability of utility services
is poor. Internal public transport facilities are not
available, which makes it difficult for workers to
get to and from places of work. The condition of
water supply, solid waste management and electricity supply is poor, but the latter has improved somewhat, but further improvement is needed to ensure
an uninterrupted 24-hour power supply to firms in
the cluster. This has a disruptive impact on production costs and efficiencies. In many cases, factories
are duplicating public services in order to maintain
production. This represents significant sunk costs
to businesses for the provision of services that are
used when supply of water or electricity is disrupted or not available.
Demand Conditions
The RMG cluster is solely dependent on orders for
manufacturing. The cluster accounts for 16% of to13
large firms and export houses
do recruit technically- and commercially-qualified employees for
production, inventory control and
design work. There is need for a
wide range of support programs
involving education and training.
The key features of the cluster
that emerged from the evaluation included the following: (i)
firms face difficulties in accessing supplier services, education
Source: NIUA, 2010 and training facilities, and product improvement services and in
building brands; (ii) stakeholders have low levels
of awareness of policy matters, government issues
and export procedures; and (iii) firms tend to use
traditional, outdated practices and have low social
capital and a lack of expertise that could help units
solve production-related problems.
The cluster’s strength lies in production flexibility, opportunities to expand the domestic market
and capacity to expand into new products. Low investment, entry barrier requirements, easy and cost
effective access to a wide range of services, abundant availability of raw materials and easy availability of cheap labor need to be harnessed in the
right manner to open up markets at all levels, and
give a fair share of reward to all the stakeholders.
Fig 4: Analysis of the Competitiveness of the RMG Cluster, Okhla,
Delhi
tal apparel exports from India. There are about 50
large export houses situated in Okhla, which are
responsible for most of the clusters exports. With
the presence of international brands, exports go
primarily to the European Union countries, Canada
and the United States. Exports are mainly focused
on clothing and discount chain markets, and not
high-priced garments.
Related and Supporting Industries
Supplementary industries and activities that support the RMG cluster include: merchants; traders;
manufacturers of fabric, thread, buttons, and fittings; processing units; buying houses; exporters;
fabricators; machine embroiderers; and machinery suppliers. The supply chain structure is well
developed, with a very large number of micro enterprises. The industry experiences a problem of
high rejection rates, indicating a quality assurance
problem within the supply chain network. The current situation in the RMG cluster is that few of the
competitiveness attributes are good or excellent.
Firm Strategy and Rivalry
Most garment manufacturing units in the cluster are small and family-owned, with the owner
and other family members taking on the roles of
manager, purchaser, marketer, negotiator, quality controller and finance controller. As a result,
few professionally-qualified people are recruited
to those roles with the exception of a few people
with diplomas holders in merchandising. However,
14
Dhaka RMG Industry
The RMG industry in Dhaka has been the leading export sector industry in Bangladesh for more
than 15 years. In 2007 there were almost 4,500
registered (and many unregistered) garment factories in Bangladesh, employing about 2.4 million
people. More than 1.2 million people are employed
in the industry in Dhaka. More than 60% of factories were located in Dhaka, 8% in Narayanganj
and 17% in Gajipur (BGMEA 2008). The garments industry in Bangladesh is mostly exportoriented. The geographical concentration of factories in these districts gave them advantages in
terms of access to skilled labor, lower transportation and other business transaction costs. This
sector has gained comparative advantage due to
January 2011
the large pool of low cost labor and low transportation costs due to co-location of industrial establishments and some supporting government policies. The government of Bangladesh has identified
this sector as one of the ‘thrust sectors’ of growth
of the economy and has provided significant support to its development.
Current Conditions
The development of the RMG industry in Bangladesh is encouraged and supported by the government since the mid-1980s. The backward linkage supply industries grew rapidly in response to
a demand for material and fabricated products.
Many of this lower order supply chain industries
became scattered around the region because suppliers could not afford rents on properties close to
the main producers and the very low profit margins
in micro or family-run enterprises. As a result, the
supply chain distribution structure became widely
dispersed, and this resulted in inefficiencies and
high local transaction costs in the industry sector.
Many of the factory buildings in the city centre
are multi-storey and not well designed to accommodate expansion or ensure efficient production.
Many of the supporting industries are located close
to the main production houses; however, the intensity of development in these areas has added to the
traffic congestion problem and over taxed many of
the utility services. It is for this reason that many
factories that have undergone expansion have relocated to areas where there is more land for expansion and vertical (same level) integration into
production systems. Despite these disadvantages,
many have well-established family businesses that
have expanded operations elsewhere in the region,
and continue to maintain premises in the inner city,
partly because of the availability of skilled workforce that continues to reside in this area.
Cluster Structure Map
Figure 5 is a map showing the structure of the RMG
industry cluster in DCR. The five core industries that
make up the cluster are textiles, knitwear, woolen
Fig 5: Forward-Backward Linkage Map Showing the Structure of the Dhaka RMG Cluster
Source: (CUS, 2010)
January 2011
15
textiles, jute textiles and handlooms. The backward
and forward linkages supporting the industry cluster are government on policy and strategy matters,
as well as utility services, industry association and
interest groups, education establishments, labor
unions, national market and international R&D/
design linkages. Many components of the clusters
are poorly developed, inefficient or missing. As a
result, the cluster is not functioning efficiently and
this will continue to undermine its competitiveness
in the face of competition from other Asian RMG
centers especially China.
There are many problems associated with the
operations of the RMG industry cluster. Most large
firms have purchased backup utility systems (power
generation, water supply, steam supply and ETP) to
overcome continuous disruptions to public agency
provision of services. The large labor force and
mid-level technical/management staff are often not
sufficiently skilled to take on greater responsibilities or are technologically literate. There is a heavy
reliance upon foreign skilled man power to do tasks
that could easily be done by trained Bangladeshis,
provided there were facilities to do so. While telecommunication have improved, transport services,
congestion and logistics management are becoming worse, thereby adding to the transaction costs
of business. Quality assurance on many projects
is weak, leading to high rejection rates on export
products.
Supply Chain Mapping
Figure 6 shows the nature of the vertical supply
chain for the textile and RMG Industry in DCR.
There are over nine stages in the supply chain for
some products produced by firms in the cluster.
Each stage offers opportunity to add value to
products, especially by horizontal integration of
design and marketing services. Mapping the RMG
supply chain was important in aiding industry understanding of the production systems operating
within the cluster, the value-adding elements of
the cluster and the linkages to supporting supply
industries and services. The textile and apparel
industry’s supply chain has extensive backward
linkages that have a strong multiplier effect on
employment and raw material supply.
Overall Competitiveness
Figure 7 shows the overall completeness of the five
driving factors affecting the competitiveness of the
cluster. Overall, the competitiveness of the cluster is
weak and in need of improvement. Demand conditions are most favorable in the cluster, as most of
the products are low-priced exports destined for discount or lower-priced stores in developed economies.
The weakest position is government support. Much
of this has to do with the need for industry reforms
and removal of many unnecessary restrictions on the
operations of the industry, and in the provision of
essential infrastructure and services. Factor condi-
Fig 6: Nine Stages of Supply Chain for Textile and Readymade Garments Industry, Dhaka
NaturalFibers:
1 .Cotton
2.JuteFibers
Fiber
ManMade
Fibers
Sy nthetic
Fibers
1 .Wool
2.Sil k
K nitting
Ginning
Spinning
Lining,Button,
Zipandother
accessories
Weaving
Y arn
Export
Cloth
Ready made
Garments
Dyeing
Local
Market
Source: Authors (forthcoming 2010)
16
January 2011
Fig 7: Analysis of the Competitiveness Drivers of the RMG Cluster, Dhaka
tions, firm strategy and rivalry and supporting industries are not internationally competitive.
Factor Conditions
Participants in the initial industry stakeholder meeting for the RMG industry cluster identified a number
of labor problems that were affecting the effectiveness and efficiency of the sector. There is lack of
adequate education and training facilities and insufficient skilled manpower to improve the competitiveness and performance of the RMG sector. The only
specialized education institution serving the sector
is the College of Textile Engineering and Technology.
Some educational institutions offer degree courses
for fashion technology, merchandising, supply chain
management, etc., but the greatest need is for education and training facilities to upgrade technical
skills and quality enhancement programs. This is a
significant factor affecting the poor floor quality of
finished goods and high rejection rates in the RMG
industry in DCR.
Utility services supporting the RMG industry
were identified as being poor and unreliable. The
DCR LGUs also need to improve the delivery and
quality of utility services, especially in areas where
the concentration of industrial units is high. Industry focus group participants also identified problems
with proximity and access to raw materials. This
indicates the need for government and industry to
January 2011
work together to make a greater effort to improve
the quantity and quality of raw materials supply and
delivery systems to support the bottom-end of the
supply chain.
Conditions for employees working in RMG factories are generally poor, due to low wages, high rents
and overcrowded housing, along with poor access to
basic health and social services. Work place safety
and health conditions in factories are poor and, in
some cases, dangerous. These factors impact on
workplace productivity and stoppages due to accidents. Many of these costs are considered externalities and not the responsibility of business; however,
they have a significant impact on the overall productivity of the sector.
Demand Conditions
Market conditions for the RMG industry are highly
competitive for exporting firms, but the domestic
market is very weak. There is the realization by
many companies that international markets are going to become more difficult to access and that expansion into the domestic markets will be important
if the industry is to grow. However, the capacity of
the domestic market to expand is constrained, as
most of the population has little excess disposable
income to spend on clothing. However, demand elasticity for cheap cloth is low, thus, making the sector
less vulnerable to international business risk associ17
ated with raw material prices. The market will have
to be developed for budget and a few niche product
lines of clothes and dress wear. The capacity of the
sector to develop new products is relatively weak, as
is the capacity to respond to change and innovate.
The ability to develop new products and change production line processes will be important if the cluster
is to maintain and develop its export market share
and develop domestic market opportunities.
The dynamics of the business environment is relatively strong and quality and reliability of product is
high, because firms have to compete in international
markets. Entrepreneurs in this sector are generally
across the need for post sales and product support,
as this is important for quality assurance and product reputation in dealing with foreign buyers. The
RMG sector in Bangladesh seems capable of dealing
with international business risks, but still needs to
improve the level of business ethics and risk management. Despite the current global recession, the
RMG sector in Bangladesh shows a moderate level of
growth, which suggests they are experienced enough
to deal with the problems this has created globally
for the industry. Demand elasticity for cheap cloth is
low, thus, making the cluster less vulnerable to international business risk associated with rapid fluctuations in raw material prices. A significant demand
factor that will affect the industry in future will be
the pressure place upon the industries to be more
carbon neutral. This will be a major challenge for
the RMG industry, as it will significantly affect costs,
and likely put a downward pressure on wages.
Firm Strategy and Rivalry
The RMG industry is dominated by local firms. There
are few joint ventures or foreign firms engaged in
the in the Dhaka RGM cluster. Foreign firm interests tend to Taiwanese and Korean. There is need for
the industry to expand its engagement with foreign
firms to speed up the rate of technology transfer, to
adopt more modern management practices and to
use the purchasing power of foreign firms to gain
access to new and expanded markets. There is need
also to improve the flexibility and integration of
production systems. While many firms are entrepreneurial, there is rigidity to change and most do
18
not have the capital to invest in new technologies
or way to respond to rapidly changing market demands. Investment in the textile and clothing sector
could generate more wealth for the country, but the
government will need to take steps to reform foreign
investment policy and tariffs if it wants to attract
foreign investment and modernize productions systems in the sector.
The practice of knowledge sharing and collaboration within the firms is new for most businesses operating in the RMG industry sector in Bangladesh.
So is the level of technological diffusion along supply
chains. The industry, as a whole, has not realized
that collaboration is necessary to take advantage of
economies of scale, and to overcome the treats from
more capital-intensive production systems that are
driving down production costs in other parts of Asia.
Firms could share the experience of knowledge on
market condition or new technology. Initiatives to
encourage the practice of knowledge sharing will be
an important step in enhancing a more collaborative approach to competition and production in the
sector.
Finally, the uptake of modern technology in the
RMG sector is not high. Bangladesh has an abundance of unskilled labor, and many firms are prepared to force down labor costs in order to remain
competitive. Many firms don’t realize that forcing
down labor costs often leads to lower productivity. Higher salaries, up-skilling of workers and the
introduction of more modern technologies lead to
increased productivity and higher returns on capital. The application of new technologies has been
frustrated by labor laws and practices that prevent
the adoption of new technologies. The slow uptake
in new technology is a significant constraint on the
development and competitiveness of the sector.
Related and Supporting Industries
The research found many firms were not satisfied
with the performance of supporting services, especially government services that are very slow and
prone to rent seeking. Modern industries are increasingly dependent on high quality information,
regulation, financial and legal services to maintain
competitiveness. These support services are weak or
January 2011
are lacking in the cluster, and it is one of the most
significant constraints on its development.
The value adding potential in the sector is high,
but opportunities to expand and develop supply chain
industries are undermined by poor knowledge, lack
of government policy and support for innovation,
research and development. Most firms do not know
how to value add, sticking to traditional production
systems and practices that are rapidly becoming outdated. Education programs to encourage innovation
and risk management of product development are
necessary.
Government
Firms in the clothing & textile sector expect a lot
of support from the government. This is partly because industrialization in Bangladesh began under
socialist policies that tended to protect and support
firms from competition. There is no coherent policy
for supporting the development of the RMG cluster
at this time. Private sector investment in R&D is
negligible. The RMG industry is the ‘thrust sector’
for the economy, and they do get some tax benefit
support from the government; however, there is the
need for long-term business development policy, institutional reforms, tax breaks for R&D and venture
capital formation and low interest loans that are
necessary to enhance the performance of the sector.
The government must also take a leading role in the
development of strategic public infrastructure, such
industrial estate and infrastructure development,
and land banking to ensure the industry can grow
and develop sustainably.
Comparison Of The Competitiveness Of Rmg Clusters In Dhaka, Colombo
And Delhi
An analysis of the attributes and drivers of competitiveness for the three RMG clusters was undertaken to identify differences between the industries
in the three countries. The results of the data collected are shown in table 3 and analysis of the results summarized in the following discussion.
January 2011
Competitive Analysis of RMG Clusters
Table 3 shows the scores for 39 current and future
attributes of competitiveness for the RMG industry clusters in Colombo, Delhi and Dhaka. Figure
8 shows the 39 competitive attributes for the five
drivers aggregated to 13 key or primary attributes.
There are significant differences between the competitiveness of attributes in the three clusters. The
comparative analysis suggests that the Colombo
cluster overall is the most competitive of the three
clusters. This is because it is more specialized and
targets the higher value end of the global consumer market. However, the cluster has a number of
weaknesses that need support if it is to enhance its
competitive position and develop. All three clusters are facing strong competition from Southeast
Asian producers and will not be in a position to
strengthen their competitive position by relying on
advantage through economies of scale in the future.
To develop, it will have to identify how to add value
along the supply chains.
Several weak competitiveness attributes are
common to all the clusters studied. Overall support
from government is weak, compared to other Asian
countries. Value adding, development of markets,
access to resources and access to skilled labor are
common factors undermining the competitiveness
of the cluster. The condition in Colombo in the
social and business environments, collaboration,
technology orientation, infrastructure and supply
chains is much stronger than in the other clusters.
The Colombo cluster appears to have a much stronger willingness of firms to collaborate, although
this might be because the firms in the clusters is
having to pitch themselves.
The market focus of all the clusters is exports,
primarily to generate foreign exchange earnings.
While leading firms in the clusters are aware of the
potential of developing domestic markets, inefficiencies in the production chain process of the cluster
mean that profit margins and the potential to add
value and expand demand in the domestic market
have not been attractive. Firms in Dhaka, especially,
are reluctant to share information and knowledge to
improve cross-industry learning that could support
innovation. Social capital in the cluster is strong be19
Fig 8: Comparison of the 13 Primary Competitive Attributes for the Three RMG Clusters
RELATED
SUPPORTING
INDUSTRIES
Government
Labour
4.00
3.50
FIRMSTRATEGY
STRUCTURE
ANDRIVALRY
Infrastructure
3.00
2.50
ValueAdding
Resources
2.00
1.50
1.00
SupplyChains
SocialEnvironment
0.50
0.00
Technology
Orientation
Markets
DEMAND
CONDITIONS
Collaboration
FACTOR
CONDITIONS
NewProducts
Structure
Business
Environment
cause of the long history and associations between
local producers and suppliers in areas with a strong
physical concentration of similar types of businesses.
As a result, opportunities for the clusters to support
endogenous growth is being hampered.
Government support for cluster development in
all three countries is generally weak, especially the
unwillingness of governments to streamline business
approval processes, increase resources for education and training, and incentives to upgrade technologies that will enhance business performance
and lead to more sustainable industry development.
Governments are also reluctant to address the serious environmental problems associated with many
of these clusters. Most clusters enjoy some strategic
advantage by being located close to sources of raw
materials that are reliable in terms of supply and
of reasonably good quality; however, there is still a
high import component, especially for synthetic garments, which weakens the competitiveness of the resource attribute. Competition in global markets has
raised awareness of the need for improved quality
assurance, production sustainability and business
ethics. Without such improvements, cluster firms
find securing international contracts difficult.
20
ApparelClusterColombo
Okhla&NoidaReadymadeGarmentsDelhi
RMGIndustryDhaka
Two sets of competitive attributes require the
most support. The first set is related to supporting industries, especially strengthening the delivery
and quality of local business support services, identifying opportunities to add value to supply chains,
and sharing this knowledge with other businesses
in the cluster. Enhancing the competitiveness of
these attributes associated with factor conditions
will require formal and informal dissemination
of knowledge though the development of training
facilities, networks and partnerships and industry
associations.
The second significant set of attributes requiring support relates to government services.
Government support for clusters is limited in all
three countries. Approval systems for business
development are bureaucratic, which deters investors and new entrants into the cluster. Business and environmental regulations are complex
and not enforced. Governments’ failure to address
environmental problems affects public health and
employees’ productivity. Government support for
R&D is limited, undermining clusters’ capacity
to raise productivity and production along supply
chain systems.
January 2011
Table 3 Competitiveness Attributes for RMG Industry Clusters in Colombo, Delhi and Dhaka
FACTORCONDITIONS
Labour
AvailabilityofSkilledLabour
ManagementSkills
EfficiencyandProductivityofLabour
EducationandTrainingfacilities
Infrastructure
QualityofInfrastructureServices(logistics)
QualityofInfrastructureServices(utilities)
CostofServices
QualityofTelecommunicationServices
Resources
Proximitytorawmaterial
Costoflocalrawmaterialsvisimports
Qualityofrawmaterials
SocialEnvironment
Qualityoflivingenvironmentforworkforce
Workplaceconditions
DEMANDCONDITIONS
Markets
Expandingdomesticandlocalmarkets
Expandingexportmarkets
NewProducts
demandexpansioncapacityfornewproducts
Responsivenessandinnovativenesstochange
BusinessEnvironment
Quality&reliabilityofproductorservice
Productsustainablyawarenessandsupport
Strongbusinessethics
Readinesstofacerisk
FIRMSTRATEGYSTRUCTUREANDRIVALRY
Structure
Extentofforeignandjointventurefirmpresence
Flexibilityofproductionsystems
Collaboration
Strongindustryfirmcollaboration
Sharedindustryknowledgecapitaldevelopment
Strongsocialcapitalandbusinessnetworks
Nationalorinternationalleadership
Civicentrepreneurshipandcommunityengagement
TechnologyOrientation
Highleveloftechnologyapplicationinfirms
RELATEDSUPPORTINGINDUSTRIES
SupplyChains
Strengthoflocalbusinesssupportservices
Responsivenessoflocalsupportservices
Qualityoflocalsupportservices
ValueAdding
Potentialtoaddvaluetosupplychains
Businessawarenessofvalueaddingpotential
GOVERNMENT
Governmentsupportforclusterdevelopment
Streamlinedbusinessapprovalsystems
Supportforsustainableindustrydevelopment
Enforcementofbusinessregulations
SupportforR&D
Average
January 2011
RMGIndustryDhaka
GapAnalysis
ApparelCluster
Colombo
Okhla&Noida
ReadymadeGarments
Delhi
RMGIndustryDhaka
NecessaryCompetitive
Position
ApparealCluster
Colombo
Okhla&Noida
ReadymadeGarments
Delhi
RMGIndustryDhaka
ApparelCluster
Colombo
Okhla&Noida
ReadymadeGarments
Delhi
CurrentCompetitivePosition
3.02
2.13
2.10
4.71
4.51
3.82
1.69
2.38
1.72
3.20
3.20
3.00
2.80
2.11
2.50
2.22
3.11
2.10
1.80
2.40
1.00
4.80
5.00
4.80
5.00
4.22
4.72
4.44
4.66
4.00
3.90
3.80
3.60
1.60
1.80
1.80
2.20
2.11
2.22
2.22
1.55
1.90
2.10
1.40
2.60
2.80
3.00
3.20
3.80
2.11
2.34
1.50
1.11
2.20
1.80
2.20
2.70
4.80
4.40
4.80
4.60
4.61
4.61
4.50
4.77
4.10
3.80
3.40
3.90
2.00
1.40
1.60
0.80
2.50
2.27
3.00
3.66
1.90
2.00
1.20
1.20
2.20
2.40
3.40
2.14
1.93
2.50
2.20
2.40
3.10
4.20
5.00
4.60
4.42
4.57
4.62
4.10
3.70
4.30
2.00
2.60
1.20
2.28
2.64
2.12
1.90
1.30
1.20
2.40
3.80
2.71
2.28
1.83
2.40
1.10
2.30
2.31
4.40
4.80
4.29
4.05
4.38
5.18
3.10
4.00
3.53
2.00
1.00
1.57
1.77
2.55
2.78
2.00
1.70
1.21
1.40
2.20
1.37
2.28
1.00
3.20
3.20
4.40
4.31
4.66
3.00
4.20
1.80
2.20
2.94
2.38
2.00
1.00
2.00
2.80
1.56
1.94
2.00
2.00
3.80
4.80
4.33
4.44
3.60
3.40
1.80
2.00
2.77
2.50
1.60
1.40
3.60
3.20
3.80
2.80
2.70
2.50
4.80
4.40
4.60
1.20
1.20
0.80
4.48
3.46
1.48
2.50
2.00
2.22
2.17
2.00
0.30
0.90
1.30
1.81
4.88
4.37
4.77
4.50
4.26
3.10
3.60
3.80
3.00
2.38
2.37
2.55
2.33
2.26
2.80
2.60
2.32
1.29
1.60
1.90
3.80
4.40
3.75
4.12
3.30
3.50
1.00
1.80
1.43
2.83
1.70
1.60
2.80
2.40
3.60
3.40
3.60
2.62
2.65
2.45
2.55
2.05
1.40
1.60
2.30
2.30
1.30
4.20
5.00
5.00
4.80
4.40
4.12
4.31
4.33
4.38
4.27
3.20
3.40
3.80
3.70
3.30
1.40
2.60
1.40
1.40
0.80
1.50
1.66
1.88
1.83
2.22
1.80
1.80
1.50
1.40
2.00
2.80
2.80
2.16
2.43
2.10
1.98
4.20
4.92
4.77
4.63
3.50
3.98
1.40
2.12
2.61
2.20
1.40
2.00
2.80
2.80
3.20
2.41
2.20
2.61
1.80
1.80
1.90
4.80
5.00
5.00
4.66
4.62
4.75
3.90
4.00
4.00
2.00
2.20
1.80
2.25
2.42
2.14
2.10
2.20
2.10
2.80
2.40
1.72
2.20
1.40
1.80
2.00
1.20
2.50
2.44
2.71
2.82
2.37
2.12
2.81
3.41
2.40
2.00
1.44
0.90
1.50
1.60
2.20
1.00
5.00
4.80
5.00
5.00
5.00
5.00
5.00
5.00
4.62
4.50
4.50
4.50
4.37
4.43
4.56
4.66
3.80
4.20
3.66
3.80
3.50
4.00
3.60
3.40
2.20
2.40
3.28
2.80
3.60
3.20
3.00
3.80
2.12
2.06
1.80
1.68
2.00
2.31
1.75
1.25
1.40
2.20
2.22
2.90
2.00
2.40
1.40
2.40
2.68
2.21
1.92
4.52
4.36
3.59
1.84
2.15
1.67
1.65
21
Competitiveness Gap Analysis in the Three
Clusters
Figures 9 show the competitive gap for conditions
for the 13 primary attributes of competitiveness
in the three clusters using aggregated data derived from table 3. There are significant differences between the competitiveness gaps for the
13 primary attributes in each cluster. The gap
analysis measures the difference between the perceived actual and necessary level of competitiveness considered necessary to a level or national
or international competitiveness. For the three
clusters, 18 attributes have an average competi-
tion. Currently, the clusters do not have enough
capacity to meet the demand for skilled labor
and management, which are essential to improve
overall productivity and performance. Education
and training facilities to meet the ongoing and
expanding demand for professional and technical
skills and competencies needed to support the nine
clusters are in short supply. Foreign enterprises
in some clusters are recruiting international
staff because of the shortage of local skills. Skill
shortages are undermining firms’ ability to build
strong, competitive management and production
capabilities.
Fig 9 Competitive Gap Analysis 13 Primary Competitive Attributes in the Three Clusters
RELATED
SUPPORTING
INDUSTRIES
Government
Labour
3.50
3.00
FIRMSTRATEGY
STRUCTURE
ANDRIVALRY
Infrastructure
2.50
ValueAdding
Resources
2.00
1.50
1.00
0.50
SupplyChains
SocialEnvironment
0.00
ApparelClusterColombo
Technology
Orientation
Markets
Collaboration
NewProducts
Structure
Okhla&NoidaReadymadeGarments
Delhi
RMGIndustryDhaka
Business
Environment
FACTOR
CONDITIONS
DEMAND
CONDITIONS
tive deficiency score gap of 2 or more considered
necessary to support the desired level of competitiveness. Nineteen attributes had scores between
2 and 1.5 for the desired level of competitiveness
improvement. The deficiency gap analysis is a useful means of identifying priorities for strengthening the competitiveness attributes supporting the
development of a cluster.
The gaps in the competitive attributes for factor conditions occur mainly in the area of human
resource development. The clusters have an abundant supply of unskilled labor, but all were experiencing a high level of skills loss through migra22
The lack of government support and infrastructure is a problem for the development of all the
industry clusters studied, although the situation is
not as bad as for the prior issues, as a significant
proportion of leading firms in the clusters are located in planned industrial areas and districts, and
infrastructure and utility services are generally
better in these locations than in inner city areas.
The costs of services, especially water, electricity
and telecommunications, are high because of system losses and theft that affect production costs,
and hence the competitiveness, of many firms. Poor
telecommunications services combined with low
January 2011
levels of computer literacy often mean that contracts are lost, many to clusters in Southeast Asian
countries where these services are much more reliable. The proximity to materials used in production
is a competitive advantage for the clusters studied,
but poor logistics are causing delivery delays and
damage, affecting just-in-time and perishable food
businesses in particular.
Many larger firms in the RMG clusters realize
that appropriate residential accommodation is essential to attract and maintain skilled workers. It
is also important to ensure healthy and productive
workforces. When planning and developing special
enterprise zones and industrial estates, governments have failed to provide for workers’ housing
needs.
Demand condition deficiencies were the lack
of capacity to expand export markets and develop
domestic markets, firms’ slow responsiveness to
changes in market demand, and lack of innovation
to respond to demand for new products. The clusters tend to suffer from inertia, which reduces the
overall dynamics of business in the cluster.
Priorities For Fostering
Cluster Development In
Rmg Industries
The goal of the CCED approach seeks to identify
bankable projects that are attractive to investors
and prioritize investment areas to maximize the
economic impact of development in cities in Asia.
Government support is important for the development of clusters, because many projects involving
major infrastructure, facilities and capacity-building programs entail high initial risks, which private
investors find unacceptable. For many projects the
economic returns to the community and business
are high, but the financial returns to investors are
not acceptable. In such cases, CCED analysis can
provide better information of “where to invest
first” to have clusters develop more efficiently and
to generate job opportunities for the local residents.
Governments have a key role to play in sharing risks
or guaranteeing cash flow during the initial stages
January 2011
of a project intended to support the development of
a cluster. This is common for public–private partnership projects, where governments need to take
a leading role in supporting cluster development
projects to overcome risks before private sector
partner(s) become engaged.
Many of the investments in the action plans for
clusters developed for the three clusters are targeted at enhancing government support and industry services, as these were shown to be particularly
weak in all three countries. Most priority projects
selected are needed to reduce the external transaction costs associated with the operations of firms
involved in the cluster. Many projects involve public sector investment, as engaging businesses in
investment projects helps to improve municipal infrastructure and services, the capacity of logistics
support systems, R&D, education and training, and
reforming business regulations. These are matters
best undertaken by governments, but stakeholders’
interests must be considered when addressing these
issues. In many cases, business can offer solutions
and be engaged in the delivery of public services,
provided it is profitable and expedient for them to
do so.
Priority areas to support the development of
RMG clusters in the three countries include:
n improving knowledge management and international marketing intelligence
n applying ICT technologies to improve efficiencies in the clusters
n providing training facilities and programs to
enhance the knowledge and skills of cluster workforces
n improving the delivery of utilities, especially
water supply, waste management, electricity, and
telecommunications services
n enhancing support for R&D, particularly to foster innovation and the development of new products
and services
n streamlining approval and permitting processes
by providing one-stop shop facilities and e-governance systems
n developing business networks and associations
to foster the dissemination of knowledge and formal and informal (tacit) learning
23
n Developing special initiatives such as an ap-
parel city in Colombo, regional garment centers
in Dhaka, and national garment institutes in Delhi
and Dhaka
Conclusion
The CCED analysis of the RMG industries in Colombo, Delhi and Dhaka has added a new dimension to analyzing the competitiveness of clusters in
Asian cities. There is growing interest in Bangladesh, India and Sri Lanka on the role clusters could
play in supporting local economic development and
attracting foreign investment. The development
and testing of CCED analytical methodology in the
three countries has involved a significant learning
process, along with experimentation not commonly
associated with this type of research undertaken by
development banks. The process has provided insights into improved project design of development
bank projects, but it took much longer than anticipated to achieve results, the data collection proved
problematic, and the facilitating of industry focus
groups to share information and collaborating in
the qualitative research involved a great deal of
trust building and education before good cooperation between industry stakeholders and the government was achieved.
CCED analytical methodology uses many
techniques well -established in regional economics research and practices to analyze and prepare strategies for local economic development.
The CCED is one of the first kinds of research in
competitiveness and cluster areas where it combines spatial agglomeration for practical urban
development perspectives. The process has demonstrated that when combined with limited qualitative data, qualitative techniques can generate
information and insights that provide valuable
understanding insights into what shapes the development of local economies and identifies the
competitive strengths as well as weaknesses in
existing strategic architecture.
The RMG industry is a highly competitive industry. In Asia it is a labor-intensive industry,
which employs millions of mainly low-skilled and
low-paid female workers. In most cases the indus24
tries are only engaged in the primary production
stage of manufacturing and export, which provides
few opportunities for RMG clusters to significantly
climb up the supply chain and add value to local
production systems. With the expansion of domestic markets, there is significant potential of the
RMG industry clusters to expand both the horizontal and vertical supply chains in the industry. To
do this they must create much more competitive
strategic architecture.
Factor conditions of competitiveness in all three
RMG clusters are relatively weak, especially government support. The enabling environments to support
cluster development in all three cities need to be substantially improved. The unnecessary high levels of
bureaucracy in governance and regulations systems,
rent seeking and the lack of government support and
know-how to develop the RMG industries in Colombo, Delhi and Dhaka is holding back the development
of the industry and undermining its competitiveness.
Greater support for clustering by local and national
government could help to overcome some the problems in infrastructure and skills shortages through
a range of partnerships with the private sectors and
the fostering of strong industry cluster organizations. By fostering a more collaborative approach
to cluster development to overcome some of these
problems, it should be possible to reduce transactions cost to business and make these cities more
attractive places for investors in the future.
The investigation into the RMG clusters has led
to important discoveries that could help policy decision making by governments, businesses, and investors to facilitate opportunities to support the development of clusters. CCED analysis has enhanced
well-established research techniques by enabling a
more detailed exploration into the competitiveness
of cities and industry clusters than has been possible before. Finally, the CCED study of the RMG
clusters has led to a better understanding of the
nature and economic importance of the three RMG
clusters in the three cities in which the studies were
conducted, and how industry and government can
work collaboratively to develop pathways that can
lead to the achievement of more sustainable development outcomes for these clusters in the future.
January 2011
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Press.
25
Determinants of Competitiveness: A Study of the Indian
Auto-component Industry
Joshi, Deepikaa1
Rathore, Ajay Pal Singh2
Sharma, Dipti3
ABSTRACT
In the present era of global competition, competitiveness is the key word to success. Industries are
competing in their respective domains to establish
the global benchmarking standards. Here determining the critical success factors is an important
task. In the context of the Indian auto-component
industry, this paper is an attempt to identify, integrate and analyze the factors responsible for
its competitiveness. Further, this evaluation will
assist in recognizing the critical factors of success to win a place in the global auto-component
industry.
Keywords: Competitiveness, Determinants of competitiveness, Automotive industry, Auto-component
industry
1 Department of Management Studies, Malaviya National Institute of Technology Jaipur, India
2 Department of Mechanical Engineering, Malaviya National Institute of Technology Jaipur, India
3 Department of Humanities & Social Science, Malaviya National Institute of Technology Jaipur, India
26
January 2011
INTRODUCTION
Unparalleled intensification of the worldwide
market has created a fierce competition amongst
various sectors and nations across the globe. Presently, when most of the nations are facing turbulent
growth rates, the focus is shifted to those sectors
of economy that promise accelerated growth. The
Indian automotive industry is one such sector having tremendous potential for future growth. Today,
domestic firms have already realized the market
opportunities and are trying hard to excel within
their domains. In this scenario, competitiveness is
the universally-accepted formula for growth [29].
However, leapfrogging of the Indian automotive industry has made it a part of the global supply chain
activity. To become competitive, firms or industries
need to find and act upon critical factors to success.
This not only helps in mitigating local competition,
but also builds up national competitiveness.
The Indian auto-component sector that initially
started with the development of small and medium
scale enterprises is now gaining recognition as a
‘global quality player’. The global attractiveness
and success of this sector depends on some significant factors. These factors directly or indirectly affect the performance of a firm or an industry. Thus,
it merits extraordinary attention of practitioners
and researchers. The present study is primarily focused on analyzing the competitiveness of the Indian automotive industry. Secondly, it identifies the
critical success factors for profitable development
of the Indian auto-component sector.
REVIEW OF LITERATURE
In the present era of globalization and industrialization, competitiveness is achieving a positive appreciation. Over a period of time, it has become
the name of game i.e. “be competitive and win”.
This has made competitiveness synonymous with
success. Various researchers have expressed it in
different ways; for K. Momaya [22] it is a useful
indicator of the long-term socio-economic health
of a country. For scholars with a resource-based
viewpoint, it is distinctive competence available
in any given organization [5] [6] [11] [14] [16]
January 2011
[19] [31] [33]; for scholars having a knowledgebased viewpoint, competence is creation of organizational knowledge that is proprietary to firm
(Nonaka and Spender, 1992); and for scholars with
a competence-based viewpoint, it is resources and
capabilities that are difficult to imitate [17]. Thus,
productivity comes from capability, which in turn
comes from resources and knowledge.
The wide-ranging concept of competitiveness is
built across three different levels of competitiveness i.e. firm, industry and nation. At the national
level, competitiveness is synonymous to productivity of the nation [15] [21] [27] thus augmenting
its trade and export performance [30] to achieve
high and rising standard of living [20] [34]. Essentially, it is not the nations that directly compete in
the global marketplace, competition actually arises
at the industry and firm level [22] [28]. More
precisely, firms of an industry struggle to build
up industrial competitiveness that ultimately augments national competitiveness. For this reason,
national competitiveness is often considered as the
macro factor while the individual competitiveness
of various industries and firms is counted as microfactors.
The study of various models and frameworks
related with ascertaining competitiveness has unveiled the important fact that competitiveness is a
collection of discrete variables that are often identified as determinants of competitiveness or indicators of competitiveness. The diamond approach to
international competitiveness [27] has identified
four factors for national competitiveness: (a) factor conditions, (b) demand conditions, (c) related
and supporting industries, and (d) firms’ strategy,
structure and rivalry. Caves [9] has identified five
factors responsible for inter-industry differences:
(a) competitive conditions, (b) organizational factors, (c) structural heterogeneity, (d) dynamic disturbances and (e) regulation. K. Momaya and A.
Ambastha [4] [22] have discussed different aspects
of industry level competitiveness: (a) assets, (b)
processes and (c) performance. Thus, competitiveness is a multidimensional concept [24]. However,
the determinants of competitiveness at all three
different levels are not exclusively separated. This
27
can be attributed to the mutual impact they have on
each other. The factors affecting national competitiveness are also considered as determinants of the
performance of industries and firms. On the other
hand, the ability of firms and industries is often
translated into the position that a nation’s economy
holds on a global platform.
Assessing national competitiveness is a complex
task. Nevertheless, it can always be measured with
reference to the competitiveness of the nation’s industries [7] [8] [22]. The dimensions of any given
sector’s/nation’s performance often depend upon
a large number of variables and sub-variables attached to it. Even the most authenticated reports
like Global Competitiveness Report and World
Competitiveness Yearbook have ranked the countries on the basis of various pillars and indicators.
These pillars and indicators are basically variables
or units used for measuring competitiveness. However, the factors (variables) governing competitiveness at the industry level are highly sector-specific,
and vary from sector to sector.
Various public policies adopted by the government are aimed at restructuring the present position of industry sectors [22]. This initiates open
border practices and creates a single platform for
exchange of goods and services. Thus, competitiveness for the trade sector depends on open trade or
no protection or subsidies [8] and international
trade agreements [7] [22]. This increases exports
from a country thereby allowing increased inflow
of foreign currency. Government-protected policies specify the level of FDI and FII received by
the industry as a whole [7]. This however requires
a developed infrastructure in the form of industrial
clusters [7] [28]. Thereby it brings in subsidies,
incentives and SEZs by government and industryspecific agencies. Moreover, the never-ending R&D
activities are central to technological innovations
[7] [13] [22], though it can also be achieved by
in-house automation, design knowledge and skills
[10] [23]. For heavy-technology-oriented businesses like manufacturing, investment in R&D activities
is the major source of positive cash flows. These
activities affects new product development, shortens lead time as well as cycle time [32] and finally
28
results in the realization of profits, revenue growth,
and market capitalization. It is also supported by
the concept of quality, which is highly subjective
in nature. But quality standards and accreditations
are universal performance indicators. Following
these standards usually indicates the firm-specific
degree of product quality [7] [10] [22] [23]. For
sectors that are involved in mass production like
the auto-component industry, labor productivity is
the key indicator of efficiency [7]. Simultaneously
it requires effectiveness too. Failure to attain labor
productivity renders production a costly affair. This
may increase the overall cost of doing business. Finally it can increase the price of products or services [10] [22]. For labor-intensive industries, the
world’s best economies are competing on unit labor
cost [3] [12].
According to the supply chain research community, any given firm is a set of management processes. These processes are interlinked with each
other. Any uncertainty at the first stage of forecasting the demand and supply situation can distort the
subsequent processes [10]. Moreover, satisfying
the customer is the ultimate aim of any business
activity. In business-to-business (B2B) markets it
often depends upon satisfying the other’s business
needs. Proper scheduling techniques and reducing
the frequency of machine breakdowns leads to perfect delivery [10]. Here information always plays
a very important role [10]. If shared properly and
wholly among suppliers, buyers and the ultimate
consumers, it can be a good source of competitiveness for the industry as a whole.
RESEARCH
APPROACH
METHODOLOGY/
The review of literature presented in the previous
section is aimed at highlighting the importance
of competitiveness. Factors that decide the competitiveness of the manufacturing sector are also
put forth. Further, in the next section a secondary
method of data collection is used for collecting the
required information. Statistical data from various
organizations of national repute like CRISIL, Society of Indian Automobile Manufacturers (SIAM),
January 2011
INDIAN AUTOMOTIVE INDUSTRY: A HIGH POTENTIAL FOR
GROWTH
2002-03 to 2008-09. Nevertheless, with continuous improvements in the production system and the
escalating demand conditions, the Indian automobile sector is growing at a very high pace.
It’s no wonder that presently India is among the
most favored destination for foreign automobile
manufacturers. This has strengthened the country’s
exports portfolio as well. Figure 2 shows the trend in
Indian automobile exports from 2002-03 to 200809. Analysis shows that passenger vehicle exports
have grown five times and two-wheeler exports have
more than doubled in 2008-09 compared to 200203. Presently, the Indian automotive sector is growing at the CAGR of 9.08% since 2003-04.
Fig 1: Trends in Indian Automobile Production
International Organization of Motor Vehicle Manufacturers, 2009
60.0
The Indian automotive industry emerged in the
1940s. After independence in 1945, this sector has
struggled very hard to become the core sector of
the economy. However, the recent global downturn
has trimmed down automobile manufacturing in
India, but due to the competence associated with
the country’s automotive sector, it has succeeded in
maintaining its position in the global market place.
Presently, India enjoys the ninth position in automobile manufacturing worldwide. Figure 1 depicts
the recent trend in automobile production from
P e rc e n ta g e o f T o ta l P ro d u c tio n
70.0
Automobile Industry
1,200,000
80.0
If auto manufacturing were a country, it would be the fifth
largest economy.
1,000,000
Commercial
vehicles
800,000
Two-wheelers
50.0
Three-wheelers
40.0
Tractors
30.0
Cars and multiutility vehicles
20.0
2002-03
Amount
2003-04
(Percent
age of
total)
Amount
2004-05
(Percent
age of
total)
Amount
Years
Data source: CRISIL Research and SIAM(Refer Table 1)
Amount
2006-07
(Perce
ntage
of
total)
Amount
2007-08
(Perce
ntage
of
total)
Com
Ve
V
Amount
2008-09
(Perce
ntage
of
total)
Amount
(Percen
tage of
total)
202,852
3.1
275,098
3.7
350,202
4.1
391,078
3.9
520,000
4.6
545,104
4.9
417,272
3.6
Twowheelers
5,109,239
79.0
5,624,950
75.8
6,454,765
74.8
7,601,801
76.0
8,436,186
73.9
8,024,804
71.8
8,385,128
73.1
Threewheelers
270,483
4.2
340,729
4.6
371,208
4.3
410,788
4.1
555,887
4.9
500,592
4.5
496,832
4.3
Tractors
166,889
2.6
190,687
2.6
245,546
2.8
296,080
3.0
352,835
3.1
345,172
3.1
335,011
2.9
Cars and
multi-utility
vehicles
721,220
11.1
990,032
13.3
1,209,654
14.0
1,308,913
13.1
1,544,850
13.5
1,767,867
15.8
1,825,748
16.1
TOTAL
6,470,683
100.0
7,421,496
100.0
8,631,375
100.0
10,008,660
100.0
11,409,75
8
100.0
11,183,539
100.0
11,459,991
100
Data source: CRISIL Research for data from 2002-2003 to 2007-2008, SIAM for data of 2008-2009
200,000
Passenger
Vehicles
2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 2008-09
Commercia
l vehicles
January 2011
400,000
0
-
2005-06
(Percent
age of
total)
600,000
10.0
Table 1: Trends in Automobile Production in India (2002-03 to 2008-09)
(nos)
N u m b e r o f V e h ic le s
Automotive Component Manufacturers Association
of India (ACMA), and India Brand Equity Foundation (IBEF) is used for the current study. Information so obtained is analyzed properly and comparison made among the data of the past five to seven
years. This unveiled the current status of the Indian
automotive industry and its future prospects. Insights from various firms have helped in determining
the factors responsible for the success of the Indian
auto component industry. The Auto Policy 2002 and
Auto Mission Plan 2006-2016 are used to validate
the identified factors of competitiveness.
29
utility vehicles
Fig 2: Trends in Indian Automobile Exports
1,200,000
1,000,000
2002-03
800,000
N u m b e r o f V e h ic le s
P e rc e n ta g e o f T o ta l P ro d u c tio n
The consistent increase in automobile manufacturing and its export has created opportunities for
both80.0
domestic as well as international firms. The industry is expected to increase its turnover to $145
70.0
billion by 2016 from the present $35 billion.
This
Commercial
vehicles by
will 60.0
increase the export revenues to $35 billion
Two-wheelers
2016. Moreover, it will generate additional
em50.0
ployment for 25 million people and is expected to
Three-wheelers
contribute
10% to the country’s GDP. Owing to its
40.0
growth status, today the country has the world’s
best
Tractors
30.0
car manufacturer’s right from the ‘people’s car’ segment20.0to ‘most luxurious car’ manufacturers. Cars and multi-
2003-04
2004-05
600,000
2005-06
400,000
2006-07
2007-08
200,000
2008-09
10.0
Auto-component
Industry
‘When an industry grows in a country, it also brings
in the growth
of 2004-05
its related
and
supporting
indus2002-03 2003-04
2005-06 2006-07
2007-08
2008-09
Yearswith the Indian auto-comtries [27]. So is the case
ponent industry. The high growth rate of the automobile sector and supportive public and private
0
Passenger
Vehicles
Commercial
Vehicles
Three Wheelers Two Wheelers
Vehicle Category
Data source: SIAM, (Refer Table 2
Table 2: Trends in Automobile Exports in India (2002-03 To 2008-09)
(Number of Vehicles)
Category
Passenger
Vehicles
Commercial
Vehicles
Three
Wheelers
Two
Wheelers
Grand
Total
2002-03
2003-04
2004-05
2005-06
2006-07
2007-08
2008-09
72,005
129,291
166,402
175,572
198,452
218,401
335739
12,255
17,432
29,940
40,600
49,537
58,994
42673
43,366
68,144
66,795
76,881
143,896
141,225
148074
179,682
265,052
366,407
513,169
619,644
819,713
1004174
307,308
479,919
629,544
806,222
1,011,529
1,238,333
1,530,660
Data source: SIAM
investment in India have highly favored the growth
of the Indian auto-component industry. Because of
its upstream and downstream linkages with various
other sectors like machine tool, steel, aluminum,
electronics, forgings, intermediate products, etc.,
this sector has a huge potential for growth.
The Indian auto-component industry reported a
size of $19 billion for the financial year 2008-09
and growing at CAGR of 23 per cent over the last
five years (IBEF). Figure 3 shows the trend of auto
30
ancillary and parts produced in India. Presently
country has approximately 500 organized and
10, 000 unorganized units involved in component
manufacturing. Total auto component produced in
country is the contribution of both organized and
unorganized units. Figure 4 shows the individual
contribution of small scale industries (SSIs) and
the organized sector.
Study indicates that the contribution of the organized sector has been far more than that of SSIs.
January 2011
Table 3: Analysis of Auto-Component Industry
Value in US $ Billion
2003-04
2004-05
2005-06
2006-07
2007-08
2008-09
Turnover
6,730
8,700
12.0
15.0
18.0
19.1
Export
1.274
1.692
2.469
2.873
3.615
3.800
Import
1.428
1.902
2.482
3.600
5.220
6.80
Investment
3.100
3.750
4.400
5.400
7.200
7.700
Fig 3: Month-wise Industrial Production of Auto
Ancillary and Parts in India
18000
17000
16000
14000
R s. M illio n
Rs. Million
15000
However, the combined efforts of SSIs and the organized sector have improved the position of clusters
involved in component manufacturing. Of the total
800,000.0
auto-components produced in the country, the major
portion
is utilized by cars, two-wheeler and three700,000.0
wheeler manufacturers. In spite of a huge turmoil
600,000.0
in the
global economy, the Indian component sector
exported $3.82 billion in 2008-09 (IMaCS).
500,000.0
There are certainly a large number of factors
responsible
400,000.0 for this growing trend; one of the most
important among them being the decision of Indian300,000.0
manufacturers to diversify their business
portfolios and to tap newer regions for exports.
200,000.0
In spite of having the world’s best manufacturing 100,000.0
practices in these regions, 58-60% of Indian
2002-03 2003-04
2004-05go2005-06
2006-07 the
2007-08US and
auto component
exports
towards
Years
Europe. Today, the Indian auto-component sector
is considered as Total
the organised
fastest-growing
sector among
sector SSI sector
Asian countries. Analysis given in Table 3 clearly
shows that investment in the component industry
13000
12000
11000
10000
9000
Mar
Jan
Feb
Dec
Oct
Nov
Sep
Jul
Aug
Jun
Apr
May
8000
Months
2003-04
2004-05
2005-06
2006-07
2007-08
2008-09
Data Source: Data as per Central Statistical Organization Compiled by Indiastat. (Refer Table 4)
Table 4: Month-wise Industrial Production of Auto Ancillary and Parts in India (2003-04 To 2008-09)
(Rs. Million)
Year
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Jan
Feb
Mar
2003-04
10075
9216
10282
10018
10108
9054
8920
9038
9648
9325
9157
9752
2004-05
9275
8772
9423
9851
9453
9472
9627
9618
10055
9763
10710
10168
2005-06
9944
10264
9939
10398
10362
10668
11094
10473
11136
10899
10797
11101
2006-07
11637
11797
11903
12122
11536
12377
11955
12343
12721
12581
12602
13356
2007-08
12381
12627
12550
12433
12706
12652
13288
12818
13538
14365
14337
16042
2008-09
14808
15366
15363
15720
16770
17107
13929
12812
10775
10047
11172
13328
Data Source: Data as per Central Statistical Organization, Compiled by Indiastat
January 2011
31
Fig 4: Individual Contribution of Small Scale Industries (SSIs) & Organized Sector
800,000.0
700,000.0
R s. M illio n
600,000.0
500,000.0
400,000.0
300,000.0
100,000.0
Mar
Jan
Feb
Dec
Nov
200,000.0
2002-03 2003-04 2004-05 2005-06 2006-07 2007-08
Years
2005-06
Total organised sector
2008-09
SSI sector
Data Source: CRISIL Research, ACMA (Refer Table 5)
As of today, the growth in the auto-component
sector has reached such a position that various
multinational companies like Mercedes, General
Motors, Ford, Daewoo, Honda and Volkswagen
have already set up their international purchasing
offices (IPOs) in India to source for their global operations. This has further complemented the growth
rate of the Indian auto-component industry. Today,
the Indian auto-component industry has become a
part of the global supply chain activity and hence
requires special attention of practitioners and researchers for its further development.
DRIVERS OF COMPETITIVENESS
The accelerated growth of the Indian automotive
sector is determined by some critical success factors. These factors are the entities and variables
involved throughout the business process, i.e. right
Table 5: Individual Contribution Of Small Scale Industries (Ssis) And Organized Sector
(Rs. Million)
Type
2002-03
2003-04
2004-05
2005-06
2006-07
2007-08
Total organized
sector
196,425.9
235,928.0
298,105.5
409,054.8
522,637.5
558,142.2
SSI sector
58,927.8
70,472.0
89,044.5
122,185.2
156,112.5
166,717.8
Total
255,353.6
306,400.0
387,150.0
531,240.0
678,750.0
724,860.0
Data Source: CRISIL Research, Automotive Component Manufacturers Association (ACMA)
has increased more than two times in the past five
years. This has supported the increase in production and exports of components in India. Both,
production and exports have shown a growth of
nearly 6% in 2009, whereas imports have shown
a growth of 31%. This is an indicator of the huge
requirement of auto-components for India-based
manufacturers. It is a matter of concern for the
locally-producing firms as they are losing domestic opportunities to foreign-based manufacturers
and hence increasing the outflow of Indian currency to the global market.
32
from procurement of raw materials to delivery of
finished goods. The degree of effectiveness and efficiency of these factors truly determines the performance of the Indian automotive industry as a
whole. For the ease of study, they are classified as
direct and indirect factors.
The elements of competitiveness actually form a
paradigm. The directly-involved entities are a member of the auto-component supply chain activity and
the indirectly-involved entities carry out supportive
functions. Moreover, the directly-involved variables
are the firms’ strategies on which an organization
January 2011
Fig 5: Entities and Variables Involved in Auto-component Business Activity
Competitive Rivalry
Third Party Logistics
Agencies
Cost
OEMs
1
2
Tier 1
Tier 2
1
2
Automobile
Assemblers
Research Firms
1
2
Customer
Delivery
Financial Institutions
Demand pattern
Directly-involved entities
Indirectly-involved entities Directly-involved variables
Indirectly-involved variables Tier 1& Tier 2 suppliers, OEMs, auto assemblers,
ultimate customers
Banks and financial institutions, third-party logistics, research firms, government and non-government agencies
Technology, human skills, resources, flexibility, quality
Competitive rivalry, demand pattern
has direct control to achieve competence. Indirectly-involved variables are mainly industry-specific
factors. A graphical depiction of the interrelationship among these factors is presented in figure 5.
The combined effect of these factors actually determines competitiveness. For the auto-component industry, which has mass production and supply, cost
competitiveness and perfect delivery are the major
criteria for success, which in turn comes from these
entities and variables. Here, 1 and 2 represent the
directly-involved variables.
Customers drive competition in the industry by
creating demand. Stipulated demand for robust and
reliable auto parts by automobile manufacturers
has forced OEMs to compete considering technology as a success factor. Today, Indian manufacturers are fully capable enough of producing hi-tech
components like electronic fuel injectors and metal
intensive components used in forging, stamping and
casting, etc. For example, Bharat Forge Limited
from India has a leading position in steel and aluminum forging across the world. However, with the
growing trend of alliances and ventures, the status
of technology as a factor is now that of an order
qualifier instead of an order winner. In this context,
success stories of Maruti Udyod Limited and SuzuJanuary 2011
ki of Japan, and that of Steering Systems and Sona
Koyo of Japan are of utmost significance. Both
these ventures were made for technology acquisition for continuous production improvement. Today, large numbers of companies are building their
product consortia and competitiveness because of
easy mode to technology transfer. Though India
is still on its learning curve as far as technology
and R&D are concerned, it has helped developing
in-house R&D and design and development (D&D)
facilities. Scorpio from Mahindra and Mahindra,
Indica and Indigo from Tata Motors and Pulsar
from Bajaj Auto’s are all indigenously-designed
vehicles. Today, Indian firms are designing after
receiving orders from manufacturers. Firms like
Sundram Fasteners have well equipped CAD/CAM
labs for testing and designing of auto components.
The developed Indian software industry is a great
source of help to the industry’s R&D activities. As
the cost of component designing in India is onetwelfth of that in the US and UK, the manufacturers like Volkswagen, Mercedes, Nissan and many
more are starting their component production in
India. Undoubtedly, intensification of the global
automotive industry has created competitive rivalry, but simultaneously it has forced firms to design
33
globally competitive business strategies to leverage
market opportunities.
Government initiatives and policies always
act as facilitators for industrial development. In
India, The Department of Heavy Industry is the
main agency for promoting the growth and development of the automotive sector. In order to
push advancement in the auto sector, the department has undertaken several measures, like the
Auto Policy in 2002, time-bound implementation
of the Auto Mission Plan 2006-16, setting up the
National Manufacturing Competitiveness Council
and Investment Commission for enhancing the
manufacturing competitiveness, and the National
Automotive Testing and R&D Infrastructure Project (NATRiP) at a total cost of $388.5 between
central and state governments to aid world-class
automotive safety, emission and performance
standards. Moreover, the government has allowed
100% foreign equity investment and reduced the
duties and taxes on raw material purchase to
5-7.5% from the earlier 10%. This has also given
an opportunity to multinationals to start their
production units in India. Apart from setting up
SEZs, the government is fostering cluster formation at the regional level, whereby manufacturers located in proximity to OEMs synergize each
others profit. Major clusters of in the country are
present in Delhi, Gurgaon, Faridabad, Manesar
(North), Mumbai, Pune, Nashik, Aurangabad
(West), Chennai, Bangalore, Hosur (South) Indore (Central India) and Jamshedpur (East). This
allows easy sharing of commonalities and complementariness. The formation of nodal associations
like ACMA and SIAM has structured the industry
for its long-term profitable development. Currently, ACMA represents 479 component manufacturers and SIAM represents 39 leading vehicle and
vehicular manufacturers in India. These agencies
act as a catalyst and interact with international
experts for the development of the sector.
The auto-component sector is a mass production industry. The advantageous position of the
country with regards to low cost skilled workforce
with multilingual capability is promoting exports
of labor-intensive work. For example, Indian firms
34
are incurring just $6 per day as compared to 33.6
in Brazil. This accounts for 9.3% of the total cost
of component production in India. Even after comparatively lower productivity, a components manufacturer enjoys a cost advantage of 2-30%. Moreover, the decreasing cost of raw materials is one of
the key factors responsible for development of the
component and ancillary industry. Raw material accounts for 57% of the total cost of auto-component
production compared to 61% in 2007 (IMaCS).
The huge popularity of cost advantage has made
India a global auto-component manufacturing hub.
German automaker Volkswagen is initiating component sourcing from India for its Russian and European plants. Carlos Ghosn of Nissan said that “If
I have to fight the battle on low cost, I am going to
do it (with a base) in India.” Thus, cost competence
is amplifying the potential gains of the Indian autocomponent manufacturing industry.
Driven by the need of export markets, quality
awareness has increased since the last decade. Indian firms have improved product quality by imbibing world-class quality standards like TS 16949,
GS 9000, ISO 9000 and OHSAS 18001. The defects have been reduced to 100 parts per million
(ppm) in 2009 from 500 ppm in 2007. Eleven Indian auto-component manufacturers have won the
prestigious Deming Award and fifteen have won
the Total Productive Maintenance (TPM) Awards
in 2009. To attain high operational efficiency, Indian suppliers are embracing modern shop floor
practices like Six-Sigma, Kaizen, TQM, TPM,
lean manufacturing, etc. Moreover, the adoption
of world-class manufacturing practices, educating
managers and shop floor workers has made Indian
component manufacturing a quality-oriented industry. It has also facilitated the flexible production
system thereby making the perfect delivery system
for firms.
The growth of rubber, aluminum and steel production as well as development of the power sector and
business infrastructure facilities within the country
has also strengthened the ancillary and component
production. However, the linkage between universities and manufacturers is still missing. These linkages, if developed properly with IITs, NITs and IIMs
January 2011
can help in technical as well as business planning activities for the enhancement of the auto-component
sector as a whole.
Various socio-economic factors that contribute
towards high growth in the Indian automobile sector are rising per capita income, falling age of firstcar users, shorter replacement cycles, rising duel
income families, new technology (which is lowering
cost of ownership), low car penetration in the country and easily-available financing options. This is
surging the demand of components and ancillaries
too. Various initiatives at the national and industry
level have made this sector a rising sector in the
Indian economy.
Besides, the strategic handling of competitive
pressure has also helped national and multinational
firms to overcome local as well as global challenges. Building industry competitiveness ultimately
paves the way towards development of nation as
a whole.
CONCLUSION
Indian is one among the fastest-growing economies
of the world. Herein, the country’s developing autocomponent industry plays a vital role. Nevertheless,
there are some factors critical to the success of developing the Indian auto-component industry. Detailed review of literature is done to identify these
factors and named them determinants of competitiveness. Findings revealed that technology, R&D
capabilities, D&D capabilities, developing status
of allied industries, low cost advantage associated
with the country, following global quality norms
and developing the socio-economic status of the
country’s population are some of the critical success factors to the Indian auto-component industry. However, government policies, nodal agencies,
escalating demand condition, intensifying competitive rivalry and large number of choices available
to the ultimate customer derive the industry competition as a whole. The study also discovered one
fact that cost and delivery are the core competence
of the auto component and ancillary industry. Any
improvement in the effectiveness of the aforesaid
factors will have a strong multiplier effect on the
auto-parts sector. Moreover, the well-implemented
January 2011
national strategies will advocate the growth of individual auto-component manufacturers and finally
the country as a whole.
The current research paper is entirely limited
to secondary data obtained from various publications of authorized sources. The above cited success
factors are required to be tested and validated in
auto component firms for generalizing the research
studies. This leaves scope for further research too.
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January 2011
Multidimensional Networks: The Changing Character
and Framework of Inter-firm Collaboration
Ploder, Michael1
Steiner, Michael2
ABSTRACT
The paper explores the form and content of economic interaction of firms based on various concepts of agglomeration and social networks. It uses
a case study of the machinery sector in the region
of Styria as empirical background.
Starting with types of clustering—the model of
pure agglomeration, the industrial-complex model
and the social-network model—the paper argues
that given geographical agglomerations allow different types of networks and different patterns
of behavior, and thus different forms of learning,
knowledge sharing and knowledge creation.
Some “stylized facts” in support of this perspective are derived from an analysis of a regional network. This network comprises more-or-less individu-
alistic open systems consisting of several areas of
overlap. Physical linkages between these networks
are rather weak, but intersections based on cooperative R&D and R&D infrastructure, qualification and
informal exchanges are clearly evident, and seem to
dominate from a regional perspective. Despite evident sectoral concentrations, direct links to the prevailing science base appear more significant as binding factors than long-term supplier networks. These
relationships are interpreted in terms of their need
for proximity, their durability and above all their direction of knowledge dependency.
Keywords: Agglomeration, Knowledge Transfer,
Social Networks, Evolutionary Economics
1 Joanneum Research
2 University Of Graz
January 2011
37
INTRODUCTION
While we are well aware that it is probably impossible to provide one single theory of clusters
and their networks, there is nevertheless a certain
consensus that several elements of specific theories
may help us understand their forms and functions.
They, thus, offer a certain unity of approach in
identifying the important elements that are needed
for explaining the changing character of the innovation process.
Recent debate has begun to focus more on how
far, and in which ways, clusters foster knowledge
creation and organizational learning, and has emphasized the organic-evolutionary dimension of
cluster-based industrial agglomerations. Knowledge has been recognized as a major source of
competitive advantage in an increasingly integrated world economy (Dosi and Malerba 1996, Grant
1996, Foss 1999, Nonaka et al 2000).
The most successful regions are perceived to be
those where firms display innovative capacity, i.e.
firms are able to adapt to a rapidly-changing marketplace and stay one step ahead of competitors.
The emphasis of cluster interpretation has
changed from an analysis of forces of agglomeration to the various forms and contents of organizational learning and knowledge exchange—the original concentration on clusters as mere geographic
concentrations of sectors and firms has been transformed into a search for institutions for knowledge
management and organizational learning emphasizing the organic-evolutionary dimension.
Growth of the knowledge base depends on intended and unintended individual processing of
experiences, i.e. ‘learning’, while the interpretation, transfer and use of experiences is influenced
by interaction between individuals and between
organizations (Cohen/Levinthal 1989, Andersen 1995, Hartmann 2006). These insights have
shifted the emphasis from material links to the
immaterial knowledge flows within clusters, and
have pointed to the need for connectivity between
different agents concerning knowledge creation
and diffusion.
This has then led to further questions concerning the degree to which clusters are to be regarded
38
as non-market devices by which firms may seek
to coordinate their activities with other firms and
knowledge-generating institutions. Ongoing learning processes between firms and within clusters
stress the importance of institutional arrangements
for the generation of knowledge and learning networks that are not available in markets (Maskell/
Malmberg 1999). As the necessary knowledge may
lie outside a firm’s traditional core competence,
inter-firm alliances and networks are widely recognized as an important organization form of innovative activity (Gay/Dousset 2005).
In this paper, we again emphasize the ideas of
agglomeration and knowledge exchange, and discuss to what extent this approach has specific regional or spatial dimensions, while focusing on the
necessity and forms of proximity, especially with
respect to knowledge exchange.
By means of network analysis we then develop
some “stylized facts” for the various dimensions of
interaction within a given network of medium-tech
firms in Styria, one of the nine provinces (regions)
of Austria. The final section is used to interpret the
findings.
GEOGRAPHICAL AGGLOMERATION AND LOCAL NETWORKS
Since Marshall (1890/1920), Weber (1929) and
Hoover (1948), many authors have dealt with the
phenomenon of geographical agglomeration. In the
discussions of clusters, networks and agglomerations, and particularly in those relating to industrial districts and agglomerations, there are certain common traits, and frequently terms are only
weakly differentiated.
The basic idea of geographical agglomeration
was brought up by Marshall (1890/1920) and the
three sources of economies of agglomeration he
mentions—input sharing, labor market pooling and
knowledge spillovers—correspond with the coreelements of the current cluster-concept, at least in
that form in which it has been discussed since the
early nineties in industrial countries. A more recent attempt to distinguish various cluster forms
has been made by Belussi (2006) by contrasting
January 2011
geographical agglomeration and active clustering
(as policy- or firm-driven strategy).
While implicitly focusing on geographical agglomeration and economies of agglomeration, we
stress here a dimension of externalities beyond
the tangible dimension of direct co-operation. On
extending the basic idea of economies of agglomeration, we see that externalities are widely enforced by informal and non-economic dimensions.
Amin and Thrift (1995) use the term “institutional
thickness” to address the existence of a supporting environment beyond firms (institutionalized
co-operations and networks). Geographic agglomeration (and concentrated versus dispersed location
patterns) set a framework for economic interaction
and (material and immaterial) linkages between
economic actors.
The existence of a cluster doesn’t necessarily
imply the coexistence of all defining characteristics of a geographical agglomeration. On the other
hand, a geographical agglomeration may also exist
in the absence of a cluster or network.
While the existence of a pure geographical agglomeration (e.g. a city) favors the development of
clusters; growing networks and clusters can also
cause the emergence of a geographical agglomeration, as was the case perhaps in Silicon Valley
in California. Myrdal’s (1957) idea of cumulative
causation corresponds with a dynamic view of a coevolutionary development of economies of agglomeration and growing clusters (without yet formalizing interdependency as was done by Kaldor, 1972
and Dixon and Thirlwall, 1975).
In other words, additional local linkages and relations strengthen tendencies of concentration and
agglomeration. Networks and clusters are possible
means of overcoming constraints of exchange within and between geographical agglomerations, and
also facilitate the definition and defense of rules of
exclusion, as already pointed out by Marshall.
Yet, what is still an open question is the microperspective. Economies of agglomeration and dimensions of interaction could be selective in respect of the actors, since they regulate the extent
to which the latter are able to participate or gain
from externalities: e.g. with respect to exchange of
January 2011
physical goods versus R&D, or labor market pools
for blue collar workers or engineers.
In addition to direct physical exchange, input
sharing and common labor market pools, systematic knowledge exchange and knowledge spillovers
have gained considerably importance as an argument for geographical concentrations of activities.
A frequently used argument is that the collaborative nature of innovation processes has reinforced
tendencies toward geographical clustering because
of the advantages of locating in close proximity to
other firms in specialized and related industries
(Storper, 1995, 1997). Transaction costs such as
transportation costs and spatial communication
costs in particular, reinforce the relationship between individual environment and the development
of embedded social networks (Granovetter 1994).
Firms establish a variety of types of interactions
and relationships, each of them having different
impacts on the knowledge generation and diffusion
process. Mariotti and Delbridge (2001) speak of
the necessity for firms—in the face of knowledge
ambiguity, of knowledge-related barriers, of tacitness and complexity of knowledge—to engage in
the management of a portfolio of ties.
Organizations are therefore likely to engage in
inter-organizational relations that show a variety
of types of ties:
They can have quite different dimensions and
can be defined according to the character of social
relations between actors, the regulation of the relationship, frequency of use, length and duration of
the relationship, and also of course in terms of the
nature of the information exchange itself (Mariotti/ Delbridge 2001, 13). It is also important to
distinguish between both content (i.e. the type of
relation) and the form (i.e. the social structure of
relations), as has been outlined by Powell/SmithDoerr (1994).
One additional question which needs to be addressed in this context concerns the legitimacy of
a pure micro-level, individual firm approach in
analysing the incentives for clustering.
Individuals and firms alone are, from an economic point of view, not capable of delivering sufficient amounts and varieties of knowledge. We are
39
confronted here with one of “the most troublesome
issues in the social sciences …” (Felin/Foss 2006,
1) – the question of the adequate level and unit of
analysis. The question of whether the individual or
social collectives (firms, networks, regions …) have
explanatory primacy is of course part of an old debate in economics, sociology and the philosophy
of science and is often now dealt with under the
heading of “methodological individualism” versus
“methodological collectivism” (Hayek 1945, Popper 1957, Coleman 1964, Douglas 1986).
Further potential for conceptual differentiation
relates to the forms, channels and mechanisms
of knowledge exchange. As this exchange occurs
through interaction, the structure of the interaction influences the extent of knowledge diffusion
(Gay/Dousset 2005). This coincides within the view
that “spatialities and temporalities are not neutral
frames, but constitutive elements of socioeconomic
transformation” (Colletis-Wahl et al 2008, p.22).
The cross-sectoral dimension of knowledge spillovers is also a source of contention in the literature.
Following Marshall (1890) and Arrow (1962),
knowledge is predominantly industry-specific.
Knowledge spillovers may therefore arise between
firms within the same industry. Jacobs (1969), on
the other hand, mentioned the significant fact that
knowledge may spill over between complementary
rather than similar industries.
The significance of geographical agglomeration
and networking is strongly determined by the particular sector (industry) and the leading technology. There seems to be a clear agreement in the
recent literature about cross-sectional differences
in agglomeration forces: As has been emphasized
by Botazzi et al (2001, 2003) and also Gordon/
McCann (2000, 2005), huge inter-sectoral differences in spatial agglomeration outcomes can be
identified.
Following Gordon/ McCann (2000) agglomeration economies appear particularly relevant in
“scale-intensive sectors” - hinting at the forms of
hierarchical agglomeration discussed above - and
in “supplier-dominated sectors”. Conversely, they
appear the least relevant in “science-based” sectors. The importance of agglomeration depends
40
closely on the prevailing sectoral and technological
pattern.
The following argumentation takes up two approaches to differentiating typologies and focuses
on the different dimensions of agglomeration and
clustering viewed as helpful guidelines in the discussion of the network observed in Styria and in
answering the key-questions of the empirical analysis. An attempt is also made to combine, and differentiate, the “agglomeration” approach with the
additional insights mentioned above.
Gordon and McCann (2000: 15) define and
discuss three theoretical approaches for industrial
clustering that reflect different (more or less idealized) perspectives on agglomeration—the model of
pure agglomeration, the industrial-complex model
and the social-network model.
n The phenomenon of economies of agglomeration
as an intrinsic motive for clustering, in the sense of
spatial concentration of economic activity, is attributed more or less exclusively to the traditional idea
of Marshallian industrial districts. Following in the
footsteps of Thünen in the field of location economics, and Smith’s idea of division of labor, the model
of pure agglomeration, which in the tradition of
Marshall is based on a local pool of specialized labor, on the increased local provision of non-traded
input specific to an industry, and on technological
spillovers may contribute to an “evolving localized
environment of learning” (Gordon/McCann 2000,
517). The Marshallian approach was quickly developed and extended by Hoover (1948) by distinguishing between localization economies and urbanization economies. Following Marshall (1890/1920),
positive externalities of agglomerations are defined
by regional non-traded inputs, knowledge and information spillovers, and a local pool of skilled
labor. From the perspective of knowledge flows
and learning processes favored by agglomeration,
such externalities occur more or less unheard and
unseen. Knowledge exchange and learning occurs
unconsciously via transfer of human or material
resources. The most important point seems to be
that the approach is not bound to the idea of direct
supply-relationships among the bulk of actors involved. Following the traditional idea of MarshalJournal of Competitiveness
January 2011
lian industrial districts, interaction is primarily led
by the needs of industrial production.
n A second group of approaches pooled by Gordon/McCann (2000: 517) under the term of industrial complex models systematically tried to
justify spatial concentration by the quantification and minimization of spatial transaction costs
(reflecting the origins of the approach, primarily transportation costs). The industrial complex
model is associated with cumulative learning
from sources inside the industry, non-transferable
experience, the role of leading firms and power
asymmetries (Iammarino, McCann 2005). Although the implicit concealment of (unplanned)
economies of agglomeration didn’t mean that they
were not relevant. Attention nevertheless shifted
to innovation as an interactive process involving
the sharing and the exchange of different forms
of knowledge between actors (Lawson and Lorenz
1999)—knowledge and competence as developed
interactively and within subgroups of a regional
economy (Freeman 1979, Lundvall 2002). The
critique here has been concerned with the question
of whether this interaction is an outcome of (neoclassical) rational behavior or the result of a more
‘associative-relational’ mode of organization, or
what has been termed ‘associative governance’,
leading to the creation of clubs, forums, consortia and other institutional schemes of partnership
(Cooke 1998; Cooke and Morgan, 1998). There
are elements of knowledge sharing in the sense
that adopting the perspective of specific clusters
represents a quasi-monopoly for the internalization of the benefits of innovation created within
the (more or less) “closed club”.
n The social-network model as the third type—
relying on trust and social embeddedness as the
dominant link between the cluster firms (and
therefore not on deliberate economic decisions
based on the minimization of different transaction
costs)—also favors the exchange of knowledge.
However, such exchange is here based on strong
interpersonal relationships that transcend firm
boundaries and allow for diverse forms of knowledge sharing. Following Iammarino and McCann
(2005), traditional and recent approaches of
January 2011
social networks may be differentiated. The traditional approach corresponds to the ‘Marshallstimulated’ industrial districts where knowledge
is mainly codified and oriented to process innovation transferred by personal contacts, and
social and political lobbying. While in the traditional approach the network seems to be based
on geographical proximity rooted in historical
experience, the new approach of social networks
seems to be based on relational and organizational proximity. The links between actors are then
stronger the more they are based on elements of
social embeddedness: norms, sets of common assumptions, habits formed by culture, history, and
of course, but not necessarily, spatial proximity.
They form social capital that favors the explicit
and implicit sharing of knowledge. New physical
technologies and innovations do not just happen,
they need social technologies as pathways to coordinate human action.
As Iammarino and McCann (2005) mention,
much of the discussion in the literature is based
on ideal types, whereas in reality all spatial clusters and industrial agglomerations will contain
more or fewer of the above characteristics, furthermore, clusters may mutate from one typology to another. From another perspective, this is
also outlined by Rychen/Zimmermann (2008, p.
768): the concept of cluster “usually considered
as a spatial concentration of industrial and technological activities” has to be enriched and “it is
more important to understand how and why firms
build links and how the structure of links will give
sense (or not) to the co-location of actors.” It is
therefore important to incorporate the dimension
of collaboration—the basic conception of firms is
a “network-driven economic strategy built on collaboration among the participants” (Reid et.al.
2008, p.2).
The following section is dedicated to interpreting the case network investigated in the light of the
approaches discussed above. The suppositions that
context, typology and significance of geographical
agglomerations and embedded networks change,
seems to be clearly reflected in the case of the machinery sector in the region of Styria.
41
THE EMPIRICAL ANALYSIS:
A QUALITATIVE APPROACH
BASED ON SOCIAL NETWORK
ANALYSIS
The empirical analysis starts with an analysis of
relevant regional data and expert interviews and
then continues with a case study analysis of the relations of engineering firms in Styria.
Interaction in the observed network
Network analysis is a well established method in
the social sciences. Recently, the method has also
been applied to the analysis of production clusters
(Krätke 2002), innovative activity and knowledge
exchange (Giuliani 2005), and alliance or R&D
networks (Gay/Dousset 2005).
Social network analysis is a helpful tool for discussing the structure of networks as it allows the
mapping and measuring of the relationships (communication and transaction) between different actors, i.e., the existence, context and portfolio of relations between actors in a regional network. It is
a method for revealing relations between different
actors. Such relations are phenomena that cannot
be reduced to the properties of individual actors or
firms themselves and thus need to be interpreted as
properties of systems than of individual actors.
The Empirical Database
The present network analysis is based on an empirical sample of firms identified by a snowballing method of sampling in cluster and network
investigation. This corresponds with the relational
approach and is developed by means of the references to actors as revealed by previous respondents
(Frank 1979, Scott 2000). 1
Our starting point was a large system supplier in
the automobile sector located in the region of Styria/Austria. The snowball method produced firms
belonging to different sub-sectors of the manufacturing sector and related supply-chain and innova-
tion-strategies. Starting with the initial firm, the
sample was developed. Following a citation path of
regional suppliers (production or commercialization of goods and services) and of regional partners
in the field of research and development (cooperative R&D and related activities and exchange, the
database for the subsequent network analysis was
extended to 23 firms, of which 18 are producers
(with different positions in the supply-chain such
as system-suppliers, component suppliers and tollmanufacturers). The remaining five are technical
business services. Additionally nine R&D institutions (universities, co-operative R&D institutions)
are included. The information and data collected
are based on extensive qualitative interviews and
supported by a quantitative survey concerning specific data.
Indicators of Interaction
Qualitative indicators revealing individual strategies of innovation are helpful discussing individual
strategies and their aggregation at the network
level. They are selectively used here to find—via
network analysis—the structural features of the
network of 32 actors. The selected indicators of
the relations cultivated by the organizations cover
three dimensions of interaction: direct delivery relations, R&D, and technological innovation in a
competitive and a pre-competitive context.
(DELIV): The firms were questioned concerning direct delivery relations (goods or services) to
clients, suppliers or partners (in the case of synergetic product bundles).2 The direct delivery of
goods and services is not reduced to the material
dimension as it also covers questions of innovation
in information management or capacity-extending
investments.
(PRE-COMP): The dimension of interaction in
the context of pre-competitive R&D was also analyzed. Pre-competitive research and development
aims to extend the product spectrum, as well as
introduce new processes and alternative materi-
1 The assumption is that the segment of the network that forms the sample is representative of the whole network. More exact knowledge of present population and relevant relationships is obviously necessary. However, results from an earlier investigation support
the accuracy of the present sample technique.
42
January 2011
als. It includes fundamental research, which is an
activity designed to broaden scientific and technical knowledge not necessarily linked to industrial or commercial objectives, as well as industrial research, i.e. research aimed at developing
or improving new or existing products, processes
or services in so far as it is also not directly connected with a client tender, offer or an existing
business relation.
(COMP): Competitive research and development and innovation processes are short- and
medium-term oriented and mostly associated with
direct expectations of return or with a direct tender
or offer etc., which is in contrast to pre-competitive
R&D that is long-term oriented.
Structure of Network and Network Density
Following the socio-centric approach, the density
of a network is given by the ratio of relations realized to the total number of potentially maximum
possible relations. We dichotomized the relations
in that we only differentiated between existence
and non-existence of a relation between two actors
[0; 1], and therefore disregarded the intensity of
the relations (in our case the frequency of interaction) surveyed. This enabled us to avoid the problems typically associated with the measurement
of the intensity of evaluated graphs (Scott 2000).
Network density yields information on the general
structure of the network as a whole.
One of the core features of an actor identified in
network analysis is its centrality. Using the concept
of centrality (in different forms) we gain insights into
the specific features of the interaction of the actors
in the network and their specific position and/or emTable 1 Density of Observed Dimensions of Networking
Relational
Dimensions
Density
(Deliv)
Direct Delivery Relations
0.068
(Pre-Comp)
Interaction In The Context Of Pre-Competitive
R&D
0.143
(Comp)
Interaction In The
Context Of Competitive
R&D And
0.074
January 2011
beddedness in the network. While density focuses on
the properties and general structure of the network
as a whole, centrality tries to capture the position of
individual actors or groups of actors within the network. This is again based on the relations revealed
by the actors, where the relations are valued ordinarily in terms of frequency of interaction. The potential centrality of an actor is determined by a broad
range of industry or sector-specific factors (Cohen
et al 2000), by capacity and individual motivation
(Bayona et al 2001, Theter 2002). A high centrality
is positively associated with multiple possibilities for
receiving and generating knowledge.
Keeping in mind that interregional and international relations exist and may be of major priority,
e.g. direct delivery relations, the analysis below focuses on regional interaction. Table 1 presents the
density measure for the three dimensions of relations between the actors.
Direct delivery relations have the weakest density. Although the datasets have been dichotomized
and therefore relations with a very low frequency
of interaction have been “up-graded”, the density
of the network of direct delivery relations is lower
than the density of knowledge-intensive and innovation-related interaction. Regional input-output
relations were reduced in order to focus attention
more on international markets.
While competitive R&D and innovation processes, especially in the case of domestic system suppliers, are partially similar in density to direct deliv-
2 The dimension of supply-chain networks is a function of vertical integration and division of labor in an industry. The automobile and aerospace industries are favorites in supply chain
networks and relations. They are, however, special cases as
middle or high volumes of products, with a relatively high
number of individual parts, are produced by specified routines. Regional clients in other areas of the machinery sector
and their limited lot or customized orders place constraints
on medium- and long-term planning, automation and growth.
This approach was not used that extensively in the machinery
sector. Given the importance of the systems subcontracted by
assemblers, a clear strategic goal of these firms is working
with a smaller number of large suppliers.
3 Even in the case of a network of 32 actors with a relatively
low density the number of cross-cutting relations is relatively
confusing, even more so with a network density of 0.223.
43
ery relations, the regional density of the network in
pre-competitive R&D is much higher. While R&D
institutions are of negligible significance in respect
of direct delivery relations, the network is based to
a considerable degree on relations with cooperative
R&D institutions.
The relational data can be used to provide a
graphical representation of the transaction network
for the organizations observed. While network diagrams offer a traditional and basic methodology for
formalizing network analysis, and are a very helpful
mean of interpretation and discussion, clarity suffers
greatly as the number of actors observed increases.3
A quite useful method of graphical representation, which is implemented in most software
packages, follows the approach of Kamada-Kawai
(1989) spring embedding algorithm. This is now
employed below.
Fig 1: Network of Firms and Knowledge
Generating Institutions
Figure 1 gives an overview of all relations recorded, and combines the three dimensions discussed above. It also takes into account the valuation of the relations in terms of frequency of
interaction. The shape of actors (nodes) corresponds
with the different types of organizations. The size
of the nodes corresponds with the size of the organization, and the length of lines corresponds with
the distance between the actors observed.
A further interesting dimension of network
analysis is ‘coreness’, which follows the idea of
core and periphery. Here we use the concept of the
k-core (Seidman 1983, Scott 2000). A k-core is
a sub-graph in which each actor is adjacent to at
least k other actors in the sub-graph. That is, for
all nodes in the sub-graph minimum the number
of the actors’ direct relations within the sub-graph
is k (in our case eight). K-core analysis complements the measurement of density, since the latter is not able to reflect structural features of the
network. The k-core is an area of relatively high
cohesion. As can be seen at first glance, we can
differentiate between those actors in the core of
the network (colored black) and those actors more
or less on the periphery of the network (colored
white). The diagram reveals the high density of
the realized relations calculated in the previous
paragraphs. In the k-core of the diagram, we find
a group of institutions that seem to interact multilaterally. In the “core” of the network, we find
R&D institutions, large system suppliers and toll
manufacturers (surface-treatment, heating etc.),
which maintain multiple, but weak relations, with
a broad range of regional clients.
Spotting a Leading Firm in the Network
Source: Present Authors
systems supplier
component supplier
toll manufacturer
technical business services
R&D- institutions
44
Here we now focus on a specific firm, ss 20 in the
total network. This is a highly specialized manufacturer of measuring equipment for science and industry. This success is based on the direct application
and transfer of scientific knowledge gained in the
measurement of physical or chemical phenomena.
The firm is highly vertically integrated and is
embedded in smaller networks following niche strategies. The partners of the firm in direct delivery
(component and toll-manufacturers) and its partJournal of Competitiveness
January 2011
ners in competitive and pre-competitive research
and development (key clients, highly specialized
business services, universities) are not identical.
On the delivery side, the observed firm interacts
with component suppliers in the field of die casting, spray casting, plastics processing, electronics,
sheet metal forming, and manufacturing of high
performance glasses.
Originally, the firm was a pure converter, producer and specialist in marketing. This division of labor
has changed since the 1980s. A well-established cooperative base allows access to university partners
and to an independent research laboratory that provides exclusive, science-driven R&D. The firm enjoys
a relatively high in-degree centrality in respect of direct deliveries. The out-degree centrality of the firm
in the region, with respect to deliveries, is considerably low bowing to the high export intensity.
A high share of the turnover is reinvested in
R&D activities, 10% for intramural R&D and an
additional 10% of the turnover for external R&D.
The degree centralities in respect of R&D (precompetitive and competitive) are higher than for
the average of the leading firms in the network. The
core competences of the firm are based on combining and applying findings from basic research, in
precision engineering and electronics.
While radical innovations and market novelties
mostly emanate from R&D or client-partners, incremental improvements are promoted by internal
R&D. R&D and production and marketing of new
products are concentrated within the region.
As the firm is not located in the core of vehicle
manufacturing, but in the interface with other sectors
such as manufacturing of plastic products or measurement techniques, it has a relatively high value for
betweenness centrality. The findings for this typical
firm serve to strengthen the thesis that firms acting
in market niches, demanding highly specialized cooperation, tend towards long-term cooperation.
The Historical Background and Changing Role
of Geographic Agglomeration in the MediumTechnology Sector in Styria
The majority of the observed firms have been in the
region for more than ten years. The current situaJanuary 2011
tion and recent developments cannot therefore be
adequately analyzed without considering the historical background and structural change of regional industry over the last few decades.
In the late 1960s and 1970s, the networks in
the medium-technology sector were dominated by
large state-owned firms that were highly vertically
integrated and had lost their headquarter functions
to Vienna. While supply-side linkages to the region
still existed, agglomeration took a very limited traditional form. In most cases, planning, R&D and
marketing/distribution functions, i.e. those functions responsible for the monitoring of markets
and technology, had been lost. Clearly, observable
lock-in effects had led to agglomeration becoming
a mere by-product of path-dependence with none
of the advantages of agglomeration mentioned by
Botazzi et al (2001).
Against the background of a history of outward dependence and nationalized standardized
mass production, the traditional indicators used
to measure the strength of social networks had
become very weak. According to Iammarino and
McCann (2005), social networks exhibit the following characteristics—knowledge is largely
codified and mature and mainly oriented to process innovation, transmitted essentially by way of
personal contacts, and there is extensive social
and political lobbying, backward and forward
linkages. As far as social networks still existed
(e.g. in the machinery and the automobile sector),
they became a fruitful base for the restructuring
of the 1990s.
During the developments of the last few decades, the typology of agglomeration and the role
of networks have changed considerably. Many large
firms were re-privatized and down-sized at the end
of the 1980s. Firms, thus, needed to learn to collaborate and develop their potential for innovation
as a strategic resource. This entailed abrupt, and
long overdue, change from a Fordist to a more flexible mode of production.
A massive structural change took place, beginning in the 1990s, especially in sectors related to
steel production, such as mechanical and automotive engineering. High degrees of diversification
45
and broad unspecified clienteles were replaced by
a focus on market niches and technological specialization, while higher lot sizes enabled higher
cross-functional integration and raised flexibility
by leaving scope for automation. Technological upgrading (including the introduction of quality and
measuring standards) also opened doors to a new
clientele. This was accompanied by extending of
their responsibilities for tool making and sourcing
capabilities, and also by shifting the responsibility
for quality and price from clients to suppliers. Innovations in these sectors were influenced by applications of specialized knowledge in the field of
materials, tooling and processing techniques, or
by the need to solve very specific problems in the
machinery sector, on the supply side, hierarchical,
spatially localized relations were developed. These
have been formed around the elite R&D-intensive
and export-oriented large firms.
Human Resources and the Regional Labor
Market
A typical characteristic of agglomerations, in the
sense of the model of pure agglomeration mentioned
by Gordon and McCann (2005), and also following
Botazzi et al (2001)—namely, a more or less common labor market pool—was not observed.
For the investigated component supplier firms
(here in more-or-less rural and isolated areas) it
is still the case that they operate with reference to
very local labor markets, binding traditions and a
low mobility of employees. Small- and medium-sized
supplier firms exhibit family-based traditional structures, sometimes over generations. Concerning the
qualification structure, there are deep differences
between original equipment manufacturers (OEMs)
or system-suppliers with R&D units on the one hand,
and basic technology providers, extended workbenches or third-party subcontractors on the other.
This is true for both lower- as well as high-skilled
workers, where employee turnover is normally a
more-or-less accepted instrument of knowledge
transfer and networking among firms. Because of
the immobility of the local labor force and the restricted capacity of the regional labor market, most
of these firms were able to retain the key-personnel
46
and competences and the regionally integrative potential of their personnel. Yet, by the same token,
this implies only little mobility of qualified personnel coming from Europe (for language reasons,
predominately from Germany). Also due to official
restrictions, labor inflow from the new EU member
countries remains limited.
Discriminative Capabilities and Heterogeneous Strategies in the Case of R&D and Innovation
As already mentioned, leading firms do not play a
dominant role on the demand side. The broad range
of material input-output linkages is directed outward and direct material linkages on the regional
level (corresponding to the industrial complex model mentioned by Gordon/McCann) are considerably
weak. In fact, the opposite seems to be true. In
the case of large firms, agglomeration phenomena
based on knowledge complementarities (Botazzi et
al 2001) seem to be clearly evident.
The R&D capacities of the observed firms were
highly varied. Nearly half of the investigated firms
(mostly SMEs) do not employ permanent R&D
staff. The leading firms have intensified R&D activities and formal co-operation with knowledgegenerating institutions since the mid-1990s.
Especially in the case of pre-competitive R&D, cooperative publicly-supported projects or participation in cooperative R&D institutions has gained
an increasing role as a policy measure during the
last decade.
In respect of knowledge-driven activities, elements of agglomeration phenomena based on knowledge complementarities were observed (following
Botazzi et al 2001). These were also in line with the
exclusivity characteristics suggested by the industrial
complex model (Gordon and McCann 2005). The
large R&D intensive firms observed here constantly
seek forms of regional pre-competitive R&D cooperation. This may result in the formation of “Clubs”
5 The Competence Centre Program was introduced in 1998.
Competence centers are co-financed by the regional government, the national government and the active partners. A
considerable part of co-operation involves third parties (preferably SMEs).
January 2011
(Gordon and McCann 2005, Cooke 2000) of closer
interaction especially in respect of R&D, or in some
cases cooperative R&D institutions. While material
input-output linkages are spreading widely, and are
outward oriented, the R&D-oriented sphere is concentrated on the local context and to a large extent
supported by intensive direct and indirect social interaction (informal exchange, contacts in the local
technical community). During the past few years,
in terms of innovation, firms already active in R&D
have undergone a shift from being demand-pull-driven (responding to market demands) to technologypush-driven (firms have become proactive in their
search for new technologies and USPs). This has increased the motivation to be integrated in the regional (technical) science community. The main spheres
of economies of agglomeration have shifted considerably during the last few decades. The newly identified
research ‘Clubs’ in publicly-supported R&D projects
are able to utilize economies of agglomeration primarily concentrated in the field of R&D and science.
As long as natural spillovers are high and competitive conflicts are manageable (e.g. in the case
of material sciences), larger firms accept weaker
partners, and/or smaller firms, and are willing to
integrate them into their activities. Low spillovers
and a higher market orientation favor more restrained, sometimes exclusive, behavior from the
stronger side. This corresponds with the findings
in the literature for partner selection in R&D cooperations (Atallah 2005).
This form of agglomeration, partially taking
place beyond formal networks, also corresponds
with the idea of a new type of social network mentioned by Iammarino and McCann (2005). Firms
engaging in cooperative pre-competitive R&D and
knowledge generation appeared to seek suitable
equal partners.
The qualitative interviews strengthened the notion that firms attempt to generate a portfolio of
cooperative partners, which consciously combines
specialization and flexibility. In terms of knowledge generation and exchange, the geographic dimension is relevant as long as the actors are able
to utilize knowledge potential. While larger firms
with noticeable R&D capacities are able to utilize
January 2011
international contacts in research and development
activities, smaller low- or medium-tech firms stick
to the region and to their regional partners. Smaller firms are confronted with a self-reinforcing combination of low R&D capability on the one hand,
and limited market demand on the other.
In agreement with the concept of absorptive capacity, it was found that firms with low R&D and
innovation potential (mainly component suppliers,
where innovation is predominately directed by investment) found it difficult to build up and retain
adequate relations with knowledge-generating organizations. The medium-tech component suppliers observed here, proved to be unable to maintain
continuous relationships with knowledge-generating institutions. They were not capable of defining,
setting up and managing relevant projects. These
low and medium-tech firms did, however, partially
utilize opportunities to establish long-term contacts
with individual public or semi-public R&D institutions (dealing with basic technologies mostly material sciences). They also tried to gain from possible
spillovers from per appropriate events or informal
inquiries. Here, partner behavior in direct delivery
and in competitive and pre-competitive research
and development, as far as existent, is not identical. While cooperative R&D and knowledge generation of regional SMEs are relatively seldom, and
supply-chain relations are dominated by extra regional linkages, low- and medium-tech SMEs gain
from knowledge-sharing in respect of quality management, information management and promotion
of the location by formal cluster organizations.
In addition, two interesting long-term partnerships between small knowledge-intensive technical
business services and large systems and component
suppliers were observed, in the network analyzed
here, and were based on long-term trust and informal exchange.
conclusion
Geographic agglomerations, on the one hand, and
networks and clusters on the other have to be interpreted as interdependent phenomena. The roles
of clusters, networks and geographical agglomeration are subject to considerable co-evolution. Dif47
ferent approaches concerning forms, channels and
mechanisms of knowledge exchange offer different
conclusions with respect to the significance of geographical agglomeration in knowledge exchange.
In the case study analysis, different dimensions
of interaction can be observed. There are networking-dimensions of material, supply-oriented transactions, and networking-dimensions of knowledge
sharing. The first belongs to the process of division
of labor dealing with the exchange of goods and
services, the second with knowledge. The main differences reside in the form of interaction and in
the impact of interaction. The spheres of physical
interaction (subcontracting relations) differ considerably from the spheres of knowledge-intensive and
R&D-driven interactions. They are different in respect of actors involved, spatial extension, and thus
significance of geographic agglomeration.
The observed network is, in its regional dimension, dominated by knowledge-intensive relations.
The qualitative evidence gathered by numerous indepth interviews reveals that the highest number of
interactions was reached in pre-competitive R&D
knowledge exchange and that immaterial dimensions dominate the material ones. The (industrial)
firms do have extensive supplier relations, but only
to a very limited extent within the region and within
the network. There is no automatic parallelism of
interactions. This does not necessarily exclude automatic spillover of knowledge connected with supplier relations, but it does emphasize that higher
intensities of knowledge exchange, as indicated by
the revealed forms of interaction are actively chosen and not a mere by-product. Knowledge-oriented
relations within the network are regionally concentrated to a large degree. Proximity per se is not sufficient to generate knowledge between firms. The
diffusion of knowledge within clusters is highly selective and strongly depends on the position of firms
within networks and their absorptive capacity. Local
universities and cooperative R&D institutions have a
dominating role and assume gate keeper functions,
especially in pre-competitive research. Firms with
a relatively high R&D capacity also take up such a
role, thus indicating the necessity of a well-developed internal knowledge base. The dominating role
48
of the newly-founded cooperative R&D institutions
(competence centers) can be taken as an indication
that this kind of network relation is rather new and
that the pattern of interaction has a temporary character, and depends on the existence of specific kinds
of knowledge-generating institutions.
In the Styrian case, the main dimensions of
economies of agglomeration have changed considerably during the last few decades. The portfolio of
interactions and the meaning of agglomeration for
the observed firms cannot be reduced to specific dimensions taken as given or not. To this extent that
they are determined by firm capabilities and firm
behavior, not all dimensions of agglomeration, and
thus economies of agglomeration, are accessible for
all agents. While small- and medium-sized firms
partially gain from economies of agglomeration
in the field of basic technologies such as material
sciences or tool making, large firms concentrated
pre-competitive research in the region in order to
gain from economies of agglomeration in the field
of science and R&D.
These agglomeration effects still seem to be concentrated around certain insider ‘clubs’. A considerable number of firms investigated are not able to
participate and gain from economies of agglomeration. While there is a long tradition of pro-active
cluster and network promotion in Styria, sectoral
diversity (i.e. a low critical mass of actors) and
relatively low absorption capacity serve to hamper
the potential gains from economies of agglomeration for a considerable share of SMEs.
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January 2011
When Policy Goes Cluster: Reflecting the European
Way(s)1
Rehfeld, Dieter2
INTRODUCTION
It is obvious that cluster activities are different
around the world. In simple words, while Ameri-can
activities are first of all business-driven, European
activities are often policy-driven (Ketels 2003). In
Europe, the European Union and structural funds
have become few of the driving forces in early
cluster-related initiatives. Cluster policy followed
with best practice in cluster initia-tives could be
studied. Despite success stories about cluster initiatives, there are different ways of implementing the
cluster approach in policy in Europe. Regional and
national governments fol-lowed their own way depending on the specific cultural and political paths
and the economic base. No wonder the cluster approach became more and more “fuzzy” (Marcusen
1999) in the course of success.
Meanwhile, management studies as well as research in economics and economic geography did
contribute to a deeper understanding of the structures and processes of cluster development (Asheim/
Cooke/Martin 2006). There is a difference, though,
between how clusters develop and work in a successful way on the one hand, and how to initiate
or influence an evolutionary proc-ess (Boschma/
Frenken 2005) like this by political strategies and
instruments on the other. The second question requires deeper understanding of political processes
because it is well-known that policy follows rules
and conventions that are different from economic
ones.
In order to fill this gap, this paper is about cluster policy from a political science point of view. It
starts with a brief outline of the context of cluster
development, and then it discusses why the cluster
approach became so dominant in all fields of economic policy. Going on, it attempts to work out what
happens when an economic success story becomes
the focus of political pro-grams. The key argument
in this context is that the differences within cluster
policy in Europe can be explained by the specific
national or sub-national strategic traditions and
cultures in eco-nomic policy. Despite those differences, there are some key problems that result from
different logics in policy and economy, and can be
studied as dilemmas that can be rebalanced, but
never solved by cluster policy. Nevertheless, cluster
policies have innovative impacts on political strategies for two reasons. Firstly, a cluster policy takes
place in the context of multi-level policy and this
means that different political levels influence each
other. Secondly, a cluster policy implies new modes
of governance or at least a recombination of given
modes of governance. In so far, cluster policy has
an experimental dimension. Finally, some conclusions are presented about the challenges needed to
improve cluster policy.
To avoid misunderstandings it is best to start
with some key definitions. In this paper cluster
resp. cluster development means the autonomous
and evolutionary economic processes that are
driven by the benefits of spatial density and re-
1 In times of network and knowledge society, all research is embedded in collective structures. Thanks to Saskia Dankwart and Anita
Pöltl for all support from additional research to language washing. Thanks to Judith Testriep for a lot of discussion and ideas.
2 Institute for Work and Technology/University of Applied Science, Gelsenkirchen
January 2011
51
gional concentration. Cluster initiative refers to
bottom-up, in most cases locally-driven, activities
of self-organization of private (and often pub-lic)
actors that aim at fostering or strengthening the
local clusters. Cluster policy refers to strategic approaches of central state activities that promote and
support the implementation of cluster initiatives by
a broad range of instruments that start with supporting self-organization and end with more-or-less
top-down planning instruments.
THE CONTEXT OF CLUSTER DEVELOPMENT
Clusters are not really new in economy. The studies of Alfred Marshal in the late 19th century are
a point of reference in most cluster studies, but
spatial inequalities and regional concentration had
been broadly discussed in economic studies in this
century (Scheuplin 2006). This is not the place to
tell the story of cluster studies in the last decades.
There are good reasons to assume that clus-ters
have been an important aspect in the spatial division of labor in the course of the 20th cen-tury,
too. For instance, the automotive industry has been
clustered at a very early stage of the development
of this value chain. In Germany, the clusters that
can be studied today had been established in the
1930s (Rehfeld 1999). Nevertheless, we can assume that in the course of mass production, standardization of the value chain, internationalization
and global diffusion of pro-duction technology, the
local environment lost strategic importance in business strategies and in academic studies as well.
When the end of standardized mass production
became inevitable, the spatially differentiated patterns of spatial division of labor came back on the
global maps. Piore/Sabel (1984) worked out the
importance of regional networking for the rise of
more flexible production systems and in regional
studies (cf. the retrospective view in Cooke 2009)
successful regional innovation sys-tems (the “holy
trinity” of regional studies refers to Third Italy,
Silicon Valley and Baden-Württemberg). In the
end, it was Porter’s research on the competitive
advantage of nations (1990) that gave the decisive
52
impulse to pay more attention to cluster development in policy as well.
In brief, there are four trends that are important
in order to understand the new interest in clus-ters.
These trends are societal, but they all have in common a specific focus on the regional level, they are
overlapping, and are strongly related to the cluster
approach (see figure 1).
Firstly, in the course of the last two or three
decades, there was a fundamental change in company culture (Boltanski/Chiapello 2003, Castells
1996) driven by different factors:
Fig 1: The Context of the Rise of the Cluster Approach
Decentralization
Regionalization
Rise of the
network economy
"Entgrenzung"
Cluster
Approach
Search of new
policy strategies
Global shifts:
New role of regions in a
global spatial division
of labor
n Companies became more embedded in value
chains than years before (this means, there is a new
balance between market relations and network relations).
n They faced rising insecurity caused by changes
in innovation speed and complexity (net-works are
helpful in reducing several of these insecurities).
n Rising integration of technology, production and
service function requires more internal and external cooperation, and a related absorption capacity
of companies’ organization.
n Globalization requires a deep understanding of
the specific impacts of different markets and the
interaction of different cultures.
This change went from a more-or-less lonesome
rider culture to a network culture that influ-enced
and partially changed the whole companies’ culture, and did not start in clusters. In com-parison
to former decades, this change raised companies’
January 2011
awareness of the region and encouraged companies’ embeddedness in clusters.
Secondly, hand-in-hand with the rise of the
network economy, the spatial division of labor is
changing. The balance between national, state
and local or regional areas is rebalancing (Sassen 2008, Rehfeld 2009). From a business point of
view, regions became more important than the national environment. Even if this is studied by different concepts (agglomeration, cluster, met-ropolitan
areas, or world cities), there is a strong focus on
the reasons and impacts of spatial con-centration
on business activities.
Thirdly, in Europe the last decades became the
high-time of regionalization and decentralization
(Hooghe/Marks/Schakel 2010). Nearly all European countries started a reorganization of the
political institutions that was driven by the idea
of decentralization—more than a new division of
responsibilities between the different political and
administrative levels. It refers to the search of new
modes of governance, especially to public-privatepartnerships, to activating instruments and to
learning processes (Benz et al 2010).
Summing up, the new spatial division of labor
and the rise of the network economy go hand in hand
and related decentralization and regionalization in
the political-administrative system gave space for
new activities that corresponded with this economic change. Clusters are of importance in all three
aspects. We can suggest that fourthly they work as
the missing link that gives policy the chance to reorganize institutional and strategic terms, and face
the economic change in a more successful way. The
next section will discuss why the cluster approach
not only became an economic success story, but a
self-enforcing process in policy as well.
THE RISE OF CLUSTER POLICY
Cluster policy is a late comer on the cluster agenda,
though there are differences. Austria and Finland
are pioneers, France and the German federal state
Baden-Württemberg hesitated for a long time,
the Middle and Eastern European countries are
somewhere in-between, and Turkey is just starting. Lower Austria, Grenoble resp. Rhone-Alpes in
January 2011
France and Tampere in Finland functioned as early
birds. West-Midlands in the UK, Wolfsburg and
Dortmund in Germany and Catalonia in Spain were
some of the most prominent followers.
Today, nobody really knows how many cluster
initiatives are active in Europe. The European
Cluster Organization Directory (2010) lists 1205
cluster organizations in 216 regions, but there are
lots of initiatives—like the privately-funded initiatives not listed in public documents—that are missing in this list.
The key impulse for cluster policy came from
two sides. On one hand, successful cluster initiatives had been established bottom-up. On the other,
international activities contributed to the dissemination of the cluster approach. The World Bank
conference in Mexico in 1997, the insti-tutionalization of The Competitiveness Institute (TCI), the
Cluster White Book (2003) and the Cluster Green
Book (2004) are some of the milestones in international cluster discussion.
In the European Union, cluster policy became
a strategic key issue in the context of the Lisbon
Strategy. Program lines like PAXIS, ProInno, Innova or KIS aimed at organizing and disseminating: good praxis, supporting networks between European clusters in order to organize shared learning
and to improve capacity building in emerging clusters and EC-policy moves towards strengthening
world-class clusters (EC 2008).
Broadly speaking, national states and federal
states have been the last actors in the field of cluster activities. The dynamics of former activities
were such that the central or federal state became
involved in the process. There are four reasons
why the cluster approach became so prominent in
policy.
In strategic terms, the cluster approach filled a
gap in economic policy. The idea of a support driven macro-economic policy that became the leading
idea in the 1980s and 1990s, in combina-tion with
the hope of rising service industries that compensate the rising weakness in productive industries,
became outdated with the crisis of the new economy around the turn of the century. The cluster approach gave the ideas to fill both gaps: to reinvent
53
meso-economic policy combin-ing regional and sector issues, and to renew the interest in productive
industries in a future-oriented way.
In institutional terms, cluster policy is a challenge for the traditional institutional setting in
Europe. Departments of different ministries had
been complementary with industrial associations
that often represented a sector and not a value
chain. Regional activities had been focused on a
small local level with strong administrative borders. Bottom-up cluster initiatives showed that it
is possible to overcome those institutional limits
and cluster policy hopes to renew the institutional
setting for economic policy.
In instrumental terms, the fuzzy character
of the cluster approach makes this approach fit
in different philosophies in economic policy. You
find versions of cluster policy that are based on
hard incentive and planning on one end and versions that try to activate private actors on the
other, an aspect that will be discussed in more
detail in the following section.
The embedding in national philosophies on
how to drive economic policy especially explains
the variations of cluster policy in Europe. Nevertheless, there are three basic assumptions in all
vari-ations of cluster policy (see fig. 2). This is
not the place to discuss the reliability of those
assump-tions because they are handled as quasi-
realities in cluster policy and in so far they are a
social fact (Durkheim 1961):
n Clusters are more the innovative spatial and
functional core in a knowledge-based global economy.
n The potential of clusters is high and can be
mobilized. The expected synergetic effects especially promise a new dynamic in competence and
innovation.
n Policy has the knowledge and the strategic capacity to make the potentials work in a dynamic
and self-enforcing way.
Following these key ideas the basic model of
intervention entails the following aspects (fig.
2):
n There is a need for deciding what clusters
(where and who) promise good results when they
get political support.
n The different fields of economic policy (labor
market policy, technology and innovation policy,
regional policy, infrastructure policy) have to be
coordinated.
n The implementation needs strong cluster initiatives that are based on a commitment from the
companies.
n If this process works, it helps to improve the
development of the cluster in a synergetic way
that brings out spill-over effects that work as innovative drivers in the national econ-omy.
From a political point
of view, this approach is
Fig 2: Key Ideas of the Intervention Model of Cluster Policy
near to the task to square
Koordination
Clustereffekte
the circle and can be
studied by the dilemma
FP1 FP2 FP3
approach (Prud’homme/
ClusterDankbaar 2007):
politik
n Policy, especially in
t1
European welfare states
Clusterti o n
ova
n
management
has strong legitimating
In
Spill-over-Effekte
from equality and co-herInnovation t0
ence. Cluster policy needs
Cluster
to select and focus on the
strong actors (“strengthen the strength”).
n The different fields of
externe Rahmenbedingungen
economic policy are em© 2007 IAT – own illustration
54
January 2011
bedded in very specific institutional con-texts and
networks, and there is a lot of doubt about the
chances of coordination.
n Implementation needs bottom-up activities,
but there is no guarantee that the interest of
those activities matches the top-down interest of
cluster policy.
n Cluster initiatives, even well-running ones, are
only one aspect in a broad range of factors that
influence cluster development. So far, evaluation
failed when they tried to isolate the impact of
economic policy and evaluation has always been
based on plausibility and indi-rect indicators.
The consequence is not that cluster policy has
no chance, but that we have to be careful when we
discuss the expected results.
Map 1: Biotech Regions in Germany
BMBF 2005
January 2011
HANDLING DILEMMAS IN
CLUSTER POLICY: TASKS AND
ILLUSTRATIONS
This chapter aims to discuss the way policy handles
the dilemmas that have been discussed in chapter
three. The first dilemma is to select promising clusters, which means the question of who and what.
Discussing this aspect we have to keep in mind that
clusters are selective by definition in at least two
ways.
First, in regional terms, clusters base on concentration. The higher the concentration of related
variety (Boschma/Frenken 2005) of economic activities (including research, education, qualification and so on), the more dense the interaction (internal as well as external) and higher the chance
of dynamic cluster effects. Therefore, cluster policy
in ideal terms has to focus on a small
group of promising clusters. To illustrate this dilemma, the case of the German biotechnology cluster is of interest. The idea was great. Germany was a
late-comer in biotechnology. It was lagging behind in the 1970s and 1980s,
but in the late 1990ies the situation got
better. There are different reasons for
the rising dynamic. It had to do with
the rising presence of international venture capital companies in Germany, and
with innovation in measurement and
analytic meth-ods and equipment. Further, all activities of sector formation
speed up: professions in education by
new curricula, different fairs, building
of an business association (biotechnology had been em-bedded in the chemical companies association before) and
so on.
The most cited reason for take-off is
the success of the bio-regio-competitive
call that was initi-ated and organized
by the German Ministry of Research
and Technology in the second half of the
1990s. This competitive call is of special
interest in our context because it aimed
55
at strength-ening the most innovative and best organized biotech-regions. Regions had been asked to
work out cooperative development strategies including crucial issues like venture capital, public approvals, university-company ties or specialized infrastructure. Due to the aims of the competitive call,
the three leading bio-technology regions (Rhineland,
Mittlerer Neckar, and Munich) were pointed out as
winners and one East-German Region (Jena) was
put in as a support region be-cause of its special
competence in biotech equipment.
Thus far, the story looked good if we think about
cluster building. Unfortunately, soon it became obFig 3: Fields of Cluster Policy in Three German
Federal States
Brandenburg
North-RhineWestphalia
Bavaria
Biotechnology
Biotechnology
Biotechnology
Aerospace
Media/IT
Aerospace
ITC
ITC
Media
Creative
industries
Automotive
Automotive
Energy
economy
Energy economy
Oil/Bio energy
Energy research
Automotive
Geo Science
Wood industry
Plastics
Plastics
Logistics
Logistics
Logistics
Optic
Nano-Micro
Nano
Paper industry
Railway
Food industries
Railway
Food Industries
Food Industries
Environmental
Technologies
Environmental
Technologies
Health Care
Medical Technologies
Tourism
Environmental
Technologies
Medical Research
Mechanical
engineering
Chemistry
Mechatronic/Robotic/
Production Systems
Chemistry
Financial services
56
vious that the losers did not accept the result. Up
to twenty regions were involved in the com-petitive
call and most of them had the feeling that they did
a good job, has high potential, and they build up a
shared vision. They tried to find new ways to get
funded, and because Germany is a strong federal
political system, most of them applied for funding by their federal state govern-ment. The federal
states programs, additional programs by the German Ministry of Research and Technology and several ways of European funding were available and
helped nearly all regions to stay in the game.
At the end of the day, there are around 30 bioregions in Germany that claim to be or to become
biotech clusters (see map 1).
Germany has nearly 600 biotech companies
and each biotech region counts for 20 companies
on an average. A lot of these regions are missing
local venture capital funds and some of them have
no laboratory infrastructure. The dilemma is that
the process was highly successful in activating local actors, but the local actors became so strong in
lobbying for public funding that at the end, public
resources became more disperse and were not concentrated on the most promising re-gions.
Secondly, in functional or sector terms, one key
result of Porter’s (1990) study is that no country
has the resources to establish globally successful
clusters in a broad range of sectors. Concentration or focusing is needed. The problem is that
there is high insecurity about industrial sectors
that will be the driving forces in the future. In
this case again, the German example illustrates
that the practice is more driven by the fear to
miss an interesting chance than by selective decision. Figure 3 summarizes the cluster activities
of three German federal states—Bavaria, NorthRhine-Westphalia and Brandenburg. We can see
that despite some differences in wording and local spe-cializations, the fields of cluster policy are
very similar.
Maybe the approach in Brandenburg is more
oriented towards productive industries, the NorthRhine-Westphalian and the Bavarian one have a
stronger focus on new technologies, but the dif-ferences are not really strong. Policy makers in charge
January 2011
of cluster policy are aware of this problem without
any doubt. In all three countries, there is a broad
consensus that 15 or 18 clusters are too much, but
because it is difficult to select without knowing the
future the key strategy is to wait for evaluation. It
is too early to discuss the results because the evaluations are in a very emerging state, but whatever
the result is the dilemma remains—in all sectors
cluster policy intends to acti-vate self organization
and when you have done this it is very hard for poli-
in regions that faced heavy sector restructuring.
This means that those regions had weak potentials
in clustering. At the same time, and without any
coordination, the central state focused strongly on
technology-driven clusters. With the shift in European structural policy towards Lisbon strategy,
the framework changed and today cluster policy
becomes linked with technology policy.
In contrast, in Finland, cluster policy had a
strong start in the context of Finnish technology
Fig 4: Cluster Policy and Cluster Initiatives Compared
Top-down
Czech Rep.
Brandenburg
France
Strategy
NRW
Austria
Finland
Bavaria
Switzerland
Bottom-up
Bottom-up
dezentral
Funding
ticians to stop the fund-ing even when the results
are not the expected ones.
As pointed out, there is need of coordination of
different fields of policy (this part bases on (cf. for
this chapter Muth/Rehfeld 2007, Rehfeld/Terstiep
2007, Terstriep (2006)). There is a long hope that
regionalization will bring out more solutions and
coordinated processes. The problem is that cluster policy on a central level is often embedded in
traditional philosophies and contexts. In most German federal states, the roots of cluster policy are
in the field of regional policy. The consequence was
that clusters got funding in regions that were lagging behind in average eco-nomic performance or
January 2011
Top-down
zentral
and innovation policy. Today, there is a shift to
strategy centers that are driven by the most important Finnish industrial value chains. In France,
we find a combination of traditional planning approaches rooted in the 1950s, in ongoing decentralization strategies and in a strong technology
driven focus. In Switzerland, cluster initiatives
are bottom-up driven in most cases and central
policy is in its emerging phase. In the German federal state Brandenburg, cluster policy was part of
the regional policy but the instruments (incentives
on the one hand, network projects on the other)
started in different contexts and now they have the
problem of coordination. In the Czech Republic,
57
you find the combination of central- and statedriven planning strategies and market-driven instruments.
These are only few examples. They illustrate
that cluster policy is often embedded in national
traditions and the related fields of economic policy.
It shows that it is far from coordinating dif-ferent
fields of economic policy, and labor market policy
has very few links with cluster policy (maybe Sweden is a case where this coordination with labor
market policy works).
Third, and this has links with the arguments
above, there is a dilemma between bottom-up and
top-down approaches, in other words, between
cluster policy and cluster initiatives. Figure 4
shows the position of cluster policy in selected
countries resp. federal states along the top-down
bottom-up axis “funding” and “strategy”. More
cluster funding and strategy are bottom-up driven
and cluster policy is only supporting, but most
strategies in cluster policy have a strong top-down
impact and they aim at activating self-organization. The problem comes to life when new activities in cluster policy meets long-standing bottomup initiatives. This is the case in most German
federal states, in certain French regions and in
some parts of the Czech Republic. The dilemma is
that if policy wants to initiate self-organization, it
has to risk that the priorities of the societal actors
are different from the central state priorities.
CLUSTER POLICY AS MULTILEVEL POLICY: FIELDS FOR
EXPERIMENTS AND LEARNING
Cluster policy is a multilevel policy. Such a multilevel policy is characterized by the following features (cf. contributions in Tömmel (ed.) 2007, Benz
et al. (ed.) 2007):
n Complex institutional and actor patterns
n Boarders between the levels and the actors are
not clearly defined, so responsibilities are not always clearly attributed
n No actor is able to achieve the desired goal on
his own, actors are interdependent
n Aim and implementation are acted out in an in58
terplay between public and private actors, and are
mainly about self-regulation and not about classical state intervention
n Which is why steering techniques that do (and
can) not fall back on authoritative instruments can
be found.
If we follow the political science discussion about
new patterns of governance, especially in the European Union, there seems to be reasons for doubt about
the success of cluster policy, since it is assumed that
multilevel policy only works if the “shadow of hierarchy” is given in the back-ground, i.e., if the state
has the possibility to fall back to other authoritative
instruments if self-organization does not work.
However, this is precisely what is not possible
with cluster policy, as without the active (and increasingly also financial) participation of the addressees, such a policy is not realistic. In order
to become aware of the demands made on cluster
policy, it is useful to keep in mind the key task.
Cluster policy wants to encourage self-organization, usually through an initial funding with digressive public participation. At the same time,
cluster policy aims towards the provision of col-lective goods that have not been provided by private
actors so far (if this was not the case, cluster policy
would not be necessary). Consequently, it is not
solely about the activation of potentials that have
been latent so far, but also about a change in corporate behavior. It is no longer the lonesome rider
company that is requested but the socially responsible and economically net-worked entrepreneur. It
should be noted that this is a development within a
specific policy field, but that such a collective adjustment of corporate action opposes diametrically
competition law, which acts on the assumption of
isolated actors only mediated through the market
and puts di-rect communication under the suspicion of not permissible agreements.
The dilemmas cluster policy has to balance are
diverse. Therefore, cluster policy can only be successful, if it proves to be adaptive with regard to
its strategies and instruments. Elements of such an
adaptive process can in fact be seen. There seems
to be a division of labor within the Euro-pean multilevel system.
January 2011
On the European level, the field for experiments
can be found. In the mentioned program areas
(PAXIS, INNOVA and PRO INNO, KIS), experiences from established cluster management activities are concentrated, new tools and instruments
Fig 5: Modes of Governance in Cluster Policy
Hierarchy
central
planningl
implementation
formation
corporatism
bundling
„venture
capital“
„
award
Market
activation
self-organization
Network
© 2007 IAT – own illustration
are tested, standards for the professionali-zation of
cluster management are elaborated and, last but
not least, the information basis for a comparability
and evaluation of cluster development is built.
The multiplicators are consultancies integrated
into the activities, networks of cluster managers,
institutions of advanced training and big international conferences. Even if the landscape of clus-ter
management in Europe is still very heterogeneous,
certain standards with regard to profes-sionalism
have been accepted that cannot be ignored in the
long run.
Cluster policy of central states, respectively of
federal states in federalist states, still has to find
its own place. If we take key categories of the governance discussion (steering through market, hierarchy and networks) as a point of reference, almost
all possible fields are covered in this triangle (fig.
5). The proceedings of states (respectively federal
states) with extreme restructuring prob-lems (e.g.
in Eastern and Central European states or Brandenburg) or of states with a strong planning tradition like France are influenced the most by classical
steering. Here, the challenge is to line the central
January 2011
state impulses with the initiation of societal selforganization.
At the other end, and this is often disregarded,
there are activities of regional self-organization of
companies that do not depend on public funding, often don’t even want to because they want to achieve
their goals independent from political requirements
and public attention.
In between, there are all sorts of hybrid
forms—initial financing aimed at a societal selforganization that later will be self-supporting
or the promotion of extraordinary cluster projects won through promotional competition—still
closely linked to markets and networks. The bundling or formation of national resources through
an intensive technological co-operation or a cooperation comparable to classical corporatism
between state, unions and companies are linked
closer to public interests. It is precisely these activities that stand to face the challenge, not to
interconnect too closely but to stay open to the
outside and therefore to new impulses.
In a certain way, such different models will always be found, depending on the economic starting
position, the readiness of social actors to participate in the provision of collective goods or na-tional
political-administrative steering philosophies and
regulation systems. However, all these different approaches have in something in common—starting
from a certain point in time they all rely on the
active participation of those addressees. This is especially true for the participation of companies.
Regardless of the starting point, cluster policy
will have to solve the distribution problems mentioned before in a different way because clear
forecasts of future economic developments are not
possible. The most promising way at the moment
seems to be to form cluster policy in accor-dance
with the promotion of venture capital.
n At first, it is reasonable to promote broadly, also
keeping in mind that not all promoted pro-jects will
be successful.
n Next, it is important to connect the promotion
to clearly defined (financial as well as material)
goals and to organize a form of support in order to
achieve those goals.
59
n Finally, at a certain point in time it is to be decided where projects can now run by themselves
and have the desired societal use, where further
support is needed because the achievement of the
desired goals take longer than foreseen and where
public activities have to be termi-nated.
If this reference to self-organization is missing, the bottom-up developed cluster management
activities and central state activities will conflict.
In the worst case, not only public resources are
wasted because of a lack of effectiveness, but the
autonomous processes of cluster development are
also thwarted, if public resources are distributed
widely as the above discussed example of German
biotechnology shows.
STRENGTHS AND WEAKNESSES OF CLUSTER POLICY IN EUROPE
The European Union bases on the idea to combine
regional diversity and coherence in a fruitful and
dynamic way. The cluster approach offers a strong
strategic frame to bring this idea to life. Due to
regional diversity, in structural as well as cultural
terms, clusters and cluster initiatives are very distinct from region to region, from value chain to
value chain. Facing this situation, cluster policy can
be studied regarding the way it balances dilemmas.
First of all, on one hand, the di-lemma allows regional distinctive ways of cluster development and
cluster initiatives; and on the other, the dilemma
makes it possible to work out general quality standards and success criteria. Without this balance, the
cluster approach becomes more fuzzy and runs the
risk of losing the potential of cluster development.
The problem is that cluster policy needs new
concepts and strategies and that there is a high
inse-curity about the results that can be expected
in a realistic way. So far, cluster policy is highly
ex-perimental and needs strong learning processes. This is, by no means, self-evident because, as
pointed out, cluster policy always runs the risk of
becoming embedded in traditional paths of single
fields of economic policy. Nevertheless, there is a
good chance of policy innovation for three reasons:
60
n Cluster policy needs to combine different modes
of governance and in the course of im-plementation; there is the chance to reflect promising ways
and to adapt policy.
n Cluster policy is a multi level policy, and in best
case the level work in complementary way.
n Cluster policy is very different on the local or
regional level and cluster managers need to act on
an international level (otherwise they risk to cause
lock-in effects), as this offers the opportunity to
share experiences and to learn from each other.
This cannot solve all the dilemmas mentioned
in the chapters above. Is it realistic to expect that
cluster policy in strong regions is so successful that
all regions benefit by spill-over effects in the long
run? Do weak regions have a realistic chance to
strengthen their economic performance when they
focus on cluster, especially in those value chains
with a long standing spatial division of labor? Is
there a realistic chance to overcome the traditional
boundaries of administrative insti-tutions? What is
needed to avoid a destructive clash between bottom-up and top-down activities?
The key idea behind this paper is that the cluster approach has a high potential to strengthen
economic performance in regions as well as in
Europe. The danger is that the cluster approach
becomes diffused and that cluster policy becomes
more vague and, in consequence, the potential of
the cluster approach becomes wasted.
Focusing on cluster policy, it is urgent to discuss
four challenges.
First, if it is true that clusters are selective and
that it makes no sense to try to develop clusters
in each region, we need further strategic concepts
for those regions that have no promising starting
points to develop clusters. A cluster is one way to
strengthen the innovative performance of re-gions,
but we need different ways to work out “innovative
spaces” (Rehfeld 2006). This includes the question
in which way these regions can make good use of
key ideas of the cluster approach, like networking,
linking local-global chains, improving competence,
organizing collective learn process and so on.
Second, we need a deeper understanding of how
cluster policy is positioned in the trends of global
January 2011
change. A lot of future trends are highly decentralized. Sustainable strategies or new health concepts
are basic challenges to improve quality of life in all
regions and it is not helpful to dis-cuss these challenges from a cluster point of view. No region is
autonomous in a global world and access to global
knowledge, and the competence to make good use
of it, is crucial for the future of all regions again.
Global migration brings out more geographical fluid
or borderless spaces and innovative, as well as, financial flows transfer geographically-fixed regions.
Clusters are nods in all trends or they have the potential to work as nods like this and cluster policy
has to avoid to fix on a given geographical level.
Third, we need evaluation concepts that are
aware of the complex aspects of cluster policy. In
certain terms it will be very successful when cluster
policy contributes to reorganize the institu-tional
setting of economic policy, when it succeeds in
combing private activities and public re-sources or
when it helps to make institutions more flexible. So
far, evaluation concepts are focus-ing on indicators,
hard ones as well as weak ones (see the examples
on the homepage of Scottish Enterprise), but, in
order to evaluate cluster policy, we need an understanding of the underlying intervention concept and
the related strategy.
Fourth, doing this we cannot expect perfect solutions, but different ways to balance dilemmas.
Good practice always is good practice in a specific
context of space and time. Clusters develop in an
evolutionary way and cluster policy has to do the
same thing. Cluster policy in this way, has to keep
in mind that it is public policy and therefore, it has
to stand for more than the economic evolutionary
way. It has to focus on public goods and benefits,
and when it does so successfully, there is a chance
for a fruitful co-evaluation between public and private interests.
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18Porter, M.E. (1990): The Competitive Advantage Of Nations. New York: Free Press Edition.
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Governance Und Policy-Making. WiiEsbaden.
January 2011
From Industrial Clusters to Global Knowledge Hubs
Reve, Torger1
ABSTRACT
Knowledge-intensive industries are increasingly located in global knowledge hubs, which are characterized by a high density of interrelated knowledge
firms operating globally. Examples include Boston
in life sciences, Silicon Valley in information and
communication technology, and Houston in oil and
gas. Typically, such global knowledge hubs emerge
from well-reputed universities and private research
labs, but they also include a wide array of commercial actors and a competent venture capital
market. Successful global knowledge hubs are able
to attract knowledge functions from major multinationals in the industry. Together with universities and their related research labs this creates an
advanced, specialized job market attracting talent
and knowledge workers on a global scale.
Global knowledge hubs emerge from industrial
clusters or geographical agglomerations of related
firms, thus such knowledge hubs are highly path
dependent, not easily lending themselves to industrial development policies. While industrial clusters typically center around large manufacturing
or service firms and their network of suppliers,
knowledge hubs are more diverse in their composition, placing universities and R&D institutions
at the center. As the density and interactions of
knowledge organizations increase, the result is vibrant innovation competition and high commercialization of innovation, given the active presence of
competent venture capitalists and investors.
Some of these knowledge hubs take global leadership positions, such as Boston in life sciences and
Silicon Valley in information technology, but they
are constantly challenged by other knowledge hubs
such as San Francisco and San Diego in biotech,
and Bangalore and Hyderabad in software and IT
services. Despite the prevalence of modern communication technology, geographical proximity matters even in high-tech industries.
In the current paper, the global knowledge hub
concept is extended to the global maritime industry, as illustrated by the Norwegian and Singaporean maritime clusters, and policy measures are
proposed to transform these maritime clusters to
global maritime knowledge hubs or super clusters.
The global knowledge hub concept is presented
as a new industrial paradigm with important implications for knowledge-based industrial development and industrial policy making.
Keywords: Knowledge hub, Maritime clusters, Norway, Singapore, Knowledge-based industries
1 BI Norwegian School of Management, Norway
January 2011
63
Introduction
In classical writings of microeconomics and organization theory, the firm is viewed as an autonomous unit facing factor and product markets. Basically, the firm is conceptualized as a production
function or an input-output system transforming
raw materials and other input factors into finished
products and services to be sold to customers in a
competitive market. The firm is basically seen as a
manufacturing unit, represented by a typical value
chain—from inbound logistics through operations,
outbound logistics, marketing and sales and aftersales service (Porter 1985).
In the writings on industrial marketing, distribution and logistics, the firm is seen to be part
of an industrial network, focusing on supplier and
distributor relationships, and the field of inter-organizational research came to power (Stern & Reve
1980, Håkansson & Snehota 1995). The same
holds true in strategy where research on strategic
alliances has been strong for many years (Lunnan
& Haugland 2008).
Rather than studying inter-organizational relations in terms of buyer-seller dyads (Stern & Reve
1980) or simple industrial networks (Håkansson
& Snehota 1995), many researchers in the fields
of economic geography (Asheim 2000) and industrial development, most notably Professor Michael
Porter (1990) at Harvard Business School, have
studied industrial agglomerations at given locations. The main terms used are industrial districts
or industrial clusters, which have been defined as
“a geographically proximate group of interconnected companies, suppliers, service providers and
associated institutions in a particular field, linked
by externalities of various kinds,” (Porter 2003).
Let us take the auto industry as an example and
see how it can be studied using various industrial
lenses.
In the first paradigm, business as manufacturing,
the auto industry is studied by analyzing major industrial actors such as GM, VW or Toyota as factories. The roots go back to scientific management and
Fordism. The analytical model applied is typically a
value chain (Stabell & Fjeldstad 1998), and the goal
is to optimize productivity and value creation.
64
In the second paradigm, business as industrial
clusters, the auto industry is studied as a network
of car manufacturers, auto part suppliers, service
providers and car dealers, particularly as the industry centers from various key locations such as
Detroit, Stuttgart or Osaka. The major manufacturing firms are placed at the core of the industrial cluster, while the other industrial actors are
referred to as related and supporting firms. This
also included universities and other knowledge providers. The model has been made world famous by
Michael Porter (1990), and empirical studies are
prevalent.
Industrial clusters represent superior locations
due to lower transaction costs of operations, and the
existence of knowledge externalities and network
effects. Knowledge externalities arise from sharing
of knowledge and from utilization of a common,
specialized infrastructure. Thus, industrial clusters
not only require a critical mass of firms at all levels
of the value chain, but there also have to be close
interactions between the industrial actors within
the cluster. The result is accelerated learning and
higher rates of innovation and commercialization,
and there seems to be clear scale effects (Krugman
1991). Thus, major industrial clusters tend to be
growing, while minor industrial clusters tend to be
reduced as firms consolidate and co-locate.
On a global scale, a hierarchy of industrial
clusters in any particular industry can typically be
observed. The first tier consists of a few key industrial locations, like what we observe in the automobile industry; with Japan, Germany and United
States being the three major auto industry locations. These are often referred to as global clusters.
Global clusters have the highest concentration of
firms and control the full range of industrial knowledge required within the given industry. This is also
where major R&D and new product development
takes place.
The second tier clusters can be found in runnerup auto manufacturing countries like Korea, China
and India. These are new industrial clusters or regional clusters challenging the existing global clusters. Many previously strong regional actors in the
auto industry (e.g., Skoda, Saab and Volvo) were
January 2011
first taken over by the major global players (e.g.,
VW, GM and Ford). Recently, new auto actors from
emerging economies are taking over old car manufacturers, e.g., Tata taking over Jaguar and Volvo
getting new Chinese owners.
The third tier of automobile clusters has a concentration of more specialized suppliers and service providers to the auto industry, such as the auto
parts manufacturers of many European and Asian
countries. These specialized clusters are built
around more specialized industrial knowledge, and
the supplier clusters are highly dependent on their
global customers. The vertical inter-organizational
relations are governed by strong contractual arrangements tying these clusters to the main actors
in the global clusters.
The fourth tier of automobile clusters simply
consists of standalone auto assembly or auto parts
plants located in countries with favorable factor
conditions, such as Brazil, Mexico, Poland and
Thailand. We may refer to these clusters as transplant clusters. In transplant clusters, industrial
knowledge generation is limited, and transplant
clusters tend to be local in nature. Most of the foreign direct investments in emerging economies are
of this kind.
Finally, there are raw material producers that
could be anywhere where factor conditions are favorable. Sometimes, these producers form commodity clusters, as we see in many countries that
are strong in natural resource industries.
In this paper, I will study the industrial cluster
structure in knowledge-intensive industries. Examples of such industries are life sciences, biotech, information and communication technology, although
most industries today are highly knowledge-intensive in some sense or another. Thus, the argument
in this paper is that studies of knowledge-intensive
industries are transferable to many other industries, such as the maritime industry, which is my
empirical focus in the second part of the article.
Finally, in applying these concepts to the maritime industry, I will introduce the concept of global
knowledge hubs. Thus, the third industrial paradigm discussed is industries as global knowledge
hubs. This concept has substantial implications for
January 2011
industrial development and suggests more radical
knowledge-based industrial policies.
The Emergence Of Knowledge Hubs
Some of the most famous industrial clusters can be
found in knowledge-intensive industries. If we study
the development of Silicon Valley (Saxenian 1994),
it started with the development of the semi-conductor industry and computer manufacturing. Key
actors at this stage were companies like Fairchild
and Intel in semi-conductors, and Hewlett Packard
and Apple in computers. Over time, the dynamics
changed into communication technology, producing
such key players as Cisco in network technology,
and Yahoo and Google in internet search technology. Behind the rapid development of the IT industry in Silicon Valley was leading edge research and
development, most notable at Stanford University
and related R&D facilities.
What characterized the Silicon Valley IT cluster was the high amount of entrepreneurship resulting in thousands of startup firms within any
possible knowledge niche of the industry. The
transition of startups into commercial successful
firms was fueled by a dynamic venture capital industry, providing competent capital to new entrepreneurs. Venture capitalists speeded up the selection processes, both in terms of killing ventures
with low commercial potential and by providing
ample funding to ventures with high growth commercial potential. Entrepreneurs, who were often
young university graduates or former employees
of some of the major IT firms in the Valley, had
the opportunities to transform their knowledge investments into stocks or cash, and many became
serial entrepreneurs, setting up new IT, software
or service companies in many locations around the
world. The Bangalore IT cluster in India is a well
known example, and a company such as Infosys
has its roots in Silicon Valley.
Empirical studies of knowledge-intensive clusters like Silicon Valley reveal dense networks of
knowledge linkages and rapid transfer of knowledge workers among the key actors in the cluster
65
(Saxenian 1994, Stuart 2000). The major universities (Stanford, Berkeley and San Jose) and
their associated research labs became major linking pins in the knowledge network. The important
role of public research organizations should be
noted (Whittington et al., 2008). New technology
and new commercial concepts came out of close
cooperation between universities, labs and major
IT companies that were all located close to each
other. The waterholes in the Silicon Valley became
famous for rapid exchange of new ideas. The driving force was innovation competition, and the rewards for commercial success were substantial. It
all peaked during the dot.com era, but the Silicon
Valley still kept up its reputation as one of the
global new venture hubs, not only in information
and communication technology, but in many new
knowledge industries, including life sciences and
biotech that we now turn to.
An even more amazing story of the rapid growth
of a new knowledge-intensive industry is the emergence of the Boston life science industry. The pattern of development in Boston is even clearer than
in the Silicon Valley case, and recently, excellent
research data has been presented for the development of the Boston and San Francisco life science
industries (Whittington et al. 2008).
The new life science industry developed from
scientific advances in biotechnology, and the development took place at the three major research
universities in Boston: MIT, Harvard and Boston
University with their associated university hospitals. As these universities were international leaders in life sciences, educating the most capable,
new knowledge workers, doctors and scientists,
major commercial actors in life science, including
major biotech and pharmaceutical companies from
around the world, set up their labs and test facilities in the Boston area. The idea was to be close to
the rapid scientific development and to be among
the early adaptors of new technologies into commercial products and services. At the same time,
many entrepreneurs trained in life sciences saw
opportunities for themselves, and a large wave of
biotech startups emerged. Again, the driver was
the venture capital industry. This industry does not
66
have its main hub in New York like the rest of the
US financial industry, and is more concentrated in
cities like San Francisco, Boston and San Diego.
These cities also happen to have the highest concentration of firms in the new knowledge-intensive
industries, such as life sciences. Recently, Genome
Technology (2008) placed Boston/Cambridge, MA
way ahead of all other biotech locations in the world,
followed by the San Francisco Bay area and San Diego.
The recent empirical study of the development
of the Boston and San Francisco life science industries, 1988-1999 referred to above, not only
demonstrates the importance of critical mass of
co-located knowledge companies, but it shows the
importance of close linkages between the same
knowledge actors (Whittington et al 2008). At the
early stage of development of the life science cluster in Boston, 1988, 114 organizations had 201
observed formal ties, while in the more mature
stage of cluster development, 1999, 740 organizations had 1559 observed formal ties. Formal
ties include research partnerships, licensing agreements, financial investments and manufacturing
and marketing contracts. Of the 740 organizations,
212 were dedicated biotechnology firms, 96 were
public research organizations (which also include
universities, university research hospitals and independent research institutes), and 240 were capital venture firms. Public R&D institutions play a
pivotal role in knowledge generation, while venture
capital firms play a similar pivotal role in venture
commercialization. In sum, these actors not only
form a strong industrial cluster, they form a global
knowledge hub.
What characterizes a global knowledge hub
is a strong core of public research organizations
(PROs), mainly universities and independent research institutes, interacting closely with the R&D
units of major commercial actors in the industry.
In the biotech industry, this means the labs and development units of dedicated biotechnology firms
(DBFs) and the many pharmaceutical, chemical
and healthcare companies. When a knowledge
hub reaches a certain critical mass, we see that
most of the global actors in the industry establish
January 2011
centers of excellence in the same geographical location. This is done to be an integral part of the
advanced learning and innovation milieu, taking
advantage of learning by interaction and diffusion
of knowledge (Sorensen & Fleming 2004), and of
learning by hiring (Song, Almeida & Wu 2003). As
the knowledge hub also contains major world-class
universities offering specialized graduate programs
and high quality doctoral programs, young talents
from around the world seek the same knowledge
hubs. This again creates a dynamic, high-talent labor market that gives rise to network externalities
that benefit all the actors in the hub.
The second layer of firms in a global knowledge
hub consists of a competent venture capital industry that increases commercialization opportunities
by funding ideas that come out of the universities
and labs at the same location. The venture capital
industry covers all stages of the innovation and entrepreneurship process—from early stage business
angles and seed capital firms, to hard core venture
capital firms going in at various stages of development before the most successful ventures reach the
IPO stage and are quoted on the stock exchange.
There is, of course, extensive takeover activity taking place during the venturing process, where large
companies take over promising startups or spinoffs.
In both cases, new ideas are turned into commercial success, giving entrepreneurs strong economic
incentives to continue to innovate. The heroes are
topnotch scientists and serial entrepreneurs that
become rich in the process.
The third layer in global knowledge hubs consists of the large array of technological and commercial actors that turn science and technology
into products and services. This is where large
numbers of small and medium-sized firms in the
knowledge industry grow up, and this is where
large multinationals, like Genentech and Novartis,
try to play dominating roles. Mergers and acquisitions are frequent and sometimes major in nature,
e.g., Japanese Takeda Pharmaceuticals taking over
Cambridge-based Millennium Pharmaceuticals in
2007 for $8.8 billion.
As in regular industrial clusters, there are numerous suppliers, intermediaries and service providers
January 2011
that have an active supporting role in the knowledge
hub. Actually, such firms, in particular, brokers and
consultants, are very important in knowledge diffusion. This is the same network mechanism that is vital in open innovation (Chesbrough 2003)—creating
social capital that facilitates innovation and commercialization. Global knowledge hubs are different
from research hubs where universities and R&D labs
exist in splendid isolation from business and venture
capital demands. In knowledge hubs, investors constantly chase ideas and vice versa.
Within global knowledge hubs, there is a small
world of scientists and commercial actors (Fleming
et al 2007) that are world experts within their areas of specialization. Small worlds are characterized by intensive information exchange and shared
values, reducing communication barriers to almost
zero, although the membership of small worlds is
often culturally diverse. The two overriding values
are the drive to succeed scientifically and the drive
to succeed commercially.
Another important feature of global knowledge
hubs is that they typically consist of several small
worlds that are in intense internal rivalry. The scientific rivalry between Harvard and MIT is well known,
and in the biotech case, key biotech firms tend to belong to either one of the two spheres. Under such
competitive circumstances, there is no time to rest on
your laurels, and innovation competition is fierce.
What we find in studying knowledge hubs, is
that governmental agencies may also play an important role, partly in terms of funding various
R&D initiatives and also by setting industry standards and new regulatory regimes. In the Boston
biotech hub, 24 different governmental agencies
had located there in 1999, and they were all active members of the knowledge hub. Thus, the role
of private-public partnerships in innovation milieus
seems to be a major driver, although the roles may
differ across nations.
The global knowledge hub of the biotech industry in Boston is beautifully illustrated by cluster
map in colors developed by Whittington (2007)
in her doctoral research. Here, the distribution
of the main components in Boston biotech inventions, 1976–2002, is illustrated by mapping the
67
Fig 1: Boston Biotech Knowledge Hub Linkages
Distribution of Scientific Clusters
Main Component, Boston
Inventors 1976-2002
Color Legend
Reds: University (21%)All other
colors: Biotech (38%)Light
Grey: PRO (26%)Black: Crosssector (16%)
formal inter-organizational ties between universities (21%), biotech firms (38%), public research
organizations (26%) and cross-sector (16%). The
number of actors and their formal ties is incredibly
high. In addition, there are many informal linkages
and networks that are hard to capture in this type
of quantitative network research.
In order to capture the structure of a global
knowledge hub like the Boston life science cluster, I would place the universities and the public
research institutions at the core of the hub. In the
Boston biotech case, you may well put the four
“Research One” universities in Boston in the middle (Harvard, MIT , Boston and Tufts), along with
research hospitals like Massachusetts General and
research institutes like Dana Farber Cancer Center
and Whitehead Institute of Biomedical Research.
Its geographical center is at Kendall Square, Cambridge, Mass which is also the home of MIT. Recently, major international pharmaceutical firms
like Pfizer and Novartis have located their R&D
facilities at Kendall Square.
The knowledge plus orientation of American research universities (Mowery et al. 2004) include
early movement of university graduates into com68
mercial firms, consulting relationships between
faculty and companies, licensing of university technologies, industry gifts supporting university research and student training, faculty entrepreneurship founding new companies, faculty involvement
on scientific advisory boards, and formal contractual partnerships to pursue joint R&D, product or
prototype development and clinical tests.
If we look at the innovation output in terms of
patents in the biotech cluster in Boston, two-thirds
of the 900 biotech patents registered in Boston
between 1976 and 1998 came from a university,
while one-thirds came form biotech companies. It
is fair to say that there are seamless relationships
between universities and private business. The result is that much of published academic research
now comes out of the R&D units of corporations,
while many new commercial ventures come out
of universities. This forms the core of the global
knowledge hubs.
What makes the core of R&D and innovation so
successful, in global knowledge hubs like Boston, is
the network of venture capital firms and investors
surrounding the universities and public research
institutions. This is a substantial economic force
January 2011
funding the majority of the commercialization activity in the knowledge hub, and offering powerful
incentives to those who succeed by taking an invention or innovation into the commercial stages.
Venture capital markets discount future earnings
into the present, thus offering venture capital to
startup firms whose earnings are uncertain future
prospects. Only major corporations are able to do
the same, e.g., by corporate funding of internal
ventures. The role of government money is limited,
except in the funding of basic research and in large
defense contracts.
The next layer of actors in global knowledge
hubs is the whole array of commercial firms,
covering the various stages of development, testing, manufacturing, marketing and services that
constitute the majority of value creation in most
industries. In knowledge-intensive industries, the
role of manufacturing is much more limited than in
more traditional industries, while product development, marketing and service represent the substanFig 2: Boston Biotech Global Knowledge Hub
Structure
PRO
VC
PRO
DBF
PHAR
VC
HCO
DBF
SSS
PHAR
REG
HCO
SSS
REG
Legend
PRO
Public Research Organizations
VC
Venture Capital
Legend
DBF Public
Dedicated
Firms
PRO
ResearchBiotech
Organizations
VC
Capital
PHAR Venture
Pharmaceutical
Industry
DBF
Firms
HCO Dedicated
HealthBiotech
Care Organizations
PHAR Pharmaceutical Industry
SSS Health
Specialized
Supporting
HCO
Care Organizations
ServicesSupporting
SSS
Specialized
IFC
Institutions for Collaboration
Services
IFC
for Collaboration
REG Institutions
Regulatory
Regime
REG
Regulatory Regime
January 2011
IFC
IFC
tial part of value creation. The focus is on R&D,
commercialization and marketing. The analytical
model is one of value shops or value networks (Stabell & Fjeldstad 1998). Finally, there are numerous
suppliers and service providers serving the knowledge firms.
The structure of the global knowledge hub in the
biotech industry in Boston can be illustrated as in
Figure 2.
At the core of the global knowledge hub are the
PROs such as universities and private R&D institutions. These interact closely with venture capital
and other competent investors that know the industry well.
The knowledge-capital core is surrounded by a
number of DBFs that breed on the ideas developed
at the universities, working closely not only with
PROs, but also with large multinationals from the
pharmaceutical and chemical industries (PHAR).
The development of an efficient biotech knowledge hub also requires well functioning healthcare
organizations (HCO), which in this sector represents both a resource and an important market.
The role of university research hospitals is critical.
Finally, there is a large fabric of specialized and
supporting knowledge services (SSS) serving and
developing the knowledge hub. This is the layer
typically creating most jobs.
Network externalities can also be better realized if effective institutions for collaboration (IFCs)
exist. These organizations also have a branding
role for the global knowledge hub. Finally, the role
of new standards and effective government regulations (REG) is critical in turning emerging industries into growth industries.
If we compare the knowledge hub concept with
traditional industrial cluster maps, we can note
the inversion from having the major manufacturing companies at the core, to having the research
and innovation at the core. The basic premise is
that new business emerges from knowledge and
market needs. This also changes the role of capital
and investors whose role is to match the two. The
knowledge dynamics primarily come from R&D
and small knowledge based firms rather than from
manufacturing and large multinationals. Universi69
ties and R&D institutes become industrial actors
that are sometimes even more important than major business corporations. Thus, close knowledge
interactions between academia and private business are vital in any knowledge hub.
Global Maritime Knowledge Hubs
The maritime industry has been extensively studied
in industrial cluster terms (Reve et al. 1992, 2001,
Jakobsen 2003, 2004). On the one hand, the maritime industry, such as ship building and shipping,
represents relative traditional industries, not typically thought of as knowledge-intensive industries.
On the other hand, a large part of the maritime industry runs purely on the knowledge-serving global
transportation markets. Shipping has no other resource base than the people owning and operating
the ships. Ship building in high-cost countries can
only survive if it is able to innovate technologically.
The remaining parts of the maritime cluster are
technical and commercial services, from the most
advanced knowledge services to simple operational
support.
The most complete maritime clusters can be
found in Norway, Japan and China, but Greece
(shipping), Korea (ship building) and Singapore
(port) are also strong maritime clusters, along with
several other EU countries.
The Norwegian maritime cluster can be illustrated by Figure 3 (cf., Reve et al. 2001:196).
The core of the Norwegian maritime cluster is
the shipping companies providing seaborne transportation services worldwide. The Norwegian maritime cluster can be traced back to about a 1000
years back when the Vikings ruled the Northern
shores. The Norwegian maritime cluster has been
highly innovative, particularly when it comes to
new ship designs, advanced ship equipment, maritime IT and new commercial concepts. Interestingly enough, ship owners from a country with
less than 1/1000 of the world population control
about 1/10 of world shipping. Norway is also home
to some of the largest global actors in shipping finance, ship brokers, marine insurance, ship classi70
fication services and maritime law. The North Sea
offshore oil industry has developed from much of
the same maritime knowledge base, making Norwegian companies world leading in new advanced
sectors such as offshore oil drilling, floating oil and
gas production and subsea technology. Thus, the
Norwegian maritime cluster is becoming a knowledge-intensive industry, thriving on innovation and
with the ability to commercialize maritime activities on a global basis.
Given the large concentration of maritime actors in Norway, its knowledge intensity and the
Fig 3: The Norwegian Maritime Cluster
Offshore
oil and gas
industry
Maritim
policies
Ship
design
Maritime
education
Efficient
fisheries
Maritime
R&D
Shipping
finance
Specialized
ship yards
SHIPPING
Advanced
ship equipment
Logistics
systems
Effective
Ports and
terminals
Maritime
IT
Shipping
brokers
Shipping
management
Shipping
insurance
Shipping
classification
services
UPGRADING
Human
resource
services
Environmental
standards
INTERNATIONALIZATION
dense network of interactions within the industry,
the Norwegian maritime cluster (cf. Figure 3) can
be re-conceptualized as a global knowledge hub.
The maritime knowledge hub model, as it applies
to the Norwegian maritime cluster, is presented in
Figure 4.
At the core of the knowledge hub is research and
innovation. This not only includes universities and
public research organizations, but also to a large
extent what takes place of R&D among the commercial actors in the industry. Much of this R&D
activity takes place outside the labs, in interactions
among the various maritime actors, customers,
suppliers and consultants.
Unlike the Boston and Silicon Valley cases, the
next circle in the knowledge hub model does not
mainly consist of venture capital, but includes a
host of private capital and investors, ranging from
risk capitalists, private equity and large commercial investors with a long history of investments
January 2011
Fig 4: The Norwegian Maritime Knowledge Hub
S ors
NT rat t
LE pe en
TA w/O gem s
re ana D
• C • M • Ph
Shipping
Investors
Ship
industry
Venture capital
Maritime
services
in the shipping industry. The ability to fund large
maritime projects, e.g., in the global oil and gas rig
industry, is astounding.
In the third circle of the knowledge hub model
we find the critical mass of maritime actors that
make up the majority of the maritime industry,
such as shipping, ship industry, offshore industry
and maritime services. These four sectors have been
described in detail in the maritime cluster studies,
and the main challenge is to find out whether they
interact closely enough to create network externalities that are so important to dynamic industrial
clusters (Orvedal 2002).
Finally, I have added four external forces that
will shape the maritime industry in the years to
come. These include the global battle for talent
and technology (Florida 2005), and the overall
forces of economics and environment. The economics have to do with world trade and global transportation markets, which in turn closely depend on
upturns and downturns in the world economy. The
recent global financial crisis illustrates the point.
Oil prices play a particularly strong role, especially
for a country like Norway. which is also a major oil
and gas producer. Environment has more and more
to do with climate, primarily the emission of CO2,
which of course, is also produced by carbon energy
usage in the maritime industry.
The knowledge hub model applied to the Norwegian maritime industry, has two main purposes.
January 2011
T
EN
M
O 2
IR O n
V • C lutio
EN
o l SR
•P •C
S
IC e
d
OM ra t s
N al t arke cs
O
b
ti
EC Glo al m poli
• lob al
b
•G lo
•G
Research
&
Innovation
First, it can serve as a descriptive model to guide
empirical research of the
Y
maritime industry, e.g., how
G
O
OL
strong is the research and inHN ICT ics
C
• ist y
TE
o g rg
novation core, and how close
• L Ene
•
do the various maritime actors interact. In particular, it
Offshore
is important to find out how
industry
closely the maritime industry interacts with PROs, and
how well academia meets the
future knowledge needs of
the maritime industry.
Second, the maritime
knowledge hub model is a
normative model that can guide industrial action
and industrial policy toward the maritime cluster.
Thus, in order for Norway to succeed as a leading maritime nation when facing keen competition
from aggressive maritime nations in Asia, Norway
needs to strengthen its strategic core of maritime
knowledge generation and dissemination. This
means strengthening maritime R&D, maritime education, and maritime innovation milieus, including investing in leading edge maritime knowledge
at universities. It also includes plans for creating
the largest and most advanced research and testing
facilities for ocean technology, referred to as the
Ocean Space Center.
In fact, the concept of Norway as a global
maritime knowledge hub was pioneered by Oslo
Maritime Network in an effort to strengthen the
attractiveness of Oslo as a location for global
shipping operations. In May 2008, the Global
Maritime Knowledge Hub Initiative was launched
in order to make Norway a global knowledge hub
for maritime research, innovation and education
at all levels.
Initially, the Norwegian maritime industry funded 10 new maritime professorships (or research
chairs) at Norwegian University of Science and
Technology (NTNU) in Trondheim and BI Norwegian School of Management in Oslo. NTNU already
had a Center of Excellence in maritime research—
Centre for Ships and Ocean Structures (CESCO),
71
Although Singapore wants to become one of the
high-tech players of Asia, focusing on such knowledge-based industries as IT and biotech, Minister
Mentor Lee Kuan Yew recently put things more in
perspective, “Biotechnology and pharmaceuticals
are ‘sexy and glamorous’ industries, but the maritime sector is basic to Singapore’s development.
Thus, Singapore wants to move from being a major
hub port to becoming an international maritime
center with a full suite of services.” (The Straits
Times, Sep. 26, 2007).
The international maritime center idea corresponds closely to a global maritime cluster, but
it has relatively little emphasis on the knowledge
content required in order to succeed. Thus, it is
also possible to re-conceptualize the international
maritime center of Singapore to a global maritime
knowledge hub, cf., Figure 5. The figure comes
out of the work of the 3rd Maritime R&D Advisory Panel of Maritime & Port Authority (MPA) of
Singapore, where the author was one of the international members.
Research, innovation and education have been
placed at the core of the global maritime knowledge hub of Singapore, surrounded by a network
of venture capital and competent investors. Again,
there are four major industrial sectors constituting
the majority of the corporate content of the mari-
while BI had developed a Global Executive MBA
program for shipping, offshore and finance, in cooperation with Nanyang Technological University
(NTU) in Singapore.
Two years later (in April 2010), there are close
to 20 new privately-funded maritime professorships
in place at four different universities and maritime
colleges in Norway, and a similar number of professorships and maritime research centers are under
negotiations. Proposals for a large national research
program, called Maritime 21, have been put forward by the Norwegian maritime industry, focusing
on demanding maritime operations, ocean technology, environmental technology and arctic technology,
as well as on new business models for the maritime
industry. Plans and designs for the Ocean Space
Center in Trondheim have materialized.
SINGAPORE
COMPARED
AND
NORWAY
Singapore has much of the same role in the maritime industry in Asia that Norway has in Europe,
although its strategic base is different. Singapore
derives much of its maritime power from its port,
strategically located on the major sea route between
East Asia, Middle East and Europe. In addition,
Singapore has become a major location for shipping and maritime service companies, including many Norwegian Fig 5: The Singaporean Maritime Knowledge Hub
72
ks
or
Y
OG
OL
HN
C
TE
AL Y
B M
LO O
G ON
C
E
tw
Ne
PORT
TA
LE
NT
GLOBAL
ENVIRONMENT
A Global Maritime Knowledge Hub shall propel the
Singapore Maritime Cluster
VENTURE
CAPITAL
SHIPPING
RESEARCH
INNOVATION
EDUCATION
INVESTORS
IN
CE
NT
IV
ES
OFFSHORE
& MARINE
ENGINEERING
MARITIME
SERVICES
s
I TY
ie
RS
lic
VE
I
D
Po
AL S
OBTIC
GLOLI
P
companies. Singapore also has
a competitive offshore industry,
with leading shipbuilding companies specializing in drilling rigs
and floating production vessels.
What characterizes Singapore
is its aggressive industrial policy
toward attracting international
knowledge-based companies, particularly in the maritime industry.
Singapore has concentrated its
maritime policies, including ownership and operations of its ports,
into one single government agency,
Maritime & Port Authority (MPA)
of Singapore.
A L ON
OB TI
GL U L A
P
PO
January 2011
time knowledge hub. In Singapore these sectors
are port, shipping, offshore & marine engineering
and maritime services. It all started with the strategic location at the Malacca Strait, and it is fair
to say that the port is still the major driver of the
Singapore maritime industry. More and more shipping companies are placing their global or Asian
headquarters in Singapore due to favorable tax
rates and a good infrastructure. This in turn has
lead to an influx of many maritime service companies. Offshore and marine engineering consists
of two major ship builders focusing on offshore
structures, expanding into global offshore markets.
Singapore is also a major port for bunkering and
repairs, and there are also major oil terminals and
a petrochemical industry that are important for the
maritime industry.
Singapore lags behind Norway, Japan, Korea
and China when it comes to maritime R&D, but
the two major universities, Nanyang Technological
University (NTU) and National University of Singapore (NUS) have started activities in maritime
research and development, as well as launching
several maritime educational programs, initiated
by MPA. Both in maritime research and maritime
education, MPA has been instrumental in setting
up strategic alliances with Norway. MPA has established a Maritime R&D Fund of S$ 400 million,
and A*Star (Singapore’s Research Foundation)
has initiated R&D programs, building international
R&D bridges, e.g. with Norway.
Knowledge-Based Industrial Development Policies
Global knowledge hubs are rare, and even the more
knowledge-intensive industries have room for more
than two or three global knowledge hubs. Boston
and San Francisco Bay are examples in the biotech industry. Thus, becoming a global knowledge
hub for a specific industry is more a long term goal
than a reality for most regions.
What is common is to find more specialized
global knowledge hubs. In the maritime industry,
Norway, Singapore, Japan and China are candiJanuary 2011
dates to become global maritime knowledge hubs.
Greece already has such a position when it comes
to shipping, while Korea has a strong position in
ship building. London has a global knowledge hub
position when it comes to the financial aspects
of shipping, while Rotterdam and Hamburg have
strong maritime hub positions as ports and maritime services.
The same type of specialization can be observed
within countries. In Norway, shipping is concentrated in Oslo and Bergen, while the ship industry (ship
design, shipbuilding and ship equipment) is mainly
located on the northwestern coastline of Norway.
What distinguished industrial clusters from global
knowledge hubs is the reliance on research and
development, its emphasis on innovation and commercialization, and its global reach.
Most ship yards around the world do little or no
research and development. They simply build according to spec, and the competitive edge is to be
the cheapest. The more advanced end of the shipbuilding industry invest in long term technological innovation, working closely with major clients,
suppliers and public research organizations. The
knowledge intensity can be measured by the knowledge composition of the workforce (percent of
workforce with PhD and MSc), the relative amount
spent for R&D (as percent of sales), the number
of knowledge alliances, the number of patents obtained, etc. These measures can be calculated for
individual companies, but more importantly such
measures apply to the industrial cluster in a given
region.
The underlying rationale is that industries in
regions compete not only in terms of productivity and low cost, but also in terms of innovation
and knowledge content. For high cost locations
like Norway and Singapore in the maritime industry, competing on innovation is simply a must.
This can be done by attracting a critical mass of
maritime actors that spend substantial amounts
of resources on R&D and who interact closely to
create knowledge externalities that benefit all the
actors in the knowledge hub. The battle is often
times over the location of centers of excellence
that the multinationals set up in several countries.
73
Such global knowledge hubs also attract the best
talents, both in the educational phase and in the
industrial practice phase, creating a highly attractive labor market and large opportunities for
entrepreneurship. This gives a special role for the
research universities, but also for more vocational
and technical colleges, educating the specialized
workforce needed in a particular industry. More
and more such knowledge hubs are able to attract
talent and companies from many countries, sometimes even globally. A key requirement again is
the availability of competent risk capital.
The implications of the knowledge hub model for
industrial policies have not been fully spelt out yet.
What we see is that common tax subsidies are replaced by more focused knowledge-based policies.
Examples include developing world class universities, specialized research institutes, labs and test
facilities, along with the hard and soft infrastructure required to attract knowledge-based companies and highly educated staff on a global scale.
What governments need to consider, are stronger
incentives for R&D and innovation, better knowledge infrastructure, easier immigration rules, and
improved venture capital markets. Often it is a
matter of making it simpler to locate companies
and easier to do business. This is not simply a question of policies and regulations, but it also has a
strong cultural component. Florida (2005) refers
to this as tolerance and acceptance for diversity
and a multi-cultural population. Many totalitarian countries, e.g., in the Middle East, have serious problems in meeting the cultural dimensions of
knowledge development. Stability, security, a clean
environment and good quality of life can also give a
region a competitive edge.
It is not new to reframe industrial policy into
innovation policy (e.g., OECD 2008). The knowledge hub model, however, puts the main emphasis
on knowledge policies, putting schools, universities,
R&D, innovation and entrepreneurship at the center stage, rather than considering these knowledge
functions as support services to corporations. This
is very clear when you study new and emerging
knowledge industries, such as biotech and nanotech industries. These industries were created in
74
research labs, and new commercial actors emerged
from the new knowledge base. On the other hand,
this was also how most other industries were originally created. Take a traditional and mature industry like the fertilizer industry and the establishment of Norsk Hydro, now Yara. Norsk Hydro was
established based on a new technology invented
by a research scientist, William Birkeland, who
convinced a venture capitalist, Sam Eyde, to put
money behind the idea of taking nitrogen out of the
air by using electricity generated by a water fall at
Rjukan, Norway. Today, Yara is the world’s largest
fertilizer producer, manufacturing and operating
globally.
One of the main theses in this paper is that industrial development mainly comes from innovative
industrial environments, here called global knowledge hubs, where specialized and basic knowledge
meets demanding markets with a drive to commercialize. Universities, public research organizations,
venture capital and competent investors have particularly critical roles in such knowledge hubs.
Global knowledge hubs are path dependent and
culturally bound, but there are also examples of how
new knowledge hubs have been created by clusterbased policies focusing knowledge and network development. The catalogue of cluster-based policies
needed to stimulate the growth of global knowledge
hubs is still not complete, and more work needs to
be done to understand all the mechanisms inherent
in knowledge-based industrial development.
Another thesis in this paper is that the development of knowledge-intensive industries is basically similar to the development of other industries.
Such a thesis asks for new comparative research.
Based on the premise that knowledge forces are
similar across industries, the maritime industry
has been analyzed in largely the same terms as the
biotech industry. In both industries, we find global knowledge hubs that take lead roles in shaping
these industries. Boston and San Francisco Bay
have such roles in the biotech industry, while Norway and Singapore may well take similar global
knowledge hub roles in the maritime industry. The
major common competitor in the maritime industry is China, as in so many other industries. Used
January 2011
normatively, the global knowledge hub model
points to knowledge-based industrial policies that
are different from what is typically implemented
in industrial development.
Conclusion
This paper argues for a new knowledge-based paradigm for understanding industrial development.
Rather than understanding the firm as manufacturing or seeing firms as part of industrial clusters, industries can be analyzed as knowledge hubs. Global
knowledge hubs have world class universities and
public research organizations at their core, and
are in close interaction with venture capitalists and
competent investors. From this knowledge core, extensive industrial development can take place, as illustrated by the development of the Boston biotech
industry.
Based on the premise that most industries are
becoming knowledge-based, and that knowledge
dynamics are basically the same across industries,
the global knowledge hub model was applied to the
Norwegian and Singaporean maritime industry.
Both countries are in a strategic position to shape
the future development of the maritime industry,
but this requires substantial knowledge investments and closer interactions between the actors
in the industry and between private industry and
academia.
The global knowledge hub model can be applied
both as a descriptive model of industrial development or as a normative model for industrial development policies. Both approaches ask for new
comparative empirical research.
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Management Science, 49: 351-365
20Sorensen, O. & L. Fleming (2004), “Science
And The Diffusion Of Knowledge,” Research
Policy, 33: 1615-1634
21Stabell, C.B. & Ø. Fjeldstad (1998), “Configuring Value For Competitive Advantage: On
Chains, Shops And Networks”, Strategic Management Journal, 19: 413-437
22Stern, L.W. & T. Reve (1980). “Distibution
Channels As Political Economies: A Framework
For Comparative Analysis,” Journal Of Marketing, 43: 52-64
23Stuart, T.E. (2000), “Interorganizational Alli-
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ances And The Performance Of Firms: A Study
Of Growth And Innovation Rates In A HighTechnology Industry,” Strategic Management
Journal, 21: 791-811
24The Straits Times (2007), Article, Sep. 26,
2007, P. 3
25Whittington, Kjersten Bunker (2007), “Employment Sectors As Opportunity Structures:
The Effects Of Location On Male And Female
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University, Stanford, Ca
26Whittington, Kjersten Bunker, Jason OwenSmith & Walter W. Powell (2008), “Networks,
Propinquity And Innovation In KnowledgeIntensive Industries”, Administrative Science
Quarterly, (Forthcoming)
January 2011
From the India City
Competitiveness
Report 2010
January 2011
77
Cities, Competitiveness, and Economic Development:
Untangling the Linkages
Dr. Christian Ketels, member of the Harvard Business School faculty at Professor Michael E. Porter’s Institute for Strategy and Competitiveness and Member of the Advisory Board, Institute for
Competitiveness emphasizes the need for Indian cities to have a clear competitive agenda in order
for the nation to achieve higher competitiveness.
M
ore advanced economies are more urbanized economies. As the interest in economic geography
has increased, this empirical fact has been more widely acknowledged. The 2010 World Development Report provided significant evidence on how cities and different levels of economic
activity across space therefore have to become a more important aspect of the policy dialogue on development.
In less-developed economies, the growth of cities and the increasing level of urbanization are largely a
reflection of the widespread weaknesses that exist in economic conditions. With infrastructure, education,
and many other aspects of competitiveness weakly developed in rural regions, cities tend to be the only
places where companies and individuals find opportunities for successful economic activity. The growth of
cities is thus more a reflection of the development challenges that exist elsewhere in these economies, not
so much a sign of true improvements. In fact, the rise of mega-cities in many developing economies creates many problems of their own, as these huge agglomerations struggle to provide public services to an
exploding number of citizens. This is why in developing economies the rise of cities is seen as an inevitable
part of development, but also as a policy challenge—it creates the need for policies that enable cities to
cope with the massive demands that are placed on them. It also creates the need for policies that enable
citizens in rural regions to develop their own economic opportunities. The challenge is to avoid a political
schism between metropolitan and rural regions that would threaten to halt urbanization and thus hurt
development.
In advanced economies, cities are able to play a radically different role. With both rural and metropolitan regions providing at least the basic level of competitiveness, the choice of where to locate specific
economic activities becomes an issue of relative productivity and cost levels. This allows cities to attract
activities that are usually more skill-intensive and where there are strong local knowledge spill-overs while
rural regions attract more capital-intensive or labor-cost sensitive activities in standardized production
processes. Cities turn out to be the places where different types of proximity benefits can reinforce each
other—specialization in specific clusters can occur as well as cross-cluster agglomeration of general
types of activities. This mixture is especially important for innovation. High-skilled people are attracted
to places that provide variety and interesting contrasts. Ideas are born where different intellectual traditions and approaches meet. But to evaluate whether these ideas have any market potential, and to then
translate them into profitable products and services, a specialized cluster of related and supporting activities is needed.
From the competitiveness perspective, the policy imperative for cities as well as for rural regions is
essentially the same, independent of the stage of economic development—develop the competitiveness of
the local economy in order to achieve higher levels of company productivity and thus support higher levels
of prosperity. The specifics steps that are needed, however, differ significantly based on the type of locality
and the level of economic sophistication it has reached. What is true in both more- and less-developed
economies is the need to focus on the specific role that an individual region can play. This requires for
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cities and for the rural regions around them to cooperate closely. It is crucial to enable less-advanced
manufacturing activities to be placed in rural regions in the vicinity of the cities, especially in developing
economies. The city can provide the advanced services and management functions, the rural regions the
land and lower cost labor. This division of labor can relief pressure on the city’s infrastructure and create
economic opportunities outside of the large agglomerations.
In the past, cities—also in India—have tried to manage their growth by creating artificial limits. In
many cases, this approach has failed and made living conditions worse. Mumbai, for example, limits the
height of buildings, which has reduced space use and forced people to live farther and farther away from
the city center. This has created increasing pressure on an already struggling transportation system. Rent
control has further reduced the incentives for land owners to re-invest in housing stock. Mumbai has
continued to grow nevertheless, but the city is less efficient in providing even basic services in terms of
housing and infrastructure than it could be. What is needed is a different policy approach that focuses on
better public services and land use inside the city, while creating real economic opportunities outside of
the city as well. There are no magic solutions. But there is a need to move away from the failed approach
of dealing only with the consequences of increasing urbanization. Instead, there needs to be a competitiveness-oriented policy approach that changes the economic fundamentals of where people live and work.
Many of the policy choices that have to be made in order to enable a balanced development of cities
and rural regions require the action of all levels of government—national, state and local. But there
is an increasing realization that cities are not helpless, and in fact control many policy tools in land
planning, infrastructure investments, and the implementation of general policies set at higher levels of
geography. Cities need to have a clear competitiveness agenda. Without cities that push for competitiveness, it is hard to see how a nation like India can make any sustained progress in its overall quest
for higher competitiveness.
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Growing with Clusters
Dr. Amit Kapoor, Professor of Strategy and Industrial Economics, Management Development Institute (MDI) and Honorary Chairman, Institute for Competitiveness explains how clusters can transform and add value to the competitive landscape of a city.
C
ities and townships are the vantage point for the growth and development of states. The World
Bank has released a status report “Reshaping Economic Geography” on the world economic regions and emphasized on urbanization, territorial development and international integration for a
country to grow economically. Thus far, India has focused on creating industrialization, but its accidental
confluence with urbanization and clusters has provided the governance with a tool for enabling industrialization in lieu of creating it. Close to 36% of the population in Maharashtra and 45% in Goa live in urban
areas and their annual growth rates are 9 and 10%, respectively. Urban centers allow for concentrated
economic activity and specialization and hence, cluster formation comes more naturally. The focus of this
article is to highlight the importance of clusters and drive location advantages to convert to economic
benefits.
Sriperumbudur, a lackluster village near Chennai with no history of industrialization is the largest
electronic hub in India. The Alappuzha coir cluster, the leather cluster in Chennai, the diamond industry
in Surat, the petroleum cluster in Bombay, the cotton yarn industry in Ahmedabad and numerous other
examples indicate the prerequisite presence of a cluster for the industry and the region to prosper. The
diamond cluster contributes 17.22% of the world export of non-industrial diamonds and iron ore and concentrates contribute 14.20%. Close to 65% of India’s exports stem from clusters. Industrialization could
never reach pinnacles of international integration without cluster formation and industry specialization.
Clusters perform a function as basic as bringing the worker and the machinery together to manufacture. Downstream and backstream industries, educational support, financial institutions and other service
providers prop up together linked by complementarities and commonalities. Clusters create the impetus
for innovations and competitiveness and facilitate commercialization. Easy access to raw material and
labor, rapid diffusion of technological innovations and incentives against rivals enable newer lines of
products and opportunities to get readily developed and absorbed in the market stream. Thus, the first
challenge that the governance faces for industrialization is the formation of clusters.
Urban agglomerates possess the factors required for a cluster to develop. With Nashik, Mumbai, Pune,
Nagpur and other centers of economic activity within the state, Maharashtra contributes approximately
15% of the national GDP. Another striking example of the effect of urbanization is Delhi; despite a small
size and population, this city-state contributes about 3% of the GDP. Sriperumbudur could develop into
an electronic hub due to its proximity to Chennai (Bombay High and Alappuzha near Mumbai and Cochin,
respectively). These regions had the resources but the means to process them came from their neighbors.
Infrastructure and human expertise available due to their proximity to relatively developed cities enabled
the regions to specialize and their industry to grow.
Location development cannot, however, be carried out oblivious of the inherent advantages of the location. Chandigarh as a tech hub failed as they could neither cater to the demand of engineers and the like
for the industry nor support the inflow of migrants who filled the job vacancies. The misconception was
that only a high-tech industry would lead to growth, but there is no such thing as a high-tech industry.
Companies in the same domain can be seen operating with different quotients of technological prowess.
Agriculture can be done with sophisticated machinery and give high returns. Location development must
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be in consideration with the local resources.
Another major barrier in cluster formations and urbanization is the creation of unsustainable urban
agglomerates. Bengaluru and Gurgaon emerged with great promises parallel to that of the Silicon Valley
and Singapore, but the decrepit state of their infrastructure tells a different tale. Economic policy should
reinforce the established and the emerging clusters; however, regulations need to be carefully laid out.
The Indian economic geography is waiting to be mapped. However, urbanization remains a challenge
for India with more than 70% of its population falling under the rural category. India reels under the
burden of income disparities and economic backwardness and urbanization would encourage industrial
clusters to create the much-needed income and employment opportunities. A cluster-based regime would
open the doors for competitive advantage to lead the entourage towards growth and progress and unlock
umpteen avenues for states and regions to create an agglomeration of prosperity.
January 2011
81
Good Urban Governance:
An Imperative for Equitable Growth
Gordon Feller, CEO of Urban Age Institute, succinctly describes how improving governance—at
the central, regional and local levels—is now a critical part of the agenda for urban economic
growth and social development worldwide.
G
ood urban governance means inclusion and representation of all groups in the urban society, as
well as accountability, integrity and transparency of government actions. Capable urban management means the capacity to fulfill public responsibilities with knowledge, skills, resources and
transparent procedures. There isn’t a single model that could fit the complex process of local capacity
building in all countries across the region; the ultimate success is determined by national policies and
local leaders’ willingness and ability to carry out their mandates. The World Bank provides technical assistance and advisory services to assist in public administration reforms and capacity building at the level
of local governments.
Firstly, we need a good definition to guide our thinking: governance is the science of decision-making.
The concept of governance refers to the complex set of values, norms, processes and institutions by which
society manages its development and resolves conflict, formally and informally. It involves the state, but
also the civil society at the local, national, regional and global levels.
Good governance implies effective political institutions and the responsible use of political power and
management of public resources by the state. Essentially, it is about the interaction between democracy,
social welfare and the rule of law. Good governance, thus, extends beyond the public sector to include all
other actors from the private sector and society. Good governance is guided by human rights and by the
principles of the rule of law and democracy, such as equal political participation for all. Particular attention is devoted to the needs of the weaker members of society.
In the United Nations’ Millennium Declaration, the international community reached a consensus that
good governance is not only an aim in itself, but also a key factor in attaining human development and in
successful poverty reduction and peace-building.
Some of the most important work now underway on good urban governance covers the promotion
of democracy and rule of law. Human rights play a particular role in this context, especially women’s
rights. Effective works in the field of law and justice means fighting corruption and promoting the
responsible use of public finances. It means supporting smart and effective government and administrative reforms, the decentralization and regionalization of state power, and the development of local
and municipal government. In doing so, it implies the promotion of locally appropriate approaches; it
not only cooperates with government institutions, but it must also promote and strengthen civil-society
actors.
Decentralization is crucial to the whole process of creating better, smarter and cleaner urban governance. Citizens, companies and associations approach the state requesting an enormous diversity of
services; the law must regulate which of these the state is required to perform. It is also necessary to
define the tasks to be undertaken at each government level—central government, regional authorities or
local administrative units. Decentralized governmental structures work closer to the grassroots and are
more cost-efficient and flexible. However, local authorities and regions are not able to solve all of society’s problems. An important criterion for dealing with the question of governmental organization is the
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‘subsidiarity’ principle. This says that tasks should be performed wherever possible at the closest level of
competence appropriate to the given situation.
Many countries want to exploit the advantages offered by an expedient allocation of tasks within the
government administration. This requires regulating decision-making responsibilities and earmarking sufficient resources for implementation.
Many governments and parliaments are in the process of defining these tasks. For which services and
corresponding infrastructure measures is the state itself responsible? Which tasks can it entrust to others? How does it plan and finance these? Which government levels should perform which tasks? Should
responsibility lie with the central government, or a regional or local authority? Who decides on the quality
of services, and how? And who monitors the actors?
In order to find technically and needs-appropriate solutions, a growing number of government actors
are focusing on performing the tasks allocated to them—what competencies do the local authorities need
in order to promote local development? How can the support measures be organized so as to produce
sustainable results? This also means involving representatives from the regions and municipalities, civil
society and the private sector in these decisions on reform.
Cities with good governance have a greater potential to create and support good living conditions.
These cities have a better chance to offer their inhabitants a more equitable share in economic growth,
access to infrastructure and services, and participation in political decision-making. Accompanying these
opportunities, however, are growing demands on the capacities of municipal institutions. As national-level
public funding dwindles for cities, public resources must be stretched to meet the needs of the growing
numbers of urban dwellers. This is one of the central challenges of our time.
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SMARTer India
Transportation bottlenecks increase business costs considerably in Indian cities. Dr. Amit Kapoor,
Professor of Strategy and Industrial Economics, Management Development Institute (MDI) and
Honorary Chairman, Institute for Competitiveness and Susan Zielinski, Managing Director of SMART
(Sustainable Mobility & Accessibility Research & Transformation, a project of UMTRI, the University
of Michigan Transportation Research Institute and TCAUP, the Taubman College of Architecture and
Urban Planning, in Ann Arbor) tell us how innovations in information technology can pose some
solutions.
I
ndia reels under the burden of congestion and traffic. While urbanization traces a new path for the
Indian populace to race and prosper, the pace of the Indian economy is slowed down due to its grossly
inadequate infrastructure. The implications of the rise in urban population on urban transportation
and subsequently on business require urgent attention. The current state of transportation leaves vast gaps
between demand and supply, and future projections indicate we are nowhere near closing those gaps.
Precious time is wasted waiting in traffic jams and at signals. The woefully inadequate public transport
system, and the insufficient routes and roads available are the prime reasons for the hours-long traffic
congestion that most people in metropolitans have learnt to live with. The number of cars and private
transport are on the rise as towns and urban areas expand, and the provision of infrastructure to support
the influx is insufficient to create conditions for the smooth flow of all forms of traffic.
The problem is not small, and the subsequent consequences cannot be ignored. The cost of doing
business rises as employers need to get their employees to work. Hours are wasted managing the traffic
situation in place of working productively. What’s more, the health and welfare of all urban dwellers are
compromised with the rise in pollution, not to mention the longer-term threat of climate change. The dual
economy means different modes of transportation are suited to needs differentiated by variance in income,
in turn creating a bigger mess on the roads if the system is not properly integrated and optimized (which
is usually the case).
In a nutshell, there is no space left and the urban areas are only attracting more people. As such the
need-of-the-hour is not just a more fuel-efficient technology (that will actually continue eating up that
space), but rather a more multi-faceted, human-oriented, integrated system that connects and optimizes
all modes and services in an innovative and cost-effective way. The transportation problem has too farreaching an impact on land use, urban sprawl, pollution and climate change, infrastructure, and safety to
be ignored or reasoned only in the wake of congestion on the roads.
Fortunately, some exciting options are emerging, that may just meet urgent transportation needs and
result in business opportunity and urban competitiveness at the same time. Much as our present telecommunication network has evolved to include and connect iPods, PDAs, laptops, desktops and cell phones,
SMART’s innovative approach integrates the various IT technologies with a wide range of transportation
modes, services, designs and infrastructure to create an urban portfolio that permits an easy, convenient,
door-to-door trip. Only a step outside the house would link the traveler to ‘New Mobility Hubs’ or places
that connect a whole range of transport modes and amenities, day-care centers, satellite offices, cafes,
shops and entertainment, all linked for information and fare payment through a cell phone, PDA or information kiosk (for those who cannot afford a cell phone). The information is relayed in real time on the
arrival, departure or availability of transport modes and services including information on restaurants,
shops and services, maps, etc. The system works to offer smooth transition between various modes of
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transport and to use the information on scheduling and options to plan the most appropriate path or journey. It also works to offer new “last mile” services that provide on-demand transfer from the hub to the
front door. A person needs to just pick a waiting car or train or hop on to the next bus cutting delays to
the minimum. Imagine getting information about the waiting carpool to reach the nearest metro station
just in time to leave in the ongoing train, only to be dropped to the office or may be the airport, all within
a single, effortless and non-stop journey. All the modes of transport are streamlined to form a single network to transport people with smoothness, efficiency and speed.
SMART (Sustainable Mobility and Accessibility Research and Transformation) is an initiative of the
University of Michigan that began in collaboration with Ford Motor Company around 2005 to address the
transportation challenge in global cities as the world rapidly urbanizes. (In 2007, 50% of the world lived
in city regions. In the next 20 years that figure will climb to 2/3 of the planet). The exciting co-benefit
of addressing the urban transport challenge is that companies and entrepreneurs that work together to
respond to the need for sustainable, integrated, multi-modal urban transportation stand to tap rapidly
emerging (and sizable) ‘New Mobility’ markets.
In this spirit, SMART and Ford have engaged a myriad of industry partners related to the future of
transportation (New Mobility) to support a comprehensive entrepreneurial and business base. The initiative promises to change the way cities comprehend urban transport. Public-private partnerships can make
room for public-private innovation where business is involved from the outset in understanding and codefining the problem, and then offering solutions that support the public good and stimulate new business
opportunities at the same time.
Apart from addressing urban congestion, this approach has the potential to provide an ideal opportunity for businesses and entrepreneurs to develop integrated New Mobility systems building on the FordSMART collaboration. The question remains however, on how companies will envision the India-specific
needs and opportunities and uses of New Mobility Hub Networks and how they might create an intricate
web of technology and transport to simplify the current complications of the urban agglomeration and
offer an almost perfect (and cost-effective, business-positive) solution.
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Habitats at Risk:
Challenges of urban governance in India
Raj Liberhan, Director India Habitat Centre, warns of impending disaster unless a realistic needs
assessment of the infrastructure needs of Indian cities is made. Ultimately, pressure from the citizens, who seek a better quality of life, will be the ultimate motivation and test for city governments
and managers.
H
umans have used nature’s assets since time immemorial in the belief that these resources had
always been around and would be so forever. The implicit view was ‘use what you need and do
not worry about regeneration or replacement’. The finiteness, however, of nature’s life-sustaining
treasures like water, energy, fossil fuels and forests has come home in a pointed manner to policymakers
and consumers alike, and is pushing us to rapidly find substitutes, supplements and replacements.
The stark reality facing us and demanding answers is that nature’s assets need to be secured and only
then can human security be ensured. The two are closely interlinked, though our perspective solely from
the prism of human security distorts the solutions we seek. This anthropogenic focus leads to a lopsided
investment of time and money and consequential unsatisfactory outcomes.
Urban habitats in South Asia (a region that gave us the immaculately planned towns of the Indus valley Civilization thousands of years ago), and indeed in much of the developing world, are fast becoming
vulnerable to multiple hazards. Mega cities, in particular, are crucibles of hazards. Smaller cities too
are deteriorating at an alarming rate and there is not even a modicum of concern in evidence, much less
an effort to ameliorate the situation. Water availability is an issue and its quality an even greater issue.
Energy concerns, both of availability and access, plague every city, big or small. Sanitation and waste
management strategies are beginning to be talked of only for mega cities. In the rest, disposal of waste
generally implies throw-what-you-do-not-need-in-any-vacant-site. Similarly, sanitation in small and medium towns is virtually non-existent. The cumulative impact of the needs of burgeoning urban populations
is depleting physical resources, and given the absence of a perspective plan for managing our cities, there
is no regeneration of sources of supply.
The big question is—will our cities survive? Or is there certain inevitability about the degradation of
city infrastructure and civic amenities that no organization or planning process can address as the volumes to be serviced are huge? In this context, questions about the sustainability and survival of the city
and its population acquire great urgency. If we couple this with the inadequacy of the solution providers
one could argue not much time is left before the inadequacies swamp any chance of a solution.
There is no doubt that the state is making efforts to provide for capital investments in infrastructure
and services at the city level as well as undertaking urban reforms (the Jawaharlal Nehru National Urban
Renewal Mission is an important example). However, the current state of civic infrastructure is a sorry
tale and the challenges are enormous.
For the capital city of Delhi alone, as per Prof. Kumon, with the number of agencies in charge of the
capital’s water supply, sanitation, health services and pollution control, it could be reasonably assumed
that the city enjoys an enviable standard of cleanliness and health. Nothing could be further from the
truth. Let us look at a few telling statistics for solid waste, water and energy as illustrative examples.
About 6000 tons of solid waste was generated daily in Delhi during 2004, up from 1960 tons in 1981.
According to the 1997 White Paper on Pollution in Delhi, this figure is expected to increase to about
12,750 tons per day by 2015 (http://www.envfor.nic.in/divisions/cpoll/delpolln.html). Per capita waste
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January 2011
generated ranges from 150-600 grams daily, depending on economic status. This includes waste from
households, industries and medical establishments. In addition, the two thermal power plants burning
coal produce 6500 tons of flyash daily. Out of this, only 65% gets collected per day by the Municipal
Corporation of Delhi and another 10-12% by other agencies (http://www.teri.res.in/teriin/camps/delhi.
htm#waste). What happens to the rest? Where does it go?
For the country as a whole, solid waste generated daily per person has increased from about 295 grams
in 1947 to 490 grams in 1997 and is expected to further increase to 945 grams by 2047 (http://www.
devalt.org/newsletter/feb04/of_1.htm). The estimated land required for disposing such huge amounts
would be humongous.
With respect to water pollution even though Delhi constitutes only 2% of the catchment of the Yamuna basin, yet the area contributes about 80% of the pollution load (White Paper, op. cit.). There are
16 drains that discharge treated and untreated waste water/sewage of Delhi into the Yamuna river. The
municipal sector is the main source of water pollution in terms of volume. In 1997, about 1900 mld of
wastewater was discharged from the municipal sector (up from 960 mld in 1977) and 320 mld from the
industrial sector. Though the installed capacity for treatment was 1,270 mld, the treatment quality was/
is not up to the desired level of secondary treatment. Thus, a substantial quantity of untreated sewage and
partially-treated sewage is discharged into the Yamuna every day. The Najafgarh drain contributes 60%
of total wastewater, and 45% of the total BOD load being discharged from Delhi into the Yamuna.
With respect to groundwater as well, 75% of the samples taken from hand pumps were found unfit
for human consumption. Delhi does not have enough clean water: as against the present demand of 800
MGD only 650 MGD potable water is available (http://www.delhijalboard.nic.in/djbdocs/r_w_harvesting/
harvesting1.htm).
The gap between demand and supply is partly being met by extraction of groundwater through wells,
tube wells and deep-bore hand pumps. It is estimated that water quality and availability problems will
become acute in the near future because fresh water sources will decrease, and the city will be forced to
use brackish and saline water.
Finally, we take a brief look at the energy scenario. The power situation is grave. At a general level
it can be said that India’s economic growth will continue to be hampered because of power supply constraints. What does this bode for India’s cities? The stories and statistics of shortages can be repeated
across the length and breadth of the country.
Yet our urban centers are growing by the day. What we need is an analysis of our cities’ strength and
deficits on five fundamental parameters that will determine their survival and growth or extinction. These
are water, energy, transport, sanitation and waste management. In our view, these are absolutely critical
and unless development in these areas keeps pace with demographic trends, the resultant disaster is going
to happen sooner than later.
We need realistic surveys and needs assessment of our cities on a given set of indicators, make an assessment of current pace of investments and the levels needed, technology supplements and strategies to
keep ahead of the volumes that will impact our cities. In the process, we also need to take a hard look at
structures of governance and their capacity to address the challenges of the five fundamental factors for
city survival and growth.
It is clear that placing the management of cities on the roadmap to sustainable development will require interventions on many fronts. Innovations are required to reduce inputs per unit of output (resource
management efficiency), restrict consumption of services (efficiency in service delivery), and augmentation of input flows (resource mobilization). Further, to assess the visible risks, alternative scenarios need
to be worked out, for example:
nBusiness-as-usual, if no changes take place on demographic and related fronts
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nFeasible interventions that control demographic and related parameters
nInnovative approaches with respect to city management processes
Some questions/issues
For initiating this process, several critical issues have to be addressed and a demand-driven strategy
designed to be implemented over a give time frame. Some illustrative issues or challenges that need immediate attention are:
nWhat have been the deficiencies in managing the growth of cities?
nWhat local innovations and policies are required to manage the rate of slum formation?
nWhat are the most effective interventions to assist the urban poor—slum upgrading, slum relocation
or other types of interventions?
nWhat are the three most critical tasks to bring back a safe and hygienic city environment—waste
management, water management, slum management, traffic management, energy management?
nWhy has the present set of interventions not worked—bad planning and policies, inefficient management, weak information base on the problems and on people’s aspirations?
nIs there a hope for our choking cities and what should be the roadmap for them to reemerge not only
as centers of sustainable growth, but as attractive destinations for healthy living?
Documentation can be the starting point of a dialogue for the citizens to demand provisioning of allocations in a given time frame and to create benchmarks for every city so that the citizen can demand
performance of their city managers and representatives. The ultimate equation of environmental security
creating the ambience of individual security will get created as a benchmark and the initiative can be extended to other cities. This will serve as a citizen’s mandate for civic governance that in turn can impact
the attitude and agenda of the political executive, irrespective of party affiliation.
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Walkability: The Critical Urban Paradigm
Sanjeev Sanyal, Founder & President of the Sustainable Planet Institute advocates urban planners
to include walkability into the DNA of Indian cities as a simple, yet radical step, towards increased
sustainability and social inclusion.
W
hen China began to reform its economy in 1978, it had an urbanization rate of barely 18%
(roughly equivalent to India in 1950). Thirty years later, the proportion is estimated at around
55%! We have every reason to believe that India will experience something similar in the next
three decades. Within fifteen years, states like Tamil Nadu, Maharashtra and possibly Gujarat and Punjab
will have an urban majority. By 2040-45, we can expect the country to have an overall urban majority.
This raises the problem of accommodating another 350-400 million people in our cities. Indian cities
already struggle to serve the existing urban population, how will they deal with this deluge? In particular, how do we ensure that these cities are environmentally sustainable at a time when climate change is
becoming a major global issue.
Of course, environmental sustainability is not the only factor to consider. Cities have to be economically- and socially-sustainable as well. This is true for existing cities as well as the many new cities that
India will build in the next half century. So we need to think of an urban paradigm that combines ecological concern with inclusive growth. Furthermore, it must be a paradigm that applies equally to small
mofussil towns like Purulia and Jorhat as well as mega-cities like Mumbai and Delhi. Finally, it must be
simple to understand, easy to apply on a mass scale and flexible enough to adapt to local conditions. Is
there a way to combine all this?
Need to think systemically
Growing awareness about climate change has recently focused a great deal of attention on “green buildings” as the future of urbanism. A plethora of “green codes” have been initiated including LEED, GRIHA
and so on. My discussions with leading architects suggest that these codes typically give us energy savings
of around 15% (higher savings are possible but they involve sharply higher costs). This is a useful saving,
but it is hardly a major strategic intervention.
The problem with so-called green codes is that they exclusively focus on maximizing an individual
building whereas the real gains come from overall urban form. Is the city dense or sprawled? Do people
live in apartments or free-standing houses? Is the city designed for public transport? For instance, energy
use drops by over 30% just by moving people from houses to apartments even if we ignored the green
codes. In other words, India needs to think more about the overall scheme. Given the scale of the impending shift in population, we urgently need to think of simple and universal paradigms that can be replicated
on a mass scale across the country.
Walking: The ultimate form of public transport
The history of every city is ultimately defined by the nature of its transportation network. London is
defined by its underground rail network, Manhattan by its street-grid (and its underground rail), Los Angeles by the highway network, Paris by its avenues and wide side-walks, and so on. This is critical to both
their evolution as well as their urban experience. This is also true of Indian cities. Mumbai developed two
railway corridors built in the nineteen-century while Delhi is the result of a car-based design (cars had
just appeared when Lutyens was designing New Delhi). Once the transportation network has been fixed,
the DNA of the city is very difficult to change. This means that our quest for environmentally and socioJanuary 2011
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economically sustainable urban form must start with the transportation network. Given our concern with
environmental impact and social inclusion, it must be some form of public transport—but what?
Any discussion of public transport ends up being a debate about buses and trains. Oddly, the simplest
and most widely used form of public transport is walking (and its sister mode, cycling). A 2008 study
of 30 Indian cities showed that almost 40% of all trips in urban India involved no motorized vehicles
at all—28% walked and 11% cycled. The proportion was sharply higher in smaller towns as distances
were usually small and the roads less congested. However, in bigger cities, the proportion of people using
conventional public transport was high, and consequently commuters walked the last mile. For instance,
in cities with more than 8 million population: 22% walked all the way, 8% used cycles and 44% used
public transport. This adds up to 74% of people who rely on non-motorized transport for at least part of
the commute.
Not only is walking a democratic form of transportation, it is clearly ecologically-friendly, healthy, enhances social interaction and gives the city a personality. Moreover, social interaction and street life have
enormous economic value as this is what makes cities dynamic and creative. This is why the core of all the
world’s great cities is consciously walkable—central London, Paris, Manhattan, Singapore and so on.
Note that walkability and public transport must be embedded in the urban DNA as soon as possible
because it is very difficult to retrospectively change urban form. Take for instance, Atlanta and Barcelona.
Atlanta has a metro network of 74km while Barcelona has one of 99km. These may seem comparable but
per capita CO2 emissions for Atlanta are ten times that of Barcelona. The difference is mostly explained
by Barcelona being compact while its American rival is spread out. As a result, less than 4% of Atlanta’s
population lives within a reasonable walking distance of a metro station compared to 60% for Barcelona.
If Atlanta now tried to give its citizens the same accessibility, it would have to build 2800 new metro stations and 3400km of new tracks!
Despite this overwhelming evidence, very little thought is given to pedestrians in Indian urban planning. A brand new city like Gurgaon does not have any network of sidewalks at all! Note that it is not just
a matter of building sidewalks. Walkability is about making it possible for the average citizen to be able
to lead his/her life by relying largely on walking for day-to-day activities. This requires a whole gamut
of urban design requirements like density, mix-use, street life, pedestrian crossings, tree-shade, publicspaces and so on. All these parameters are important in their own right, but walkability is a simple way
to encapsulate this philosophy of urban planning. This is why I strongly feel that walkability is the single
most important urban design paradigm that must be adopted while thinking of India’s urban future.
“Traffic and Transportation Policies and Strategies in Urban areas in India”, Wilbur Smith Associates (sponsored by Ministry of Urban Development), 2008.
World Development Report 2009, The World Bank.
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January 2011
Branding a City From Within
Madhav Raman, Partner at Anagram Architects and Anupam Yog, Director with Mirabilis Advisory
take a look Delhi’s inherent urbanism, its urban identity and experience and at the interstitial elements within Delhi that could be used to build a brand for the city, from within.
Urban experience
“A single exhaustive definition eludes a city’s “urban experience”—which can also be interpreted as a
city’s brand. Nevertheless, it could perhaps be described as a woven composite, mainly defined by its built
character, its urban identity and the behavior of its residents.”
Built character: The evolution, conservation and renewal of the built character of a city is governed by
planning norms, building controls and urban policy, which are the traditional instruments of urban planning and urban design. The built character makes the most immediate spatial and visual impact of the
city’s “hardware” on the psyche of its residents. Through its deliberate control and careful manipulation,
a physical sense of “place” may be created within different precincts of the city. It is even possible to create “urban icons”, spaces that induce a sense of belonging through their distinct and unique singularity.
Urban identity: However, “place-making” is truly the work of the citizens of a city. Certain urban
contexts of the city strike a deep chord with its residents. Even though they may be unremarkable architecturally, the chord resonates with the citizenry so strongly that a collective identity gets invested in these
“places”. The “places” then move beyond the realm of physical symbolism and become iconic within the
minds of the residents, contributing immeasurably to their urban identity. Quite often, this is less through
physical engineering, but due more to the nurturing of numerous inherent characteristics such as historicity, accessibility, multi-vocal qualities and inclusive nature.
Urban behavior: Multi-vocal urban contexts carry unique meaning to each individual; their simultaneous inclusiveness allows people to openly engage with them both individually and collectively. Such spaces
and contexts within a city have a deeply reciprocal relationship with the urban behavior of the residents,
the manner in which they view and engage with their city, and with each other. The urban behavior of a
city replicates itself in recognizable patterns at multiple scales.
Interstitial urbanism
“As emerging cities hurtle along the path of rapid urbanization, many issues that pertain to urban experience fall outside the purview of formal tracks of urban planning and policy.”
Urban experience evolves over many years of habitation in a settlement and has deep cultural and
socio-economic roots. Its very nature makes it impossible to describe, and therefore analyze, in purely
statistical terms. Yet, it adds immeasurable value to the city. It enhances the livability of the city and
increases its ability to attract and absorb human capital. In short, it vitalizes a city, encouraging a sense
of belonging amongst residents and widening their engagement with the city and with each other. This
helps empower segments of urban society whose means are limited and who seem to have a reduced stake
in the city. It increases the adoption and utilization of the city’s infrastructure and spaces through culturally congruent means. Other aspects of healthy urban behavior such as syncretism, tolerance, a social
conscience and a liberal outlook are intrinsically linked to a vibrant urban experience.
The urgency for development in emerging cities puts a strong emphasis on global models of infrastructure development and technological advancement. Yet, this often results in eroding the intangible quality
of urban experience. Moreover, the pace of development frequently allows inadequate time and space for
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the city to adopt new physical infrastructure and spaces, and infuse them with its inherent urban character. Crucially, the rapid introduction of new physical assets to the city renders older, often more vibrant
assets, redundant, defunct or underutilized. Their reinterpretation and regeneration may help in creating
timeless, relevant socio-cultural anchors that are vital for cities experiencing vast change over a relatively
short period of time.
What are these core assets that hold the key to revealing a city’s identity or character? What is the
nature of their potential to add value to the urban living condition? In what manner could these be tapped
or reinvented to create more inclusiveness? How can these assets empower residents, and result in socioecologically aware lifestyles?
Branding Delhi
Let us evaluate the possibilities of building Brand Delhi by looking within.
Redundancies enroute: Within Delhi’s grade separators, interchanges and rotaries, pockets of redundant spaces and surfaces such as flyover soffits, traffic islands, medians and roundabouts exist. Such
features are permanent components to our cityscape. While they are constantly on view (to commuters
for example), there is scant engagement with the city. Can these spaces do more than merely channelize
traffic?
Defunct urban hardware: As Delhi acquires new infrastructure and buildings, old structures, “hardware” and edifices are abandoned, get under-utilized, or become superfluous. Many of these have significant urban value due to their age, iconic status or location. Could they be innovatively leveraged?
Water conduits: From the natural drainage systems (nullahs) to sewers, water supply pipelines to water
tankers, various conduits and channels of water scour Delhi. How can their value as existing networks be
better used by the city?
Green reserves: Delhi’s Ridge Forests were a contiguous belt that ensconced the formal city just a few
decades ago. Rapid agglomeration has reduced these to green enclaves of various sizes. While it is imperative that these are protected and allowed to thrive, it is equally important for them to be part of Delhi life.
What form of engagement should this be?
Urban villages & historic settlements: Delhi’s many “original” settlements and rural enclaves give a
unique flavor to the city, but seem to be at odds with development policies. Being outside the ambit of urban controls, they remain excluded from the fabric of the city. Could these settlements potentially enhance
the inclusiveness of the city and become vibrant contributors to Delhi’s urban experience?
Wholesale markets and street commerce: Delhi’s urban culture, like that of most other old cities across
India, is very deeply linked to the commerce of the street. This is the essence of Indian city life and Delhi
has its own special relationship with what is now termed as the “informal tertiary sector”. Similarly its
wholesale markets, some of which have existed for many centuries, are significant cultural anchors. Can
these seedbeds of interstitial urbanism be revived?
This is a radically different way of looking at building a contemporary city brand. Eventually, however,
in the context of India, and perhaps elsewhere too, it is important to look within to build a city brand that
finds resonance and has the ability to endure.
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January 2011
An Eleventh Intermission
Sam Miller, journalist and author of ‘Delhi: Adventures in a Megacity’, recounts his experience of
crafting and then running his beloved Delhi on SimCity from the year 1900 till the present day. His
frustrations as Mayor of Delhi in the game mirror the tremendous complexities of real-life urban
planning and management, both disciplines increasingly critical to the growth trajectories of cities
across the world and areas where Indian cities like Delhi urgently need expertise and intervention
today.
T
he year 1999 was one of the worst in Delhi’s history. Air pollution reached record levels, there were
daily power cuts and water shortages, rioters took to the streets, a tornado struck the south of the
city, there were huge fires in the largest industrial area; a plague of locusts descended on Delhi’s
suburbs, space junk landed in the city center and the Yamuna turned into a raging whirlpool. The population halved in the course of the year, with people fleeing to the neighboring countryside, and the city went
bankrupt. Delhi’s long-standing mayor, Shyam Mitra, leaned back, stared at his computer screen, and felt
he had no option but to resign. Or he could go back to his previous saved version of SimCity, when Delhi
was still a flourishing metropolis.
Until my son introduced me to SimCity, I thought all computer games were about killing or winning,
or both. In SimCity you can’t win, and no one ever dies (even during an earthquake). Instead, you build
your own ‘simulated’ city, call it what you want, become its mayor and see how successful you are at running it. As the clock of history ticks by, at your chosen speed, on the toolbar at the bottom of the screen,
your city grows and shrinks. People (‘Sims’) migrate to your city when it’s an attractive place to live and
work in. And they leave if they don’t like it, perhaps because you haven’t built enough schools or there are
too many power cuts, or because it’s too boring. I became a secret addict. It’s unexpectedly realistic, and
because there is a serious side to it—like a beginners’ course in urban planning—I felt able to pretend
that I was hard at work.
SimCity has a number of pre-installed cities—real and invented—including London, Los Angeles and
an all too plausible Dullsville. But there’s not a single city from the developing world. So, no Delhi. I felt
it was time for me to have a shot at running this city that had become my home. First, I had to recreate
the terrain of Delhi on an empty greenfield site, carefully sculpting, with mouse-and-toolbar, the contours
of my virtual city. Delhi would not be Delhi without the Ridge and the Yamuna, and I was able, god-like,
to raise and sink the land to create the ancient topography of Delhi on my computer screen. I then had to
skip the next few millions of years of Delhi history, since the game automatically gave me a formal startdate of Jan 1, 1900.
I hurriedly created Old Delhi first, with a central street, just like Chandni Chowk, as its main east-west
axis. I carefully placed homes, factories and shops around Old Delhi in a way that mimicked the real city
at the start of the twentieth century. I could lay out the streets as I wished, and had a choice between
residential, commercial and industrial buildings of low, medium or high density. The population began to
grow. I laid railway lines, created landfill sites, built hospitals and schools. The architecture of the building was very Western, so compromises were necessary. For the Red Fort I had to make do with a Disneystyle Cinderella’s castle; a lighthouse became the Qutub Minar, surrounded (this was the early 1900s) by
a small village. The only nod to India in the entire pre-packaged SimCity game is the Taj Mahal, which,
quite appropriately, I was able to place on the site of its precursor and inspiration, Humayun’s Tomb.
In 1920, I began building British New Delhi. The avenues of India’s new capital were laid out accordJanuary 2011
93
ing to the plans of Lutyens and Baker, with the Arc de Triomphe and the White House proving suitable
substitutes for India Gate and the Viceregal (now Presidential) Palace. I moved on quickly to the concentric circles of Connaught Place. The city’s population continued to grow slowly. The new parts of the city
were too low-density, I was told by Constance Lee, one of a series of virtual advisers.
I soon came upon the ‘disaster’ menu, a drop-down list that allowed me to summon up a wide range
of catastrophes. And so, at the click of a mouse, I was able to replicate the great North Delhi tornado of
1978. Similarly, the Partition riots of 1947, the anti-Sikh riots of 1984, the anti-Muslim riots of 1992
all took place (this time without serious casualties) on the streets of SimDelhi.
However, the SimCity computer model was not working like the real Delhi in a number of telling ways.
Sims are a lot more fussy, or spoilt, than the people of Delhi. By the late 1990s my city only had a population of just over half a million, a twentieth of the size of the real Delhi. If the roads aren’t kept in perfect
condition, or there are a few power-cuts, Sims leave the city in droves. They began demanding a Metro as
early as the 1920s, and would not put up with what were, by Delhi standards, rather low levels of pollution. Sims won’t move into homes without an underground 24-hour water supply.
As mayor of Delhi, I became more and more frustrated, and began to run out of money. Most of the
city’s income came from taxes, and its residents kept moving out if I raised tax rates. In early 1999, an
old electricity generating station became overloaded, and blew up. I didn’t have enough money to buy a
new one, and all the other electricity plants tripped. Suddenly Delhi had no power, not even enough to
work the water pumping stations—and my lovingly created city had no water either. In the real Delhi, poor
people would have used handpumps and wells, the rich would have used water tankers and generators. But
Delhi just collapsed. A self-destructive anger, born of impotence, overtook me. I pressed every disaster
button, and went to get a beer from the fridge. My city was black with the carcasses of deserted buildings
by the time I returned a few minutes later. In two SimCity years, the population had dropped to almost
nothing. I realized that I hadn’t destroyed the city quite as quickly as the British had following the 1857
uprising, or as Mohammad Tughlaq had in 1327; but I had come pretty close. Delhi was dead.
I searched out my son, and told him my tale of woe. And he told me a secret. He taught me about cheat
codes. Most computer games have them, he told me with a slightly patronizing air, as if I were the child.
‘With SimCity, you just need to type in the special code, and everything is free.’ He reverted to my older
stored version of SimDelhi from 1993, held down four keys at once, (Ctrl-Alt-Shift-C) and up jumped
a little dialogue box. He typed ‘I am weak” and suddenly I had unlimited credit. Everything was free.
Another cheat code “nerdz rool’ converted all my old industrial buildings into hi-tech ICT businesses. I
began to create the perfect Delhi, my version of Amir Khusro’s heaven on earth.
Like Delhi’s city planners of the nineteen-sixties and seventies, I was able to ignore reality. They just
pretended it was a middle-sized city without major infrastructure problems. I could just print money, and
buy any solution I wanted. I did still try to keep the city authentic. So the Metro appeared in 2002, and
an earthquake shook the city in 2005. Lots of sporting facilities sprang up across the city in time for the
Commonwealth Games of 2010, by which time the Metro had spread across all of Delhi; there were still
more sports stadia for the 2020 Olympics, and I was delighted when my city became an international hub
for space travel in 2045.
As the population continued to grow, I felt pleased with myself, despite the double artificiality of a city
that exists only on a computer hard drive and in which construction costs are zero. But it did raise the
same issues, which remain at the heart of Delhi’s modern dilemma. I had chosen population growth as my
indicator of success; recognizing that improved services mean more migrants, which puts greater pressure
on services. If these services can be improved, the city’s population would, well, spiral.
SimCity has a limited number of pixels, or land squares, on which I can ‘grow’ my city. And in the
end I ran out of space, with a population of just over two million. There are no geographical limits—no
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January 2011
mountains and no coastline—to the expansion of the real Delhi; it could, for better or worse, continue to
grow in every direction, and it may once again become the most populous city in the world.
Outside the Console
Agreed, this is just a video game. But this “game” puts forth some serious considerations for all of us.
While we are busy ranking our mega cities, SimCity, by not having any Indian cities as an option, lands
a blow to our ego. One might contend that it is a western game and hence it might have been created to
cater to a similar audience. That is very sound logic, especially since it had no cities from the developing
world. Well, to the competitive Indian that is still an insult: it is okay to ignore the rest of the developing
world, but they must have chosen some Indian cities to represent the emerging world!
The policymakers do not have it easy. Even inside the console, creating and maintaining a city turned
out to be a tough task. As the author discovers, coping with the population growth alongside the growth
in the diverse demands of the people is overwhelming even in a virtual world. By how much this difficulty
compounds in the real world is a matter of debate, what is a certainty is that the difficulty does compound.
Unlike Miller, our mayors do not have ‘special codes’; hence everything is not free! That’s the real
world for you. Hence, it is not possible to create everything perfectly like in SimCity. However, unlike
Sims, real Delhi-ites do not think luxurious amenities as being mandatory before choosing a city to live.
So we don’t really need to build Delhi to perfection, and can still be rest assured that it will continue to
grow. The end result, just as in the video game, we have ourselves a situation where the population spirals
and Delhi continues to grow until it reaches its boundary, like in the game, or a point of self-destruction.
In a strange way, the simulation augurs the need of careful planning for Delhi—and any big city in
India for that matter—as we concentrate on making our cities productive, competitive and livable. It
calls for detailed vision and implementation of decisive regulations pertaining to advancement of infrastructure, population control, environmental sustainability, etc., from the policy makers. Thus, while our
mayors fence away to make their respective cities as competitive as possible as business destinations, they
may fare better if they heed this SimCity fable!
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FDI, Cities and Competitiveness
Sandeep Mann, COO, Remorphing writes about how cities can leverage their competitive position
to attract investment and what a long path Indian cities need to tread to really interest investors.
A
nand Mahindra once stated that any region aspiring for a healthy incremental capital output ratio
(ICOR) of 4, with the usual growth rate of 8%, needed reinvestments to the tune of 32%. Unfortunately, no region has savings matching this figure, usually capping savings at 5-20%. Naturally,
this deficit has to be plugged with foreign investment. All regions have to chase higher and more sustainable planes of prosperity; falling in line with a Nietzsche kind of directive to emerge as ‘exceptional
regions’ with ‘exceptional inhabitants’. Though the competitiveness of any region can be measured in different ways, the enhancement of all such levels would always be fuelled by further investments.
The Gandhian thought that work remains so long as there is a tear in any eye is contemporarily
matched by initiatives that seek to provide a decent life for workers and citizens be they from Brasilia,
Vladivostok or Hyderabad. Levels of affluence have been correlated with quanta of foreign direct investments (FDI) received, whether the trigger was selfless service or ‘sacrificing one’s own selfishness via
making all prosperous’.
Indeed, like any vanilla investment, FDI too is an investment by an investor in a specific industrial sector, which is highly linked to geographical moorings, as in a parallel sense observed about international
trade by Ghemawat’s CAGE model. FDI would find its appearance in industrial activity over a large
tract of land, or setting up marketing channels or placement of offerings on buying shelves for consumers
or industrial buyers; but it essentially resides in a city. The administrative function of any commercial
enterprise, willy-nilly, is based in a city, maybe with production facilities situated in the near or distant
precincts. Consequently, although FDI influences the economy of a vast region per se, it emphatically influences cities therein. So any city wishing to shoot up its competitiveness has to go gunning for FDI—for
regions around it and for its own direct upliftment. The same goes for quasi-cities that spring up in and
around SEZs.
Data over the past years would indicate that a ranking can be developed for FDI attracted by various
cities, apportioned pro rata over their GDP onto the state’s FDI. This shows that the top winners are Delhi,
Mumbai, Bengaluru and Hyderabad. However, as FDI winnings is a global canvas battle, Indian cities are
far from entering such face-offs with other cities in the world. For Indian cities, competitiveness via FDI
still carries a surrealist feel. Tangible realism needs to be brought forth.
It needs no vociferous proclaiming that there is a compelling urgency for all cities to project themselves as branded destinations for FDI. Intense soul-searching and mapping of competitive positioning
alone shall enable every city to carve out its unique appeal as an investment destination, rather than a
faceless, generic, monolithic we-are-open-to-all-kind of investments pitch. Aping the leading cities by the
laggards shall be surely a futile and counter-productive exercise.
As Professor Porter illuminates, factor advantages are to be created not inherited. On the value chain,
the regions that are factor-led scores lower than the ones that are efficiency-led, which again score lower
than the innovation-led regions. Indian cities have to discover where it is they have and can pitch for
competitive advantages and advantages that can be sustainable. An integrated analytic look at the four
pillars of Porter’s Diamond Model, done carefully, sifting realistic assessments from biases and politically-motivated slanting of facts, shall duly brighten the path ahead. For instance, why should Ahmedabad
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ask for FDI in voice-based outsourcings, when it does not have suitable labor pool (as large as Bengaluru,
Pune or Delhi). Instead, it should walk into showing itself as the best destination for concept arbitrage, a
knowledge kind of outsourcing, drawing on entrepreneurial and managerial traditions its people are very
strong on. Bengaluru can’t beat Hyderabad on cost of living index; why doesn’t it move its IT sector onto
high-end priced services. Why can’t Jaipur be an all-season tourist hub, conceiving adventure sports for
its harsh summers? After all, cities in Arizona are as hot as Jaipur and still enjoy significant tourism.
Again, we have seen that attracting FDI is shadily managed by Indian cities and governments. In this
world of online connectivity, no city has a decent tell-all website. Ironically, Holland maintains a better
FDI India site than does the Indian Union Government! There is no serious activity to associate an FDI
investor with a local alliance partner; and how can that be done, there is no detailed profiling of local
entrepreneurs who can thus be brought together! Which city has a dedicated think tank tracking what
cycle industries are undergoing in various parts of the world? The investor is nothing other than an organized or loosely-formed think tank, acting for a large organization, seeking optimal or maximal returns
on investment (RoI).
Is this FDI investor being reached? Some itsy-bitsy foreign tours with ministers and their entourage
meeting small pools of the Indian community abroad never do the trick. Is adequate faith being won over
by showing accountability and objectivity in governance, inspiring confidence that investments wouldn’t
run into hot weather down the line? If these questions make policy-makers squirm, the first tentative
seedlings towards shaping competitiveness have been sowed.
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Papers and ideas
presented at the
13th TCI Global
Competitiveness
Conference 2010, India
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January 2011
Examining Open Innovation Practices
Among International Networks Of
Clusters
Andersen, Lise, University of Southern Denmark
Smith, Madeline, EKOS Ltd
Wise, Emily, Lund University, Sweden
Those who work with clusters spend time trying
to encourage collaborative behaviors between companies through trust-building, knowledge-sharing
and learning. The social capital generated can make
the difference between being just a group of companies in the same sector, and being a truly innovative,
growing and successful cluster.
The importance of social capital wasn’t always
at the heart of cluster approaches. Initial studies
focused on agglomeration, benefiting the companies
through economies of scale, pools of specialized skills
and shared infrastructure. However, this spatial analysis failed to adequately explain the success of some
industrial groupings and the failure of others.
It is therefore with interest that cluster practitioners and policymakers have viewed the rise of
open innovation, which acknowledges the requirement for companies to collaborate beyond their organizational boundaries. Open innovation builds on
the assumption that valuable ideas and knowledge
can emerge from internal as well as external sources and can enter the market from inside or outside the company. Therefore, companies that look
outside their in-house resources have better access
to ideas, expertise and technology than those that
rely solely on in-house sources. In a global economy, global links and connections are essential.
Such connections help in the dissemination of new
techniques, facilitate the adoption of new practices
and the development of new products and customer
value. This fundamental shift in behavior from a
previously internally-controlled innovation process
and mindset to a more open innovation process has
led a recent paper from the Economist Intelligence
Unit to claim “the future belongs to those who collaborate...with many players, from customers and
partners, to competitors, distributors and university researchers.”
January 2011
Clusters play a key role in helping to build those
networks and connections. Clusters can be a valuable means to bring the different knowledge triangle
actors in an innovation system together, connecting
companies to universities and research institutions.
Research-driven clusters build on the knowledge
strength of a region and through establishing linkages, joint strategies and collaborations across the
Triple Helix, help produce a route to exploitation
from those ideas. For policymakers, clusters are a
great opportunity to support this type of collaborative behavior, to help companies explore open innovation, and help overcome barriers that prevent
companies engaging in this type of innovation.
Social capital plays an essential role in the pursuit of open innovation collaborations, and many
companies are already stressing the importance of
clusters when engaging in open innovations activities with external actors.
It’s not surprising, then, that policymakers are
beginning to ask “What does social capital within
and between clusters have to do with open innovation practices? What role, if any, can policy play?”
The presentation introduces action research on
a network of ICT clusters in the Baltic Sea Region
that is scheduled commenced in early October. The
research will explore the role that cluster organizations and other actors have in facilitating open innovation activities between companies in a cluster. The
research will also examine whether open innovation
activities within and between clusters support greater
collaboration within and among clusters thereby fostering a stronger international innovation dynamic.
The action research will lever the cluster dynamics survey (introduced and discussed at previous TCI
conferences) to examine social capital between clusters in an international context, as well as a newly
developed interview questionnaire to gain insights
on open and user-driven innovation tools used by
companies working in international contexts.
The aim of the presentation is to discuss and gain
peer perspectives on the research approach planned
for exploration of the following research questions:
a) Is it important to have strong internal cluster dynamics (i.e. social capital) before pursuing open
innovation activities internationally?
99
b) Do open innovation activities between clusters
create a stronger international innovation dynamic?
c) Do existing policies support open innovation activities within a cluster and between clusters internationally?
n What activities are undertaken by regional authorities in this regard?
n What role is played by cluster organizations/intermediaries?
n What are companies’ perspectives on these policies?
A further challenge to be explored is whether
encouraging open innovation between clusters at
an international scale threatens to undermine the
internal dynamics and growth of social capital within a regional cluster. How can the best balance be
achieved between building social capital and strong
dynamics on a local level with sourcing knowledge
and working with open innovation practices internationally?
The aim of the research is to gain a better understanding of the interdependence between social
capital, open innovation, cluster building and internationalization. The role of social capital in open innovation activities and cluster building will be looked
at, and social capital and open innovation processes
function in an international context will be explored
to gain a better understanding of how open innovation activities between clusters can contribute to a
stronger international innovation dynamic. Finally,
how policies can support open innovation activities
within and between clusters in an international context will be explored.
Comparative Analysis of Marketing
Externalities and Process Knowledge
Spillovers Among Various Industrial
Clusters
Arbi, Khalil A.
University of Management and Technology, Lahore
Fast-paced globalization has put corporate and
SME firms under great pressure to maintain their
comparative advantage. Prevailing literature on
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cluster development suggests that small and medium firms consider location as key point for their
sustainable comparative advantage. From various
studies across the globe, businessmen take location
of their business as a fundamental source of success. It is claimed that networking and co-location
are big sources of business knowledge that are necessary to compete in the international market.
The studies done by Brown, P. et al (2010) and
Felzensztein et al (2008) cover analysis of marketing externalities across various geographical locations. Studies done by Brown, P. cover electronic
clusters of New Zealand in which the authors have
given analysis of active and passive marketing
externalities. On the other hand, research from
Felzensztein et al covers a comparative study of
salmon-farming industry cluster across two different geographic locations i.e. Scotland and Chile.
Both studies have given a detailed analysis of marketing externalities, but the difference among them
is that one is confined to only a single geographic
location, while the other takes into account one
cluster in two different geographic locations. The
results of both studies are somehow same with little differences due to different nature of industrial
clusters.
This research has been executed to make a comparison of marketing externalities and production
process knowledge spillover across various industrial clusters of Pakistan. It is different from the
above mentioned studies in many aspects. Here we
have taken four different industrial clusters in the
Punjab province of Pakistan. Two of these clusters,
surgical instrument and sports goods are found in
the same geographical location of Sialkot, whereas
the other two cutlery and textile clusters are found
in Wazirabad and Faisalabad, respectively. The results from these clusters will be multidimensional
and provide more in-depth knowledge about the
behavior of various firms working at the same as
well as in different locations. Interesting findings
will come from two different clusters working in
the same location.
The objective of the research is to provide an
analysis about how various firms working in the
same cluster differ with firms working in other
January 2011
industrial clusters. Obviously there are differences and similarities of their behaviors. We want to
catch the nature of benefits from marketing and
production process externalities that these firms
currently enjoy. The results of this research will expose the underlying characteristics of various clusters situated at the same and at different locations.
The research results will show the extent of benefits
gained by firms across various locations and various disciplines of business. It has been statistically
seen that the selected four industrial clusters have
varied performance in the international market.
Some of them are highly export-oriented whereas
some are performing fairly in the international
arena. The results of this research can also be used
to evaluate cluster performance at an international
level. Along with export performance, we have also
tried to catch innovation in the clusters as well.
An increased networking and knowledge spillover
has a logical consequence of increased innovation.
In this research, our intention is also to gauge the
level of innovation in each sector as well.
Clusters as Incubators for Innovation
Bode, Alexander
Hessenmetall Cluster-Initiative, Germany
During recent years clusters have gained much
attention from both practitioners as well as researchers. The organization of clusters is regarded as one vital instrument for increasing competitiveness of member companies or even of a whole
region. The underlying assumption is that collaboration of companies that compete in different
fields, the so-called “competition”, stimulates innovation. Knowledge spillover among companies
from a region shall result in a unique combination
of resources and a pool of knowledge. As a result
of this process, specific cluster companies achieve
a competitive advantage. However, one problem
many clusters face is that they have trouble in
acquiring money for the work they are providing.
Many clusters are founded by public funding e.g.
in Europe by funds for regional development from
the European Union. This sponsorship ensures a
sufficient cash flow for a certain period, mostly
January 2011
three to five years. However, after the funding period most clusters got into trouble for they could
not implement a sustainable business model. The
member companies are not willing to pay the total
cost of the cluster-coordination because the benefits of the cooperation for the members are not
transparent or maybe too low to justify the costs.
Most clusters in the EU will disappear after the
funding period, if to they cannot deliver measurable results for their members.
It is this paper’s aim to introduce a sustainable
cluster model that delivers measurable and valuable benefits to its members. Hence, we like to introduce a model of a cluster with network characteristics that is used as a platform for collaborative
innovation activities.
The central constituent element of clusters,
which is agreed upon, is the geographical concentration of its players. As is evident in literature,
the (competition) relations between the players are
subject of ongoing discussions. Therefore, the relationship between the individual players of clusters can be anything from competitive (respectively
non-competitive) to cooperative.
Networks are characterized by the relations between the parties, which are mainly of a cooperative nature. The geographical expansion, however,
is not a constitutive characteristic of networks.
Production networks for example can span globally
while innovation networks between suppliers and
customers cover a smaller region. Networks may
prove to be an essential element of clusters. The
presence of a cluster does not necessarily lead to
the establishment of a network.
These observations lead to two possible parameters for classifying both clusters and networks:
(1) geographical expansion—a network can be at
any point on the continuum between global and regional, while a cluster is concentrated in a region,
and (2) intercompany relations—while a network is
initiated for close cooperation, companies within a
cluster can cover the total bandwidth between cooperation and competition.
The “cluster with network characteristics” is
an approach that uses the most promising aspects
of both concepts. As a prerequisite for generating
101
competitive advantage the cluster with network
characteristics is established among companies
from one industry that have overlapping but complementary assets. The regional component facilitates the control, as people from one region see
each other again, and they may easily lose their
reputation they will not so easily be attracted by
“free-riding”.
The collaboration in a cluster with network
characteristics is based upon mutual trust. Establishing trust is a work-intensive process that requires commitment from all members. The level of
value-generating activities within a cluster is closely linked to an increasing level of trust. As high
value generation requires collaboration in fields
with core competencies, companies only open up
the heart of their company if they have confidence
in the other cluster members. Cluster activities in
the start-up phase are comprised of activities not
crucial to competition in order to slowly establish
some level of trust. Starting from exchange of experiences on the market in general or the collaboration for sourcing of indirect materials lasting to
sharing knowledge on general topics, for example
the effect of the economic crisis.
Once a sufficient level of trust is established, the
members can tackle more core activities leading to
the enlargement of the common knowledge base.
This is also the starting point for joint technology
and R&D projects together with research institutions. As clusters are a pool of relevant players
from one industry with complement resources and
competences, this is the ideal pool for starting up
intercompany innovation projects.
A certain level of trust is mandatory for collaborative innovation projects. In order to establish
trust some prerequisites are necessary:
n Participating companies need a phase for learning and getting to know potential co-innovation
partners
n The number of cluster members should not be
too high so that it is possible to get to know everybody within a reasonable time frame
n Open mindset of participating persons
n Continuity in participating employees from one
company
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n Eternal cluster-management, as an uncommitted coordinator
These prerequisites show that huge regional
clusters with 50 or more companies, organizing
just “get-togethers” are not the ideal platform to
establish sufficient trust. Therefore, such kind of
clusters can’t be used to initiate intercompany innovation projects. For establishing a platform for
technology-driven collaborative R&D projects,
companies need a cluster with network characteristics that provides a smooth initiation phase
for trust building among a manageable number
of companies. The companies can see and measure the benefits of such an approach and are
more willing to pay for the beneficial activities
of the cluster. All in all one can state that the
cluster with network characteristics is a sustainable business model for an innovative cluster that
creates benefits for the member companies and
for the region.
Analytical Framework towards
Competitive Clusters Local Economic
Development [CCLED]: Application to
Delhi
Choe, KyeongAe, Asian Development Bank
Roberts, Brian, SPMS Australia
Cities play a significant role in the economic
development of Asian countries. The urban GDP
per capita in most developing countries in Asia is
two-times greater than that in rural areas on an
average. Within a decade, more than 50% of the
population of Asia will live in cities. By 2030, almost all new jobs and wealth in Asian countries
will be created in cities. This means that most of
the secondary and tertiary industry sectors are agglomerated in cities and city-regions, as the key
forces of the engine of economic growth.
In tandem, economic challenges in developing
Asian countries have become more complex—
urban populations are growing at great cost to
the environment; income gaps between countries
and urban and rural areas widening; and climate
change has increased risks of natural disasters.
January 2011
These trends affect the sustainable industry growth
and reduce the effectiveness of the local economic
development.
Industries tend to locate where businesses can
have a competitive advantage, relying on cities’
competitiveness too. Cities offer shared access
to common infrastructure linking supply chains
and networks, and to required human resources
and skills, which help to reduce production and
transaction costs. Yet, government resources are
limited to provide supporting infrastructure for
rapidly growing urban areas and pose enormous
challenges. Governments and entrepreneurs in
Asian cities need to find ways to improve their
competitiveness, if they are to maintain sustainable development in a world where cities compete
for global trade and investment.
Despite these backdrops, structured systematic information is hardly available to assist
surging industries and micro, small and medium
enterprises to achieve competitive clusters in and
around city-regions in Asia. How can Asian cities and industries become more sustainable and
more competitive? What are the attributes that
make their urban industries competitive? How
can governments or development agencies identify and strategically invest, to boost competitiveness and sustainability? If so, which industry
clusters in which locality should get support under limited resources available? Most of these
issues have not been well assessed systematically—until now.
An innovative new analytical framework examining clusters and competitiveness of cities has
been initiated and formulated by the Asian Development Bank (ADB). The Competitive Cluster Local Economic Development (CCLED) approaches
to assess not only the strengths but also the deficiency gaps in facilitating competitive industrial
clusters, in a selected city-region. At the end, action plans are prepared for enhancing competitiveness of industry clusters and the cities.
This presentation will demonstrate the innovative analytical process of CCLED, applying the
6-step method in the Delhi National Capital Territory in India as a case study.
January 2011
Step one: Ranking competitiveness
Major competitiveness factors with relevant attributes are prepared. In this case, five key factors
are used (Ernst and Young, 2007)—city prosperity, urban governance, infrastructure, business
environment and quality of life. Using weighted
and aggregated scores from the five key competitiveness factors, a group of cities can be ranked
for their competitiveness, and national average is
calculated as the benchmarking score.
Step two: Evaluating the key drivers of cities’ competitiveness
From the result of step one, a city (or a cityregion) could be selected for its local economic
development. The technique in step one details
out strengths and deficiency gaps toward enhancing competitiveness of the selected city within a
country. This result will be matched with the infrastructure needs of the industry clusters, which
will be identified at step five.
Step three: Assessing structures and changing patterns of multisector industry in a selected city-region
Using the government’s standard industry classification, this step explores the profile of the industry; how the percentage distribution of local
industrial sectors in the city-region have changed
(using location-quotient and shift-share techniques), by comparing census data of at least five
years interval. It demonstrates which industry
sector is the largest contributor to the local economy, and how industry sectors have been growing or declining over time in the city-region. The
top three employment-generating industries in the
Delhi-region in 2005 were manufacturing (31%
of total employment), retail trade (25%) and services (16%).
Step four: Mapping the selected industry
clusters using GIS
Once key stakeholders determine which industry
is to be invested in to increase competitiveness,
those firms and enterprises in the selected industry-sector are geographically mapped out. This
result is useful for geographically locating clus103
ters in a city-region and for further infrastructure
supports by the government. In the Delhi-region,
automobile component manufacturing, general
machinery/equipment manufacturing and textiles
industry-clusters were identified under the manufacturing industry.
Step five: Analyzing competitiveness of selected industry clusters using Porter’s Diamond Model
Each selected industry cluster is analyzed for
its competitiveness using 39 attributes under
the five factors of Porter’s Diamond Model. For
example, in case of the textile industry-cluster
in the Delhi-region, out of the 39 competitiveness attributes, 72% have an average score of
less than 2.5 out of the maximum score at 5. To
compete at the international textile market, all
five competitiveness factors in the textile industry cluster in Delhi need to be improved above
the score of 3.66.
Step six: Preparing business and action plans
for the selected industry cluster
The results from step two and five provide useful information in what the deficiencies are to
strengthen the competitiveness of industry clusters as well as supporting infrastructure in the
city-region. Key stakeholders pursuing further
interventions, based on the analysis results from
the previous steps, prepare a business plan. Action
plans are also prepared laying out priorities and
urgencies to foster the competitiveness of industry
clusters, as well as infrastructure needed for the
selected industry cluster area. Pre-feasibility investment proposals can also be included for seeking investments by PPP, government or international development agencies.
The CCLED analysis framework provides a
strategic foundation that is useful to enhance
competitiveness of the selected industry clusters,
as well as helpful for informed decision-making
by the government to decide where and what infrastructure to provide first, for fostering local
economic development, important for Asian cities in the context of a rapidly-changing global
economy.
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Stimulating Transsectoral Innovation in
‘Mature’ Clusters
Eetgerink, Frank
East Netherlands Development Agency (Oost NV)
The region East Netherlands (two provinces)
accommodates three universities, acting as crystallization points of knowledge-intensive entrepreneurial activities and clusters. The clusters
are well established with cluster organizations
supported by the triple helix partners. Food Valley is built on knowledge from Wageningen University and Research (WUR). Health Valley is
located at the campus of the Radboud University
(RU) Nijmegen, close to the academic hospital
UMC St. Radboud. Innovation Platform Twente
is based close to the Technical University Twente
(TU). The three main cluster organizations are
connected through an innovation policy program
Triangle of the provinces Gelderland and Overijssel. Triangle aims at stimulating the synergy between the clusters through the funding of innovation projects.
Connecting the clusters there are three themes:
bio-based economy (combining agrofood and technology), food and health, and RedMedTech Highway (medical technology, imaging, biomedical).
These themes recently emerged out of the cluster
activities.
The regional innovation policy was quite successful in the last few years. The cluster organizations are in place and enjoy support and legitimacy
with the regional partners. At the national level,
the food cluster is best recognized. The flipside of
the coin is a tendency of clusters to institutionalize into ‘sectors’, which is in a way counterproductive to open innovation and ‘neue Combinationen’.
Clusters could develop into a state of lock-in, where
transactions become suboptimal.
The region needs sectoral and economic diversity to balance too much dependency on spearhead
sectors or big dominant companies. Transsectoral
innovations stimulate economic diversity, which is
by definition related to variety.
A question to answer could be: how can a region
stimulate related variety through transsectoral inJournal of Competitiveness
January 2011
novations, how to keep networks and clusters open
enough to prevent stagnation or lock-in?
A part of the answer can be found in analyses of
dynamics in alliances and the groups/teams involved
in open innovation projects. All sorts of multi-party
collaborations, combinations of partners, exist in
the triple helix. If we understand the dynamics in
such groups, the agenda building, leadership, patterns of processes better, we could intervene and
stimulate better.
The Triangle innovation policy grew out of
‘Knowledge Mapping NEW Triangle’ (NEW =
Nijmegen, Enschede, Wageningen). The starting
point was the assumption that if you can identify
‘hot’ spots of cutting-edge knowledge or technologies and the persons who are the leading and acknowledged experts in these fields, and, if they do
not know each other, you can connect and facilitate them in research programs. This will with high
probability lead to new combinations of knowledge
and can eventually lead to innovations through connected businesses.
This approach could be combined with the potential market drive of societal challenges relevant
for the main clusters, like ‘Feed the World’, ‘Renewable energy and sustainable production’, ‘Affordable health care in an ageing society’ etc. Or
a starting point can be a by definition be a transsectoral integrating theme, like Smart Living (ICT,
domotica, smart energy, care, building, technical
installation, etc.).
Another challenge would be the internationalization of clusters trough international cross sector
combinations of clusters. We are currently developing a European project under the Interreg 4B
scheme addressing this subject.
Clusters 2.0: How to Think Positive and
Think Big in a Crisis Period?
Estévez, Joan Martí
ACC1Ó, Catalonia Government
In Catalonia, cluster policy was started around
1993 with a focus on promoting strategic change
in the 23 micro-clusters (narrow approach in small
geographical areas) identified at that time. Since
January 2011
then, there has been an interesting evolution in
inter-cluster reinforcement—an open-cross innovation approach.
One of the most remarkable experiences we are
involved in is a corporate entrepreneurship project
with 20 cluster leaders of the clusters we are developing at the moment. Through this process we are
generating a new community of inter-cluster leaders (fashion, ICT, motorcycles, pharmaceutical,
food, etc.) working together, sharing interests in
new projects, which become new companies, having
these leaders as investors. The result is, basically,
the generation of new companies with an expected
high growth and a global reach, because they have
the powerful management skills and finance capacity of these leaders. These cluster leaders share the
view of thinking positive and big to get out of the
crisis through transformational projects.
Learning Clusters in Creative Environments
Haasis, Klaus
MFG Baden-Württemberg mbh
In our days the business environment that we
work in changes nearly every day. Globalization
causes developments that are hard to understand
and even harder to foresee, the financial crisis affects sectors you wouldn’t expect and two years
later business again develops faster than ever. To
cope and keep track with such developments doing
business as usual isn’t enough—not for companies
and at least not for cluster initiatives.
The classic cluster management approach needs
to be thought through and adapted. The Manifesto
of the European Year of Creativity and Innovation 2009 states that workplaces need to be transformed into learning sites. More than ever, this applies to cluster organizations. They have to support
their members in difficult times and open their eyes
for strategic future developments. New cluster approaches shouldn’t only be business-oriented, but
also need an empathic component focusing on individual persons. The presentation addresses these
challenges and will demonstrate how learning and
change processes can be organized.
105
We will look at two components that are essential for learning organizations, knowledge management and relationship management—knowledge
management to learn from and with each other,
and relationship management meaning to trust
each other.
Knowledge management
Peter Senge explains in “The Fifth Discipline: The
Art and Practice of the Learning Organization”
that a learning organization has to be skilled in
specific fundamental disciplines. He describes five
components a “learning organization” requires:
1. Personal mastery of one’s capacities
2. Team learning through group discussion of individual objectives and problems
3. Employees and managers are also encouraged
to examine together their often negative perceptions or “mental models” of company people
and procedures
4. Shared vision
5. Systems thinking
These principles support the “learning from and
with each other” in organizations. This concept not
only applies to organizations, but also to regions
and clusters. The presentation gives an overview
on how to adapt this very appealing concept to a
cluster environment and why cluster managers and
regional representatives will be well advised to implement it in their future strategies.
Relationship management
One aspect that remains a key element of all successful clustering approaches is relationship management and along with it the aspect of trust. Cluster actors need trust to learn from each other and
to benefit from collaboration and exchange.
Currently we find people cautious about sharing their knowledge and information with each
other—a development also mirrored in Europe in
public discussions on privacy issues of services like
“Google Street View” or Facebook. Boundaries
between open and closed, real and virtual become
more blurred. How do we deal with that challenge?
Creating a trustful environment for cluster organizations is a crucial first step that can be supported
by different approaches:
106
n Appreciative inquiry, a concept brought to life by
David Cooperrider, serves to analyze the strengths
of an organization and how to foster them. This
method promotes positive relationships and builds
on the basic goodness in persons, situations or organizations. That way it enhances a system’s capacity for collaboration and change.
n The person-centered approach from Carl Rogers, who was an influential American psychologist,
can contribute to create, ensure and increase trust
between the different actors. Carl Rogers has developed his own approach to understand personality
and human relationships, the so-called person-centered approach. This approach found wide application in various domains such as psychotherapy
and counseling, education, organizations and other
group settings. It can be used as an effective tool
for cluster management.
n Positive psychology by Martin Seligman and
Mihaly Csikszentmihalyi is a branch of psychology
that seeks “to find and nurture genius and talent”,
and “to make normal life more fulfilling” not simply to treat mental illness.
Using the example of MFG as a well-experienced
cluster organization (recognized as “Excellent
Knowledge Organization” by the Federal Ministry
of Economics and Technology) and the Creative
Industries in Baden-Württemberg, the presentation will demonstrate different practical examples
on how to make use of the concepts introduced in
terms of regional and cluster management.
Internationalization of regional innovation networks
Hyder, Akmal , University of Gävle, Sweden
Roxenhall, Tommy, Mid Sweden University
It is becoming increasingly common for networks of actors (universities, research institutes,
enterprises and government organizations, etc.) to
be formed in order to jointly develop innovations.
Such networks are often encouraged and financed
by regional and national authorities. However,
more and more innovations are created between
actors in the international arena. The regional innovation networks must therefore be able to atJournal of Competitiveness
January 2011
tract international operators and investors, and to
recruit individuals with key skills that are active in
the international market.
Studies show that regional innovation network
has established relationships with international actors, but few have knowledge of how to internationalize it (Vinnova 2008). Furthermore, ongoing
globalization creates new challenges for process innovation networks. Research institutions and companies are woven together in very complex networks
that cut across national boundaries. An increased
number of companies that are continuously looking for research expertise around the world create
considerable pressure on regional innovation networks to enable them to compete with the leading
innovation networks in the world. Paradoxically,
the regional innovation networks in their specific
areas of expertise collaborate with world-leading
innovation networks so that competitive knowledge
and skills are guaranteed.
In many cases, regional innovation networks are
working with many small businesses and they need
to attract more foreign companies as partners. This
is to help smaller companies to come out on foreign
markets with technology solutions and products
that smaller companies have developed in the regional innovation system. This is of course not an
easy task for regional innovation networks as there
are many competitive players active in the global
market seeking international outlets. This complexity also explains why many regional companies
with high technological potential fail to grasp a
satisfactory position in the international market.
It is our conviction that mere contact or certain
access to other foreign networks is not adequate,
regional networks need to establish some vital ties
with foreign partners for long-term collaboration
and development.
In general, there is a lack of knowledge about
how regional innovation networks are internationalized through collaboration with innovation networks in other countries. The purpose of this project
is therefore to study such processes. The hub of a
regional innovation network contacts their foreign
colleagues in order to create a partnership between
them by forming a strategic alliance. Once such a
January 2011
vital alliance is established, it becomes easier for
member companies to identify relevant partners
to establish different kind of contacts for getting
a foothold in the foreign market. By exploring the
knowledge on internationalization of regional innovation networks, this work can make a practical
contribution in organizing innovative companies
around hub of their local networks and get benefit of internationalization through long-term ties
(strategic alliances) established with vital foreign
partners.
Arizona Nanotechnology: Our Cluster
Strategy
Kim, Matt
QuantTera, Arizona
In general terms, nanotechnology, the science
of the small, involves research and development of
extremely small components and structures, and
transcends many disciplines. Semiconductor firms,
for example, have process geometries approaching
65 nanometers and require intense research and
development to produce high quality integrated
circuits at those extremely small dimensions. In
more specific terms, nanotechnology involves using
quantum properties that occur at very small sizes,
and by utilizing these effects that arise from small
dimensions it is possible to create structures that
have unique properties that are normally unrealizable in nature.
The presentation describes how the two main
categories of nanotechnology—nano-engineering
of the solid state and molecular nano-engineering—allow the formation of new types of manmade
structures and how it is possible to nano-engineer
the materials to enhance certain physical properties, with applications of these materials to energy,
biology and the environment.
With nanotechnology allowing for control and
tailor making of materials properties, its importance in Arizona, nationally and internationally
will be discussed. The Arizona Nanotechnology
Cluster promotes technology statewide for Arizona. How linkages to the general public, government
and other organizations make for an important and
107
necessary base for economic technology development will be described.
New Approaches towards Cluster Management Excellence
Köcker, Gerd Meier zu
Agency Competence Networks, Germany
Clusters provide fertile ecosystems for companies to thrive, which drives innovation, regional development and competitiveness. After many years
of efforts to develop clusters, the challenge today is
not to create more clusters, but rather to enhance
the competitiveness and sustainability of existing
and new clusters, and to create more dynamic clusters with global reach.
One of the key questions today is how to better promote clusters and how to make better use of excellent
clusters in response to societal challenges. This would
require shifting focus from supporting clusters to using them more effectively. Clusters are said to provide a more productive and innovative environment
for enterprises, and this could also be used to achieve
a higher impact of research and innovation support.
The issue is not to consider clusters as privileged or
even exclusive partners for finding better solutions,
but to build upon and exploit the cluster concept,
which is based on collaboration between companies
and research institutes and other institutions offering
knowledge to businesses. Thus, clusters and cluster
organizations must seek excellence in order to better serve the needs of enterprises and support their
competitiveness; this should be the baseline objective
of all cluster initiatives worldwide.
However, today enterprises and clusters face new
ways of dealing with innovation and management
of knowledge in order to be efficient and successful in a more open‐knowledge environment. Cluster
organizations play an important role in catalyzing
and facilitating action in cluster initiatives.
Promoting cluster excellence is of high relevance, especially for cluster managers. So far,
there are three approaches prevailing how to promote cluster management excellence.
n Benchmarking of cluster managements2
n European Cluster Excellence Initiative3
108
n Quality Frame4
Benchmarking organizational cluster management performance and the quality of cluster organizations is already an accepted approach within
Europe. There is clear evidence that benchmarking
can lead to much better results than conventional
evaluation approaches. As benchmarking has to be
understood as a voluntary comparison among cluster in order to stimulate mutual learning among the
involved cluster management, it is not a new type of
ranking or rating. Furthermore, it is not policy-or
scientific-driven.
The most common cluster management benchmarking approach was designed in 2007 by the
Agency of Competence Networks Germany, in order to enable measurement, assessment and comparison between clusters’ performance. Dedicated
focus is given to cluster organizations, but other
aspects related to the cluster framework conditions
and cluster actors are also regarded.
The benchmarking approach is based on seven
dimensions and 60 specific indicators:
n Cluster structure
n Financing of cluster organization
n Typology and governance
n Diversity of services offered by the cluster or-
ganization
n Output of services
n International orientation and visibility
n Achievements and reputation
Besides the practical approach, the quality and
completeness of the comparative portfolio, against
the individual cluster managements are compared,
is the key success factor for benchmarking. So
far, the comparative portfolio contains 85 clusters
benchmarked so far. All of them fulfill high quality
in order to be listed in this portfolio. Clusters from
various European countries are listed, like from
2 Meier zu Köcker, Rosted (eds.), Promoting Cluster ExcellenceMeasuring and Benchmarking the Quality of Cluster Organizations and Performance of Clusters, Conference Proceeding of
EC-Expert Workshop, 2010, http://www.clusterobservatory.
eu/index.php?id=102&nid=
3 http://www.cluster-excellence.eu
4 http://www.iit-berlin.de/veroeffentlichungen/quality-frame.pdf
January 2011
Austria, Denmark, Germany, Hungary, Norway
and Switzerland.
An additional key success factor for the recognition of the benchmarking approach is the following
aspects that are regarded in the current approach
n Cluster managements can be benchmarked
against pre-selected groups with specific characteristics (technological domain-wise, size-wise,
age-wise)
n A flexible approach allows to encompass the
broad variety of clusters and cluster initiatives
n A simple procedure consisting of a face-to-face
dialogue (max. half-day) between the cluster management and the Benchmarking Team
n The benchmarking is mainly addressed to the
cluster management. It doesn’t provide information whether a publicly-funded cluster initiative has
met the political objectives nor can substitute an
impact assessment
The main objective of the European Cluster Excellence Initiative (ECEI) is to gather key European organizations in order to identify and set up
quality indicators and peer-assessments of cluster
management. The ECEI aims at developing training materials and setting up a relevant approach
to label the quality of cluster organizations. Such
labeling is intended to support cluster managers in
achieving high levels of excellence and succeeding
in their peer-assessments. Besides, the ECEI will
Figure 1: The key areas of the European Cluster
Excellence Initiative
then create and act as a club of professionals and
institutions promoting cluster management excellence. Figure 1 reveals the four key areas.
Quality frame stands as quite a new approach,
which is based on a peer-assessment according to
January 2011
the internationally recognized EFQM-Model (European Foundation for Quality Management). The
presentation reveals the specific approach, how to
set up the peer review groups and results
European Clusters Go International:
Current Status and Key Success Factors
Köcker, Gerd Meier zu, Agency Competence Networks, Germany
Müller, Lysann, Agency Competence Networks, Germany
Zombori, Zita, POLUS Programme, Hungary
Creating stronger linkages between clusters
in different locations that offer complementary
strengths is one of the most promising ways to
get access to the most advanced technologies,
best know-how or relevant markets. Changes in
the global economic environment are also making
cluster linkages on the international level more important. As firms within clusters internationalize
their activities in creative ways, it is important that
cluster initiatives and organizations (which support
them) internationalize too. Policy makers on all
levels as well as cluster organizations give a lot of
attention and make considerable efforts in order to
better internationalize clusters and their firms. Although, as evidence shows, most actors involved in
clusters are interested in learning from and developing concrete activities with partners in other geographical locations internationally, there is still a
lack of knowledge about main barriers and drivers
as well as about the progress made so far. Future
policy supporting measures can only be effective if
the real demand of the cluster organizations and
cluster firms are known.
The findings presented here are the outcomes
of the second European cluster poll in which more
than 100 clusters from 11 countries participated.
Dedicated attention was given to involve mainly
matured and internationally-competitive clusters.
As the first poll was made in 2007 and the European cluster landscape and framework conditions
have changed dramatically, the current findings
show what has been gained within the last three
years and how the current challenges looks like.
109
The main findings can be summarized like following:
n Cluster organizations in Europe are taking over
more and more responsibility to actively support
their cluster firms in internationalization matters.
n The barriers and enablers for internationalization did not change much over the last few years.
Financial and personnel shortages are still the main
huddles, but quality of products and technologies is
still an important aspect.
n Whereas the existence of an internationalization
strategy was still an exception in 2007 (only 10%
of the participating clusters had have such strategy
set into force), nowadays more clusters have an appropriate strategy in force.
n Most European clusters made considerable progress in going international with often positive impact
on the business development of the cluster firms.
n There is clear evidence that cluster organizations
being in charge with internationalization matters
on behalf of the cluster firms perform much better
in this respect than clusters where the cluster firms
feel responsible to internationalize.
n Whereas good progress in initiating international
co-operations has been gained, little progress is reported of increasing international visibility and reputation. This is considered a considerable challenge.
n EC-funded projects with focus on internationalization matters have been very successful, if the
benefiting cluster organizations really have a mandate to support cluster firms to go international.
If not, those projects mostly fail and do not reveal
any positive impact on the cluster organizations or
respective firms.
Based on the statistical evaluation and deepening
expert interviews, there is clear evidence that cluster firms and cluster organizations tend to be more
successful in going international than others, if the
following key success factors are fulfilled:
n High competitiveness of the products and services provided by the cluster firms
n The cluster organization is officially in charge
and has a mandate to support cluster firms going
international
n The cluster (organization) has developed and
implemented an internationalization strategy,
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which is implemented and accepted by the cluster
firms
The presentation will discuss the findings mentioned and also reveal that there are considerable
country specific differences although mainly the
most competitive clusters have been invited to the
cluster poll. The findings are expected to contribute
to better understand how clusters and cluster organizations should internationalize, what the main
key success factors are and how policy makers can
better support clusters and cluster organizations
going international.
The authors are convinced that the main findings
are of relevance not only for the current situation
in Europe rather than for all clusters world wide
interested in internationalizing their business.
The Road to Prosperity is Paved with
Innovation: Embracing the Prosperity
“Value Chain”
McCord, Mark T.
Deloitte Consulting, LLP
USAID Jordan Economic Development Program
The presentation discusses the effects of innovation on the creation of prosperity, as well as a fivepronged methodology for promoting innovation.
This methodology focuses on business development,
research and development, access to financing, development of a world-class workforce, and creation
of an enabling environment that promotes innovation. This methodology is the common thread that
innovation-oriented countries have used to build a
culture of prosperity. The methodology is outlined
in order to promulgate the development of a prosperity “value chain”, the premise of which is that
innovation drives productivity, thereby building
competitiveness, which creates prosperity.
The major themes of the presentation are:
n Linking innovation and prosperity
A.If it isn’t broken, fix it anyway: The practical
definition of innovation Innovation is the practice of turning ideas into reality, thereby improving process, outputs and ultimately prosperity.
B. Begin with the end in mind: The groundwork for
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innovation is laid through the development of a
cohesive strategy that includes the involvement
of the public and private sectors as well as academia, and the implementation of the strategy
in an organized manner to promote prosperity.
C. Acceleration is the Key: Innovation accelerates
a country’s ability to achieve impact targets by
creating a culture of prosperity.
D. Innovation’s Dirty Little Secret: Countries that
are known for innovation must continue to innovate or they will not sustain the prosperity developed through implementation of their initial
strategies.
n The prosperity value chain
A. Innovation drives productivity
B. Productivity builds competitiveness
C. Competitiveness creates prosperity
D. Prosperity is sustained through innovation
The premise of the prosperity value chain is that
prosperity supports economic, social, and political
stability, countries must continue to innovate to
sustain prosperity, and that innovation must permeate society, which comes through a change in the
way citizens think about their quality of life, their
government, their economy, and ultimately their
value system.
n The innovation methodology
A.Develop a strategy: The development of an innovation strategy must include influential members of the public, private, and academic sectors,
as well as civil society. Until a cohesive strategy
is developed, other elements of the methodology cannot be implemented. The strategy should
include a focus on target sectors where innovation can make the country competitive and ultimately prosperous.
B. Develop a world-class workforce: Countries must
focus on core sectors and develop a workforce
within these sectors that will promote competitiveness. Development of the workforce has to
come before other elements of the methodology
in order to lay the foundation for success.
C. Develop a supportive enabling environment: The
catalyst for innovation can come either from
the private sector (as in the case of Nokia in
Finland) or the public sector (as in the cases of
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Ireland and New Zealand). However, a public
sector must collaborate with the private sector
to develop an enabling environment that supports innovation and ultimately the creation of
prosperity.
D. Business development: Innovation begins at
“home”, meaning that if local companies begin
to innovate, thereby moving up the prosperity
value chain, significant impact will be created in
the areas of job creation, revenue enhancements
and public support. This will create a “mass” of
innovative and competitive companies that will
in turn create opportunities for foreign direct
investment.
E. Support for research and development: For innovation to take root, a country must develop
significant support for research and development
by building alliances between the academic community, the private sector and the government.
F. Access to financing: Access to capital is crucial if companies and ultimately countries are
to move up the prosperity value chain. This includes, but is not limited to, start up capital, angel networks, research and development funding
and other mechanisms designed to promote innovation.
n Conclusions:
A.Prosperity trickles down not up: Countries
must focus on high value jobs that are created through innovative approaches in targeted
sectors. High value jobs will create economic
opportunities throughout the strata of society,
thereby increasing prosperity. The premise is
that poverty alleviation programs, which have
long been a staple of development in emerging
markets, will not build prosperity because they
do not promote innovation and/or productivity.
They do not build competitiveness, but simply
make countries “less poor”.
B. Innovation is like cellular division: Innovation
has to continue in order for countries to maintain prosperity, which means that mental models
have to be changed and that there must be broadbased support for innovation throughout society.
C. Every day without innovation is another day of
falling behind: The gap between countries around
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the world is widening. Therefore, it is time to stop
thinking about the development of an innovative
culture and move on with making it happen.
Cluster Research in Norwegian
Regions: The Case of the Norwegian
Water Cluster
Normann, Anne Katrine
Research Council of Norway
The presentation has two interlinked parts; one
is on the Program for Regional R&D and Innovation
(Norwegian acronym: VRI), which is the Research
Council of Norway’s main support mechanism for
research and innovation in Norway’s regions; the
other part is a presentation of a case study—the
creation of a water cluster, which has been funded
by this program. Here the method for developing
learning networks is central.
VRI is one of the main programs funding innovation and organization research. VRI encourages
innovation, knowledge development, and added
value through regional cooperation and a strengthened research and development effort within and
for the regions. The program’s time-frame is ten
years (2007-2017), and it offers professional and
financial support to long-term, research-based development processes in the regions. It is designed
to promote greater regional collaboration between
trade and industry, R&D institutions and the government authorities, and to establish close ties to
other national and international network and innovation measures. Fundamental components of the
VRI program include research activity, exchange
of experience, learning, and cooperation across
scientific, professional and administrative boundaries. Results of the funded research projects are
an indicator of the success of this kind of research
program and funding mechanisms.
Innovative networks and clusters have been the
subject of extensive research, while there is less research on how they develop. It is debatable to what
extent it is possible to impact on and manage the
development process of clusters. The assumption
here is that while it is not possible to manage, it
is possible to spark mechanisms that support and
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stimulate the cluster development process. This
must be done according to the participants’ needs,
and building legitimacy is a vital part of the process. Legitimacy and trust are intertwined. An assumption is that development of trust is essential
for the establishment of regional networks. Network IGP (individual, in group and in plenary) and
network reflections are methods that can develop
trust through organizing persons from different
enterprises to partake in individual and collective
reflection processes. These methods have proven to
have a positive effect on the development of innovative networks. IGP function as meeting places,
and implies that the participants are from different
enterprises; group work with persons from different
enterprises; people rotate for each group work so
that people that are new to each other have to collaborate. Optimal organizational learning processes are assumed to be achieved through a combination of individual and collective processes, which is
conducive to high levels of innovation.
The case is the water cluster in the VRI region of
Vestfold in Southern Norway, where 20 core firms
form the cluster. The research poses the question
whether social researchers can contribute directly
to the development of inter-firm networks, conducive to an industrial cluster. Furthermore, which
methods are adequate for facilitating networks
among knowledge-intensive small and mediumsized enterprises? The method chosen is decisive
for the process of developing networks. The method
needs to center on ways to impact on and develop
interpersonal relations. The nature of interpersonal
relations has an impact on innovation. It is not sufficient to be innovative in terms of products. The
production of services is rapidly expanding and it
is necessary to work smarter, and hence, process
innovation becomes increasingly more important.
Process innovation depends on abstract, tacit and
contextual knowledge. Such knowledge can only be
shared through interaction, and hence, the development of personal relations and social networks
can be an efficient innovation strategy. The nature
of interaction depends on, among other factors,
geographical distance. Geographical proximity
between enterprises makes interaction easier than
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long distances, but the innovative power of geographical proximity is under debate. For proximity
to stimulate innovation, the regional networks must
be knowledge-intensive, open to global knowledge
and global capital. Regional networks are essential to innovation, but they must be part of global
cooperation.
The water cluster as a project works towards
creating arenas and establishing networks in order
to increase the activity and strengthen the value
creation and innovation in water treatment enterprises. Social researchers have used network IGP
in an early phase of the development of the water
cluster. The water cluster has developed from being
a losely organized network with an interim board
without commitment for the enterprises, to be established as a project with an elected board. While
there initially was skepticism towards group work,
reflection processes are now in demand at the cluster’s meetings.
Balancing Bottom-up and Top-down
Cluster Activities: The Case of North
Rhine-Westphalia
Rehfeld, Dieter
University of Applied Science, Gelsenkirchen
In 2007, the federal state of North RhineWestphalia launched its new and in our view
very ambitious cluster strategy focusing on 16
sectoral clusters and related professional cluster
management infrastructures. While some of the
clusters where upgraded from successful regional
to federal state clusters, others are based on sector initiatives or focus completely new thematic
areas.
In doing so the North Rhine-Westphalia approach combines top-down and bottom-up activities. It tries to balance key performance indicators
on the one hand and to base on a strong commitment by the companies and their self organisation
on the other hand. Doing this, different institutional settings have been established, each with specific
strengths and weaknesses.
The presentation will begin with an introduction
of the North-Rhine Westphalia cluster approach,
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its institutional and strategic settings. This introduction will be followed by a discussion of key challenges and questions that arose in the course of the
first three years namely:
n How to balance regional and federal state interests and activities?
n What set of functions is needed and who pays
for it?
n How to balance the need of strategic orientation
and the requirement of openness facing short-term
new challenges?
n How to evaluate young cluster initiatives that
aim at long standing impacts?
n How to organise cross-cluster management with
clusters based on very specific sector and cultural
backgrounds?
Summing up, the strengths and weaknesses of
the North Rhine-Westphalia approach will be discussed.
Development Challenges in Networking/Partnering/Clustering Management
Rezec, Irena
Wotra Ltd
The networking/partnering/clustering approach
is of extreme importance for competitiveness, however only with a duly selected form or type of networking/partnering/clustering in relation to a specific problem or vision of a company. At the same
time, with the right management that considers both
the different aspects of networking/partnering/clustering as well as the trends in the environment and
together with this also introduces suitable methods
and tools used among individuals in a selected connection. In practice, numerous combinations are of
course established, and the influence alone of these
combinations on management or even development
of suitable tools has not yet been systematically researched. Different combinations of the elements evident in the following graph substantially affect the
selection of suitable management, and all together
affect the final success of any networking/partnering/clustering forms.
Companies face the issue or search for suitable
ways to reach their goals, strategies and visions on
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a daily basis. Networking/partnering/clustering is
without a doubt one of the strategies that can be
used in various cases for various purposes. However,
a company usually does not possess such knowledge
on the appropriate networking/partnering/clustering form or later the implementation. Governmental
support usually refers either to clusters or technological platforms, while the other forms are practically not promoted. This is appropriate in certain
cases, but from the viewpoint of consultants and
companies, this is at the same time also a “trap”, as
especially small and medium-sized companies do not
decide at the same time or only also for other types
of networking/partnering/clustering, which might be
even more appropriate for their own cases. The appropriate form or perhaps more forms of networking/partnering/clustering at the same time, as well
as management adapted to this has a important influence on the development or even competitiveness
of an individual company or a group of connected
companies.
The next question that arises in the process of
networking/partnering/clustering is connected to
various aspects of networking/partnering/clustering,
which can be classified under general managerial
aspects (e.g. legal-formal, financial, HR, etc.), and
numerous other aspects, among which are regional,
sector-based aspects and the aspects connected with
the basic purpose of networking/partnering/clustering, i.e. the interest or economic aspect, innovation
aspect, knowledge-sharing aspect, perhaps the aspect of internationalization, etc. This is actually the
central element of connecting that originates from
the purpose of networking/partnering/clustering,
and also substantially affects the selected networking/partnering/clustering form, networking/partnering/clustering management, the selection of methods
and tools, and others.
If we analyze the needs for the appropriate
management style or the necessary methods and
tools with regard to the current phase of the lifecycle of networking/partnering/clustering development, or if we analyze the trends in the environment for all previous elements of the model
or trends in relation to the selected combination,
we perhaps get the recommended business, orga114
nizational and managerial model and the recommended methods and tools.
Researching combinations that originate from
the research model bring numerous new questions
to light, as well as new development challenges of
the networking/partnering/clustering management,
for example:
n Can we similarly to technology transfers, where
we can successfully transfer technology even from
one sector into a completely new, seemingly noncomplementary sector, develop also a business, organizational or managerial model of networking/
partnering/clustering and related methods and tools,
which is transferred from one networking/partnering/clustering form into a completely different networking/partnering/clustering form even for a different purpose? Can we learn something from good
or bad practices, good or bad training programs, or
applied methods and tools introduced in strategic alliances, and transfer part or all of these experiences,
good practices, methods and tools to clusters or perhaps technology platforms, cooperatives, etc. If yes,
in which cases and in what way?
n In what way and which trends should be monitored, or which are the trends that most affect the
management and methods and tools in a network?
n Which methods and tools will be necessary for
successful networking/partnering/clustering of companies or networking/partnering/clustering management in the future, and do potential governmental
initiatives for the development of these methods and
tools meet the trends?
n In what way should companies, consultants and
also those offering governmental or other support
to companies be taught that the issue of networking/partnering/clustering is complex, and that it
therefore should also be treated this way, and that
professional management correspondingly qualified
for networking/partnering/clustering management is
necessary especially for some individual networking/
partnering/clustering forms or perhaps according to
an individual combination of elements evident in the
graph?
There are many other questions and development
challenges arising, yet all probably demand more
managerial dynamics than what we are used to.
January 2011
Links between Business Competence
and Learning Networks: Theoretical
Model
are the links and interaction between these two
concepts.
Rissanen, Riitta
Savonia University of Applied Sciences, Finland
Funding Innovation in Atacama, Chile:
Where the Money Comes From
Business competence and capability to use and
create knowledge in learning networks are in a key
role among business leadership skills. Especially,
past research in management (Nonaka, von Krogh
& Voelpel, 2006; Doz & Kosonen, 2007, Prahalad
& Krishanan, 2008) emphasizes the meaning of
strategic competences, learning, networking and
innovation as a success factor in various business
contexts. Earlier studies have found the connection
between dynamic capabilities and organizational
learning as a source of innovation-based strategy,
where management can effectively coordinate internal and external competences and create new
competences (Teece, Pisano, Suen, 1997; Zollo &
Winter, 2002). Furthermore, empirical research
results show (Ritter, 1999), that such factors as
availability of internal resources, network orientation of human resources management, integration
of communication culture and openness of corporate culture, influence a company’s network competence.
Learning organizations (Senge, 1990) and networks (Tidd, Bessant, Pavitt, 2005) have a key role
in sharing knowledge and learning to design alliances. In successful alliances, the people-related
factors or competences, for example creation of
trust and informal networking, are significant.
The theoretical orientation of this paper encourages diverse approaches of business competences,
learning networks and innovation performance,
into to the same field of discussion, in order to lay
the foundation for later empirical testing. This paper aims at giving a conceptual basis of “business
competence” and “learning network” for future
empirical research, as well as attempts to identify
the components of a theoretical model.
This study attempts to answer the following
questions—how the concept of business competence
and the concept of learning network is defined and
verified empirically in previous research, and what
Implementing competitiveness programs and
innovative initiatives with a regional and local
perspective, sometimes represent problems that
go far beyond putting in place perfect methodologies and to have in place social capital, because
what it is needed in practice is funding in order
to put in place actions and projects that would be
able to keep the energy of the process and the confidence of both the private and the public sector.
Atacama Regional Government, under the Innovation Fund for Competitiveness (FIC), released the
first public competition to fund innovative projects
to promote and develop economic and institutional
environments that encourage innovation in the region.
In a process never held before, the Atacama Regional Council, through its Commission of Science
and Technology, the Regional Government and the
Regional Development Agency (ARDP) developed
the basis of a contest that responds to a vision of
the requirements of the territory and innovation
needs of the region.
In this contest may participate universities
(state or recognized by the state), or institutes,
technology centers, public or private, having suitable human and material resources as well as experience in research, technological development,
transfer and technology diffusion, and whose main
activity is research, technological development and
transfer and technology diffusion.
The projects should be framed in the axes defined as strategic by the Regional Government,
which are contained in the Regional Innovation
Agenda 2010, prepared by the ARDP, after examination and evaluation of regional experts. The initiatives presented in this contest, shall be designed
to promote science, applied research, innovative
entrepreneurship, development, dissemination and
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Salvador, Marynella
Atacama Regional Development Agency, Chile
115
technology transfer, including for the strengthening of regional innovation networks, training and
attracting skilled human resources, infrastructure
and equipment support and promotion of culture
towards innovation and entrepreneurship.
In the case of the Atacama region, the overall
amount available for this item is $ 671,633,100,
approx. 1.4 million dollars.
The FIC is a financing tool for the implementation of national and regional innovation, aimed at
strengthening the national innovation system and
in regions, providing transparency, flexibility and
strategic direction for public action by the State.
Thus, this fund is the main instrument to provide
new and additional resources to the various efforts
that the State is doing around innovation.
With this orientation, the instrument is joining
the regional institutions in the process of strategic
decision on the issue of innovation and resource allocation, under the leadership of the Regional Governments (Gores), from the provisions of the Budget Law Public Sector, which states that they define
the destination of the resources available, taking
into account the National Innovation Strategy for
Competitiveness, the respective Regional Development Strategy (ERD), the Strategic Innovation and
Improvement Plans Competitiveness (PMC).
From the point of view of local innovation and
competitiveness, this case marks a milestone for
decentralization in the management of public funds
with resources from the FIC. On the one hand,
accredited institutions can submit projects that
strengthen regional capacities and networks for innovation, training and attracting skilled human resources, infrastructure and equipment support and
promotion of culture towards innovation and entrepreneurship. On the other hand, is in innovation,
where indicators of competitiveness place Atacama
in eighth place (2008 SUBDERE Competitiveness
Indicator), the percentage of public funding allocated to I+D+ is relatively low, of the 15 regions
occupied last, there are 21 doctors, which places
it at number 13; not file patents which places it in
last place, along with three other regions.
Therefore, we are working of the quartile model:
government, private sector, technological institution
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and financial issues, in a technical model that acknowledges the gaps and constraints that currently
exist in the region to innovate the requirements for
a qualitative leap and streamline—a model that
recognizes the particular character of innovation
according to a regional but global vision, and has
also been built on the basis of an agenda that was
elaborated with a bottom up technique.
Thus, through this competition, the innovative
culture will be strengthened, implementing and
transferring methods to activate the regional system, generating elements to balance economic development depending on the conditions of the territory in respect of water, energy and environment.
It is being considered that people are important
for innovation and competitiveness so it is important to attract, develop, strengthen and maintain
skills, promoting, inter alia, training initiatives and
advanced technical work for innovation through
programs—construction and updating maps of applied skills in the regional productive sector, set
of researchers in industry, specialized internships
and technological development, dissemination and
transfer of best business practices in innovation.
These are some of the lines to which institutions can access a proposal that is expected to be
welcomed and represents a clear effort to shift towards decentralization of productive innovation,
towards increasing business initiatives to improve
productivity and boost the regional economy on a
sustained basis as a contribution from Atacama to
a more developed Chile in 2020.
Emerging Business Clusters in Russian
Toys and Baby-Goods Industry
Sheresheva, Marina, State University - Higher School of
Economics, Russia
Gorokhov, Dmitry, State University - Higher School of Economics, Russia
The purpose of the paper is to analyze the case
of building relationships within the Russian toys and
baby-goods industry. After all the macroeconomic
and political changes of the past decades in Russia,
the industry was heavily damaged. At the beginning
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of the decade Russian toys and baby-goods producers seemed to have no competitive advantages at
all. Their market share has fallen to less than 10%
of the fast growing Russian toys and baby-goods
market (14 to 20% per year).
The situation in the market began to change recently. The most active firms of the industry started to build intensive relationships aiming to raise
competitiveness in Russia and abroad. Russian toys
and baby-goods producers and retailers started to
create win-win situations considering each other as
collaborators, not as adversaries. There are some
obvious results of such activity. Relational assets
built by actors that now appraise the role of intensive relationships helped them to strengthen their
consolidated position and to gain governmental
support of their initiatives as well as to create new
value by combining complementary assets and key
competencies.
The paper presents the results of preliminary
research carried out by means of in-depth interviews conducted with top managers, as well as
interviews with industry experts. The study is
based on the IMP network approach that offers
a solid ground to observe network relationships
in which economic actors are involved. Looking
at the changes in the industry and analyzing the
recent evolution of inter-firm networking, we aim
to find out which forms of long-term relationships
are the most promising for the industry in modern
conditions. What forms of inter-organizational
cooperation can better help Russian toys and baby-goods enterprises to gain sustainable competitive advantage and to fight the problems brought
by the world economic crisis?
The paper is organized around the following
topics. Firstly, it focuses on the literature on the
subject, followed by a brief overview of the developments in the Russian toys and baby-goods
industry pointing out some industry-specific and
country-specific features and showing the trend to
reappraisal of long-term inter-organizational relationships, regarded now as one of the main factors
of success. It also aims to discuss some results of
the research paying main attention to recent initiatives in clustering and their possible effects on the
January 2011
competitiveness and profit-generating capacity of
cooperating actors.
What is the Role of Government in Creating Prosperity in the New Economy?
Singh, Indira
Ontario Mineral Industry Cluster Council
Governments around the world aspire to create
prosperity for their citizens but, over time, very few
have been successful in achieving and sustaining
this goal. The presentation will focus on what constitutes prosperity, what are its key components,
and how governments can activate and harness
them. In this context, a number of government policies, programs and interventions will be explored
and presented to illuminate the pivotal role of governments at the federal, provincial, and regional/
municipal levels as they participate in the creation
of enduring prosperity.
Internationalization Initiatives within
Clusters: Both the Means and the End
Solé, Albert
Cluster Development, Barcelona
Boosting exports is usually seen as one of the
top goals within a cluster. Not surprisingly, a group
of local companies within a region and a value
chain is better equipped to compete in the global arena when cluster dynamics are in place and
SMEs tackle strategic common needs collaboratively. Nevertheless, internationalization is more
than that. Field experience increasingly tells us
how clusters turn to internationalization in order
to strengthen cluster strategies that will improve
and sustain overall competitiveness. Just like the
‘cluster’ concept, internationalization therefore becomes the ‘means’ to an end (competitiveness), not
an end in itself.
The focus of the presentation is to demonstrate
the above by means of cases and examples that allow the audience to familiarize them with cluster
practice cases, and get inspired by the ongoing applications of cluster initiatives worldwide.
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Two key concepts discussed are internationalization as the ‘means’ to strengthen cluster strategies, and internationalization and access to global
markets as the natural goal of any cluster. Internationalization sustains and enriches the execution
of the strategies for the future by improving the
value chain of its member companies with international initiatives and alliances. On the other hand,
in an increasingly globalized economy, the international component must be inherent to any cluster’s
strategic plan. In a cluster development project,
companies are more confident and committed to
collaborate in non-local markets. Both these things
are done with the ultimate goal of increasing competitiveness in a global context.
The presentation introduces examples in the following two areas, classic export-oriented set and
more strategy support ones.
Initiatives to increase sales by expanding into international markets
n International public procurement
n institutional support to foster Cluster initiatives
in strategic countries
n Inter-cluster collaboration in third markets
n Representation in strategic markets
Initiatives to reinforce strategy
n By strengthening competitiveness along the value chain
-Delocalization of phases of the value chain
-Joint productive internationalization
n By innovating in product design and manufacturing
-Penetration of markets with sophisticated demand (test your product or service)
-Partnerships, alliances and consortiums with
companies of superior know-how or technology on
international projects / programs
-Gain access to the consumption habits of the
end consumer in order to innovate in product/service
n By excelling at the raw materials sourcing
-Grant access to key raw materials
Special attention is given to cross-national, inter-cluster collaboration, a field where cluster de118
velopment is increasingly getting involved throughout Europe. The case of solar power clusters in
Spain and France that collaborate to penetrate
third countries around the Mediterranean basin,
taking advantage of geographical and cultural
links, with complementary specializations along
the value chain, and the establishment of European
decision-making institutions being headquartered
in both Barcelona and Marseille.
In addition, a third section explores how regional development agencies can support the internationalization process of companies and how clusters facilitate this public-private effort. Based on
four years of experience being in charge of sectoral
policies at the Catalan Competitiveness Agency,
examples of how a cluster approach had helped
the agency to tackle initiatives that were in fact
in position to better assist the real strategic needs
of the companies, and optimized public resources
to support the companies’ long-term strategies are
introduced.
Long-term Sustainability of Cluster initiatives: The Cluster Innovation System
Solé, Albert
Cluster Development, Barcelona
Cluster Development’s high degree of specialization and the fact that, throughout its history, the
firm sustained long-term relationships with a wide
array of public-sector clients has gradually triggered the materialization of cluster development
projects that, because of its approach and nature,
are at the front line of the cluster arena at present
times. That is to say, experienced clients with cluster experts on their teams (from regional governments to local development agencies) increasingly
require to take the cluster concept one step forward, defining solutions to guarantee the cluster’s
ability to collaboratively identify and implement
those initiatives that better serve winning competitive strategies.
Generally speaking, clusters are developed following this basic methodological process:
0. Strategy development: Shared vision and discussion on the strategic focus of the cluster
January 2011
1. Cluster activation: Formalization and articulation of the cluster, with transfer of leadership
from the sponsor of the initiative to cluster companies and institutions
2. Cluster innovation system: Systematization of
promotion and management of projects within
the cluster and consolidation of the visibility
and international positioning of the cluster
Step number 2 will be the goal of the presentation. Those cases in which the cluster manages and
participating companies and institutions manage to
sustain the innovation-driven collaborative dynamics, to later draw the theoretical conclusions based
on field experience (not the other way around) will
be outlined. Often times we see how a cluster initiative successfully manages to kick-start the process
and captures the ‘momentum’ to deliver short-term
action initiatives. The real challenge, though, is
how to bring into the formula the proper structures, leadership and support to do that on a regular basis, and without missing the strategic focus
the cluster needs.
Given that Cluster Development SL works with
both emerging and mature clusters, it is with this
second group particularly that we have learn the
dos and don’ts of long-term cluster dynamization,
and the purpose of this presentation is to convey
our learning experience in this field.
How to establish a cluster innovation system
The training of the cluster manager is not enough to
guarantee that the cluster faithfully follows a roadmap towards the shared vision and, more so, that it
is able to reinvent itself and refine the strategy as
inescapable changes take place in global business.
It is not a matter of the cluster manager’s ability
alone, as that ‘roadmap’ is seldom a detailed plan
that goes beyond the first year of implementation.
Rather, the enduring cluster operations and processes require that a specific set of ingredients are in
place in order to foster the continuous mushrooming and implementation of strategic projects within
the cluster. Therefore, it is imperative to establish
a working methodology that goes beyond the mere
facilitation of group discussions. This methodology
will have to encompass three basic areas and three
January 2011
different phases towards the generation of strategic
projects:
Area 1: Strategic content
The strategic content deals with the ongoing ability to continuously identify, structure and develop
those key areas of special interest for cluster companies that better support the strategic framework
agreed upon during the activation of the cluster.
Unlike other tools used to identify the current strategic position of a cluster (often criticized for being
too ‘static’), the proposed working scheme has to
do with building on successes and failures of previous years. The strategic content must noticeably
influence the annual calendar of cluster activities
and projects.
Area 2: Process
The process development has a dual objective—
among cluster companies, first, and internationally speaking as well. Often times the local value
chain is not comprehensive enough, forcing us to
look overseas and to establish strategic alliances
among clusters in order to develop state-of-the-art
or excellent projects.
Area 3: Communication
The communication process is key to the cluster’s
national and international visibility and to facilitate the integration of new members and to establish linkages with other clusters and international
networks of experts.
The methodology is divided into three phases,
each one consisting of different tools to generate
content, to establish a cluster’s network of innovation (process), and for the visibility and positioning
of the cluster (communication). The phases are the
following:
n To establish a technology monitoring and competitive intelligence system
It has to do with the definition and updating of
strategies for the future of the cluster. It is nurtured
by the continuous exposure to business trends and
international best practices that may influence the
key success factors within a business segment. This
activity does not need to be done constantly, but the
119
platform for debate and discussion must be taken
into account.
n To reach consensus on and definition of the different areas to develop
n To identify and select those projects that must be
pursued immediately because either they represent
short-term opportunities or because of strategic
relevance
n To establish a process for the execution of projects
The project management process of those projects identified in the previous phase has to be specific, measurable and duly timed. It has to allow
for a diversity of company typologies (with different
capacities and resources) to participate according to
the initiative, main objective and included tasks.
Improving Competitiveness and Innovation Through Better Cluster Management
Stürzebecher, Daniel
Project Manager, Cluster Excellence, MFG Baden-Württemberg mbH
How can cluster initiatives be managed professionally? And what skills do cluster managers need
when striving for cluster excellence? These questions are being explored by the consortium around
Cluster-Excellence.eu—the European Cluster Excellence Initiative, a PRO INNO Europe Project
lead by IESE Business School, University of Navarra. Thirteen project partners from nine countries—all well experienced in the field of cluster
management and support—create a uniform set of
cluster quality indicators and develop a label for
promoting excellence in cluster management. The
European Cluster Managers’ Club and the ClusterCollaboration Platform set up within the framework of Cluster-Excellence.eu are modules to foster excellence in cluster management.
Today, everybody can claim him or herself to be a
cluster manager. While management at the company level has been developed as a science by business
schools across the world, the skills needed for cluster
management are still in a nascent stage. They are
120
only transmitted from master to apprentice based
on experience on good judgement in codified knowledge. Cluster excellence means a more efficient
cluster management that follows a methodological
approach. Needless to say that better cluster management not only serves the companies involved but
results in a more efficient use of public funds provided through cluster organizations. All modules of
Cluster-Excellence.eu, therefore, target those cluster organizations who want to become excellent.
In order to make clusters competitive, the excellence of cluster management organizations has to be
improved based on the given framework conditions.
The promotion of high quality standards of clusterrelated activities and services could be one of the
main approaches to make cluster management more
efficient. But to translate this overall goal into reality, a precondition is to make excellent cluster management measureable before it can be improved.
Cluster-Excellence.eu thus is structured around
a set of indicators that will define “quality cluster
management”. The cluster quality label developed
within the project will be based on these indicators.
The overall approach is to create an independent,
voluntary proof of cluster management excellence
that is accepted and recognised all over Europe. The
quality label will motivate cluster managers to compare with each other and to learn from the best. It
is applicable for all different types of clusters existing all over Europe and will enable cluster managers
to demonstrate their excellence towards interested
third parties like members, stakeholders and policy
makers. The following aspects are important to point
out, in order to clarify the intention of the label:
n The quality Label focuses on cluster management, not on the framework conditions or a cluster
as such.
n It is based on a modular set of quality indicators
and a transparent process of how to benchmark
them.
n The quality label is voluntary and enables cluster
managers to receive proof of their cluster management excellence by an independent third body according to clear indicators.
The European Cluster Managers’ Club and the
European Cluster Collaboration Platform, both
January 2011
modules in the framework of Cluster-Excellence.eu,
will support and promote the adoption of the label.
The Club will be the first professional association for cluster managers striving for excellence.
It will provide different services to improve cluster
managers’ skills. These range from the promotion
of the label and the training materials to tailored
activities like workshops and case studies on issues
of special concern for cluster managers.
Clustering in the Republic of Macedonia
Trajanoska, Nikolina
Ministry of Economy, Republic of Macedonia
Clustering represents a new, fairly unknown
method for economic development and business partnership in the Republic of Macedonia.
According to the research, three factors can be
identified that are critical for the development of
successful clusters in the region:
1. The presence of functioning networks and
partnerships
2. A strong innovation base, with supporting
R&D activities where appropriate
3. The existence of a strong skills base
Assessment of current situation
The process of clustering in the Republic of Macedonia started in 2002 with the support of USAID
project Macedonia Competitiveness Activities
(2002-2006).
2002: Mapping, identification of potential clusters
Conclusion from the mapping exercise: Culture
of cooperation is low but there are groups with
potential for cluster development
Strategic decision: “Bottom-up approach”,
learning by doing
2004: Pilot projects
Start with the pilot projects, invitation for the interested groups to become pilots
Selection of five projects with the highest interest and potential
2007/2009: Cluster policy design (Ministry of
Economy)
January 2011
Cluster development program
Direct measures:
n Incentives for networking: Specialization in
valued/production chains, development of technology networks
n Promotion of networking: Network of experts,
management support in development of “local
clusters”, experiences exchange
n Incentives for cluster development: Support
for initial phase (one year), support in development (two years)
Indirect measures:
n Incentives for investment in R&D: Industrial
research, technology investment for groups of
companies and R&D institutions
n Incentives for productivity increase measures:
Introduction of new management tools, quality
standards and continuous improvement systems
in value/production chain
Several cluster initiatives are already operating in Macedonia—textiles, information technology, wine, tourism, lamb meat, sheep cheese,
agricultural mechanization, automotive components, wood processing, food-processing, fashion
design, etc. These clusters are at various stages of
development and as such need specific support to
further accelerate their development.
The key weakness that all existing Macedonian clusters share is a lack of potential for innovation, development of new products and services
to compete better in the global markets. Existing
clusters have mainly been created with the purpose of “grouping of small enterprises” to better
sell on the markets and have done much less in the
area of sharing and creating economies of scale
in purchasing, applicable research and development and innovation. Big companies are generally not active members of Macedonian clusters.
Analysis of successful clusters around the world
shows that successful clusters gather, apply and
expand knowledge and create innovative solutions
to business challenges. These qualities of clustering still need to evolve in Macedonia.
According to the survey, Macedonian firms
would highly appreciate policy measures oriented
121
in the enhancement of collaboration in networks
and clusters regionally and internationally (5.26
on the scale between 1 and 6).
According to the interviewees, the most
promising areas for networks/clusters in Macedonia are the food industry (35.3%), agriculture
(39.4%), tourism (23.5%), winery (20.6%), textiles (18.6%), IT (18.6%), etc.
Macedonian companies exhibit the highest
intensity of cooperation (networking) with their
suppliers (score of 3.71 on the scale between 1 =
weak and 6 = strong). The intensity of cooperation with the customers is not far behind (3.67).
As expected the intensity of cooperation with
competitors is much lower (2.23). In all three
kinds of cooperation the exchange of information
is the expertise, training and joint development
of products/services. In the case of cooperation
with competitors, there are possibilities of joint
purchasing and joint marketing, but this proved
to be less customers is stronger in the case of
majority foreign-owned than majority domesticowned firms, and in the case of export-oriented
than in domestic-market-oriented firms. Thus, it
seems that export market orientation stimulates
cooperation/networking with other firms and that
foreign-owned firms are more aware of the benefits of networking.
Measures
The following measures for collaboration in clusters and networks are introduced by the government:
1. Further awareness raising and training for
clustering/networking: Awareness raising
activities will be implemented by seminars,
regional and international conferences and
match-making events. Knowledge about
clustering and cluster management will be
strengthened by training sessions and international knowledge and experience exchanges.
2. Support cluster analysis and strategy development accompanied with action plan and specific projects: Cluster analysis and strategy
development will be supported by the govern-
122
ment together with action-oriented initiatives
mobilizing a set of strong leaders from business, government and universities in a process
that will enable competitiveness of Macedonian clusters. Specific development and international cooperation projects of clusters would
be co-financed by the government.
3. Supply chain partnerships acceleration: To improve the competitive position of the Macedonian industry, stronger supply chain partnership
led by key exporters needs to be created. Groups
of companies that co-operate as buyers and suppliers will be invited to apply for co-financing
of analysis of existing supply chain and joint
projects. Such projects can deal with variety of
their business challenges, for example “on time
delivery” implementation, better positioning on
the wholesale or retail markets, implementation
of common information system to track orders,
inventory, etc.
4. Stimulation of, technological centers and parks
on the regional level, support of networks of
R&D institutions to provide a variety of applicable technological services and integrated
and efficient innovations: Members of such a
network are to become a complete network of
highly-qualified individuals and advanced technological infrastructures driven towards promoting a solid and competitive industrial web.
Expected results
Implementation of policy measures in clustering
and networking will lead to the improvement of
understanding of the positive effects of clustering
and networking for the Macedonian industry.
Governmental support to clustering and networking will emerge throughout the public-private dialogue, which will be beneficial for both,
the public and private sector, to better overcome
challenges of collaboration.
Implementation of policy measures (supported
by the government as well as other donors, EU
programs and funds) will contribute to the creation of demonstration clusters as best practices
for future innovation-based clustering.
January 2011
The Role of International Cluster Cooperation in Increasing the Prosperity of
Regions
Tõnnisson, Rene
Baltic Innovation Agency, Estonia
When in 1776 Adam Smith published his seminal
work Wealth of Nations, his intention was to examine what makes nations prosper, but incidentally he
also laid down the foundations of classical economic
theory.
Based on some empirical experiences the presentation examines what role clusters play in making their
regions prosper and more specifically what is the role
of international cluster cooperation in this respect,
defined in the current presentation as intentional and
structured attempt for internationalization.
The presentation focuses on the ways how clusters and cluster initiatives that are strongly engaged
in international cooperation can contribute to the
increase of prosperity in their own and other cooperation regions. It particularly focuses on innovative
cluster-based international cooperation approaches
as new ways to stimulate prosperity.
The presentation includes the firsthand experiences gained from such innovative cooperation projects like European Business and Technology Center (EBTC) in India, iRegions (Internet-based and
mobile technologies for regions in the net economy),
CLOE (Cluster Linked over Europe) and also reflects
on the policy discussions and recommendations by
the European Cluster Policy Group in this area.
Special mentions
Al-Zo’ubi, Kawthar A., Ministry of Planning and
International Cooperation, Jordan; Asra, Sunil,
January 2011
MDI, India; Ba, Ibrahima, PCE-USAID; Breault,
Bob, Breault Research Organization, USA; Cavanagh, Stephen, Auckland Tourism, Events, Economic Development Ltd, New Zealand; Chaplin,
Gareth, New Zealand Trade and Enterprise; Chaplin, Gareth, New Zealand Trade and Enterprise;
Eklund, Lars, The Scandinavian Competitiveness
Group, Sweden; Enright, Michael, Enright Scott
and Associates, HK; Ffowcs-Williams, Ifor, Cluster Navigators Ltd, New Zealand; Frater, Paul,
Green Chip Ltd; Fuller, Cliff, New Zealand Trade
and Enterprise; Gulati, Mukesh, Foundation for
MSME Clusters, India; Gupta, V. K., MDI, India;
Hagenauer, Simone, EcoPlus, Austria; Johansson,
Cecilia, Vinnova, Sweden; Korpi, Anna, EduCluster Finland; Koziarski, Alan, New Zealand Trade
and Enterprise; Kunt, Vedat, Vego Consulting,
Turkey; Lalis, Georgette, European Commission,
DG Enterprise and industry; Lehmacher, Wolfgang, GeoPost Intercontinental; Maini, N.K.,
SIDBI, India; Markkanen, Mikko, Business
Arena, Finland; Marsé, Marta, Government of
Catalonia, Spain; Mittal, Manoj, SIDBI, India;
Montoya, Manuel, CLAUT Automotive Cluster
of Nuevo Leon, Mexico; Nawangwe, Barnabas,
Makerere University, Uganda; Pamminger, Werner, European Cluster Collaboration Platform and
Clusterland Upper Austria; Ribas, Eduard, Cluster
Development, Spain; Sarkar, Tamal, Foundation
for MSME Clusters, India; Shah, Jagat, Cluster
Pulse, India; Sorvari, Rauli, Regional Council
of Central Finland; Subirà, Antoni, IESE Business School, Spain; Taylor, Joy, Desert Knowledge
Australia; Wade, Ibrahima, SCA, Senegal; Waelbroeck-Rocha, Elisabeth, BIPE, France; Walker,
Richard, Economic Development Australia
123
Institute for Competitiveness, India
An international think tank dedicated to conducting meaningful research in
the core fields of strategy, economic development, productivity and prosperity, the Institute for Competitiveness (IFC) works to put together a body of
knowledge that encompasses economic distribution, business environments,
distribution of wealth and enhancing productivity.
IFC is affiliated with the Institute for Strategy and Competitiveness at the Harvard Business School and is dedicated to enlarging and disseminating the body
of research and knowledge on competition and strategy as pioneered over the
last 25 years by Professor Michael Porter.
Publications
City Competitiveness Report
District Competitiveness Report
Livability Index: The Best Cities in India
State Competitiveness Report
Newsletters
India Immersion
Think Competitiveness
Upcoming
India Economic Quarterly
Innovation Index for Indian Firms
Parliamentary Constituency Competitiveness Report
Regional Attractiveness Index
Responsible Competitiveness Index
Sustainable Competitiveness Index
Understanding the Creative Economy in India
World Competitiveness Report
enhancing
prosperity
enhancing
prosperity
U 24/8, Ground floor, DLF Phase 3, Gurgaon 122 002, Haryana, India
Tel: +91 124 4376676 Website: www.competitiveness.in

Journal of Competitiveness

Transcription

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