Why do firms engage in organizational innovation? Thuc Uyen Nguyen-Thi

Why do firms engage in organizational innovation?
Thuc Uyen Nguyen-Thi 1, Caroline Mothe2
1
CEPS/INSTEAD, BP 48, L-4501 Differdange, - Grand-Duchy of Luxembourg
[email protected]
2
Research Institute of Economics and Management, University of Savoie, Annecy, France
[email protected]
Preliminary version – Do not quote
Abstract
The objective of this paper was twofold. First, we try to understand what factors influence the firm‟s
decision to implement organizational innovation. Second, we wonder whether and how the motives of
such a strategy may differ depending on whether the firms operate in the manufacturing or service
industries. For this purpose, we make use of a systemic approach integrating in the same model
services and manufacturing. We made use of three groups of explanatory variables, namely firms‟
market and networks factors, financial and human factors, and firms‟ internal characteristics factors.
The results show firms‟ market and networks factors matter for organizational innovation, whether in
services or manufacturing. There is a positive relationship between competition and organizational
innovation. Concerning the incoming spillovers, important differences between services and
manufacturing are found. Information sources coming from customers as formal or informal partners
matter for manufacturing while those coming from R&D institutions are more likely to be important for
services. As regard to financial and human resources factors, we also observe some differences in the
determinants of different practices of organizational changes. As expected, the skill level of employees
seems to be more important for services than manufacturing in the organizational fields. The
hypothesis that large firms are more likely to invest in organizational innovation is confirmed only for
services sector.
Overall, this paper provides strong evidences of the heterogeneity in the motives of firms‟ decision to
engage in organizational innovation. On the one hand, differences arise when we consider the
determinants of various organizational innovations, indicating the appropriateness to differentiating
different practices of organizational innovation rather than using an aggregated measure of
organizational innovation. On the other hand, the determinants vary according to the type of industry,
even though the similarities are not negligible. This suggests that theoretical and empirical works on
the determinants of innovation, on the impact of innovation on firm‟s performance and, more generally,
on economic wealth, should use a systemic approach integrating in the same model services and
manufacturing.
Keywords : Organizational innovation, incoming spillovers, CIS, obstacles, technological innovation
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1. Introduction
Today, firms face a changing environment characterized by the rapid advance of
globalization, the emergence of new competitors and diversification of demand. In this
context, firms‟ innovative capacities depend not only on technological competencies or
Research and Development activities, but also their capacity to develop organizational
strategies for managing the innovation process. Many authors (Penrose, 1959; Nelson and
Winter, 1982; Wernerfelt, 1984; Teece, 1988) and other theorists of the resource-based view
(RBV), highlight the importance of completing the R&D-based strategy by investing
significant resources in other innovation strategies such as those implemented organisational
fields in order to maintain and build capabilities for technological innovation. The European
Commission‟s 1997 Green Paper – „partnership for a new organisation of work‟ spelt out a
crucial priority for a higher competition in Europe, namely, „improving employment and
competitiveness through a better organisation of work at the workplace, based on high skills,
high trust and high quality‟.
Despite of the crucial role of organizational strategies to the process of innovation, studies on
innovation have been mainly focused on technological aspects and largely concentrate on
manufacturing industries. When analyzing organizational innovation, interest essentially
resides in the relationship between organizational innovation and labour productivity
(Ichniowski et al., 1997; Caroli and Van Reenen , 2001; Greenan, 2003; Piva and Vivarelli ;
2002 ; Laursen and Foss, 2003; Evangelista and Vezzani, 2010); in the relationship between
organizational innovation as non-technological innovation with technological innovation
(Schubert, 2010; Mothe and Nguyen-Thi, 2010a,b; Battisti and Stoneman, 2010) or in the
presence of synergistic effects that may arise from simultaneous adoption of complementary
organizational practices (Ichniowski et al., 1997; Cappelli and Newmark, 2001; Nguyen-Thi et
al., 2008)
It is surprising to note that there are few empirical works on the motives which cause firms to
adopt organizational innovation. In order to remedy this lack in the literature, we seek in this
article to understand why some firms decide to engage in organizational innovation as well
as whether and how the motives of such a strategy may differ depending on whether the
firms operate in the manufacturing or service industries. For this purpose, we will adopt a
comparative research strategy (Arvanitis, 2008) that takes the “dissolution of boundaries”
(Drejer, 2004: 561) between manufacturing and services into account (Coombs and Miles,
2000). Embracing a view of innovation that accounts for its different forms (Tatikonda and
Montoya-Weiss, 2001), the paper investigates the determinants factors within a unique
framework, however distinguishing manufacturing from service firms.
The article is organized as follows. The next section reviews the literature on different
practices of organizational innovation and organizational innovation in services and
manufacturing. The section 3 outlines the data set, variables and method, based on the
large-scale Community Innovation Survey 2006 carried out in 2008 for Luxembourg. Section
4 presents and discusses the results and shows how different initial conditions can lead to
different results in organizational practices. Finally, Section 5 presents some conclusions,
implications for theory and practice, and derived consequences for policy making.
2. Theoretical framework
2.1. Organizational innovation
Theoretically, organizational innovation is a broad concept that encompasses strategic,
structural and behavioral dimensions (Gera and Gu, 2004). The notion of organizational
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innovation is subject to various definitions and interpretations (Lam, 2005). Black and Lynch
(2005) view organizational innovation as including components such as workforce training,
work design (more decentralized and flexible allocation of labor in the firm), employee voice
(allowing workers to have greater autonomy and discretion in their work) and shared rewards
(incentives such as profit sharing or stock options).
According to the OECD recommendations published in the Oslo manual (OECD/Eurostat,
2005), organizational innovation encompasses four types of practices: business practices,
knowledge management systems, workplace organization and external relations. The first
category of organizational innovation refers to the introduction of new business practices,
which aims to organize work and procedures. Examples of this practice are supply chain
management, business re-engineering, lean production, quality management. The second
category of organizational innovation refers to the introduction of knowledge management
systems. The knowledge management, here including complementary practices such as
management skills, up-skilling of employees, sharing, codification and storage of knowledge
is usually associated with more flexibility, adaptability, competitive advantage and better
organizational performance (Prahalad and Hamel, 1990; Grant, 1996; Spicer and SadlerSmith, 2006).The third category of organizational innovation refers to the change to the work
organization. The European Commission‟s 1997 Green Paper sees it a key priority for higher
competitiveness, based on high skill, trust and quality. According to OECD (2001), new work
practices are related to decentralize decision-making, job rotation, team work and shared
rewards. Implementing new work organization could result in substantial improvements in
organizational flexibility which in turn leads to improved firm efficiency and performance. The
fourth organizational practice refers to relations with other firms or public institutions, through
alliances, partnerships, outsourcing or sub-contracting. The growing role of networking in
firms‟ innovative capabilities is closely linked to the context of the emerging knowledgebased global economy. Because of the tacit and non transferable character of knowledge
and of the evolutionary and continual character of the learning process, innovative firms
should concentrate on their specific capabilities while involving in cooperative arrangements
in order to develop new competencies and extensions of the firm‟s know-how to new
applications. Firms should moreover be encouraged to engage in external relations in order
to access partners‟ complementary or synergistic competencies and capitalize “incoming
spillovers” (Kogut, 1988, Kogut and Zander, 1993; Cassiman and Veugelers, 2002), to
reduce the duplication of R&D efforts as well as risks and costs associated to innovation
projects (Jacquemin, 1988; Sakakibara, 1997), to benefit from scale economies (Kogut,
1988).
2.2. Organizational innovation in Manufacturing and Services
Over the last decade, the literature on service innovation has represented an increasingly
important field of research. In this stream, Knowledge Intensive Business Services (KIBS)
have received particular attention (e.g. Flikkema et al., 2007; Koch and Strotman, 2008,
Shunzhong, 2009). The on-going debate on whether services can be treated like
manufacturing with respect to innovation has not been resolved yet and three distinct views
on service innovation co-exist (Coombs and Miles, 2000): (i) for the demarcation approach,
service innovation is different from manufacturing and therefore requires specific theories; (ii)
the assimilation approach considers that services are similar to manufacturing and attaches
little importance to non-technological innovation; (iii) the synthesis approach is an integrative
view that allows for innovation to take place in manufacturing and in services (Gallouj and
Weinstein, 1997; Love and Mansury, 2007). Motivated by the need to integrate research on
manufacturing and service innovation, we used a “comparative” research strategy designed
to compare results for manufacturing and service firms in order to assess the adequacy of
using conventional models when analysing innovation in services, and specifically the factors
associated to organizational innovation. This view has recently been made possible in
Europe where innovation surveys and European Community Innovation Surveys (CIS) in
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particular have made remarkable progress, taking into account the specific aspects of
services, for instance by extending the definition of innovation to include organisational
innovation, which is supposed to be key for service industries.
Organizational innovation is viewed as being more prominent in services than in
manufacturing (Tether, 2005; Tether and Tajar, 2008; among others). Innovation in services
is mainly non-technological (organisational, marketing, management, service delivery, etc.)
with “softer” attributes such as workforce skills or cooperation practices (Tether, 2005). The
necessary interaction with clients, service delivery and marketing aspects has also been
emphasized (Gallouj and Weinstein, 1997; Tether, 2005; Flikkema et al., 2007; among
others). It is thus often analyzed in terms of technological, conceptual, client-interface and
service delivery innovation (Gallouj and Weinstein, 1997; Evangelista, 2000; Flikkema et al.,
2007). Literature has therefore put forward that firms in services do more non-technological
innovation than manufacturing companies – with the result that, in services, there is a greater
share of firms doing these activities. Evangelista (2000) suggests that organisational aspects
can either be linked to, or be independent from, the introduction of technological innovation.
However, no previous study has empirically studied why some firms decide to engage in
organizational innovation as well as whether and how the motives of such a strategy may
differ depending on whether the firms operate in the manufacturing or service industries. This
paper seeks to answer these questions.
3. Data and methodology
3.1. Data
The empirical analysis is based on firm-level data drawn from the Luxembourgish
Community Innovation Survey (CIS2006) carried out in 2008 by CEPS/INSTEAD1 in
collaboration with STATEC2. The objective of this survey is to collect data on firms‟
innovation behavior, over the three-year period from 2004 to 2006, according to the OECD
recommendations published in the Oslo manual (OECD/Eurostat, 2005). It provides a set of
firms‟ general information (sector of activities, group belonging, number of employees, sales,
geographic market), information about technological and non-technological innovation as
well as perceptions of factors hampering innovation activities or subjective evaluation of the
effects of innovation. The dataset also comprises information about sources of information
for innovation activities, competition intensity on the market as well as qualified personnel.
For the purpose of this paper, we used a sub-sample of firms with a least 10 employees in
the manufacturing and the service sectors. We thus obtained a sample of 561 representative
firms.
3.2. Variables and research expectations
The dependent variables of the model are five dummy variables. The first four variables are
equal to one if the firm has introduced during the three years 2004 to 2006 (1) new business
practices, (2) new knowledge management systems, (3) new methods of workplace
organization and (4) new methods of organizing external relations. The fifth dependent
variable is organizational innovation as an aggregated measure, taking the value 1 if at least
one of four above organizational practices is undertaken, and 0 otherwise.
At the firm-level, theoretical and empirical models that seek to answer the question why and
what kinds of firms introduce new or improved organizational practices underline three
1
2
International Network for Studies in Technology, Environment, Alternatives, Development
Central Service of Statistics and Economic Studies
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determinant factors : firms‟ market and networks, financial and human resources and firms‟
internal characteristics. We will include in the model a range of explanatory variables
supported by this view. However, we must note that it may remain rather explorative given
the lack of straightforward theoretical predictions available on the subject. Appendix A
presents definitions of all variables used in the model.
3.2.1 Firms’ market and networks factors
In order to take account of the firms‟ market and networks factors, we include three variables:
competition intensity, incoming spillovers and market-related obstacles. The first one is
competition intensity, a dummy variable which takes the value 1 when the firm describes that
the competition on the market in which it is operating is very intense and 0 if the competition
is few intense or not at all. Numerous theoretical and empirical studies have investigated the
relationship between competition and innovation, delivering however contradicting
predictions (Schumpeter, 1942; Arrow, 1962; Dixit and Stiglitz, 1977; Schmutzler, 2007). The
differences related to the assumptions made with respect to the competition type and
technological characteristics explain partially these inconclusive claims. More recently
Aghion et al. (2005) have shown that innovation increases initially with intense competition in
the product market and then declines, predicting thus an inverted U relationship between
competition and innovation. As regards to organizational field, we expect a positive
relationship between competition and organizational innovation.
The second variable is incoming spillovers. In the CIS survey, the firms are asked to rate the
importance of different external sources of information for the firm‟s innovation activities. We
include five dummy variables taking the value 1 if the score of importance of the following
five sources is “crucial”, respectively: (1) competitors, (2) customers, (3) suppliers, (4)
universities or other higher education institutions or governments or public research institutes
and (5) patents, databases, trade literature and fairs. To take account of firms‟ market and
networks factor, we also include market-related obstacles dummy variable, taking the value 1
if the scores of importance of uncertainty of products demand or/and dominance of
established firms is crucial.
3.2.2 Financial and human resources
In order to control for the importance of the skill level of employees, we create the variable
qualified personnel which is defined as the share of employees with higher education in total
employees of the firm (include post-secondary college diplomas and university graduates,
i.e. diplomas over baccalaureate, abitur, etc.). We expect that firms with greater skill
resources, whether in services or manufacturing, are more likely to see benefit in investing in
organizational innovation than firms with less skilled employees, in line with the results
carried out by Lynch (2007).
We also control for the importance of the managerial perception on the lack of knowledge,
whether concerning technology, market or partnership. Knowledge-related obstacles is a
dummy variable taking the value 1 if the scores of importance of lack of qualified personnel
or/and lack of information on technology, market or/and difficulty in finding cooperation
partners is crucial. To capture the impact of problems related to financial resources and high
costs which can hamper firms‟ innovation activities, we make use cost-related obstacles, a
dummy variable taking the value 1 if the scores of importance of lack of funds or/and high
costs of innovation is crucial. Our expectation is that the lack of knowledge could spur
organizational innovation while the lack of financial resources discourages firms to engage in
such long and costly organizational strategies.
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3.2.3 Firms’ internal characteristics
In order to control for firms‟ internal characteristics, we use four groups of variables: firm‟s
size, belonging to group, internal knowledge flows, and technological intensity. For firm‟s
size, three dummy variables representing three size divisions are used: (1) small for firms
with less than 50 employees (reference), (2) medium for those with between 50 and 149
employees, (3) large for those with more than 149 employees. In line with previous literature
(Lynch, 2007; Lynch and Black, 1998, Sapprasert, 2010), our expectation is that
organizational innovation is more frequent in large firms.
We also include belonging to a group, expected to have a positive impact on innovation as
far as firm being part of group could draw on group financial and resources for reorganizing
(Lynch, 2007). The third variable is internal knowledge flows, a dummy variable taking the
value 1 if the importance of other group firms as source of knowledge for the firm‟s
innovation process is crucial and 0 otherwise. We expect a positive impact on organizational
innovation, as firms that rely more on internally generated know-how are more likely
constrained to introduce new practices of management for enhancing communication and
knowledge exchange between workers within the group.
Finally, to measure the technological intensity, we use two groups of variables. The first
variable is the speed of technological change, measured as sum of sales of firms in the twodigit industry that stated that they had introduced products (goods or services) new to the
industry, divided by sum of sales of all firms in the industry. The second group of variables
are created, namely sub-sectors dummies, according to the two-digit NACE classification: (1)
High and medium high-tech manufacturing industry; (2) Medium low-tech manufacturing
industry; (3) Low-tech manufacturing industry (reference); (4) Transport and communication;
(5) Financial intermediation; (6) Computer activities; (7) R&D – Engineering activities and
consultancy, Technical testing and analysis and (8) Wholesale trade (reference).
3.3. Empirical methods
Five dependent variables are used in the model. The first four variables are individual
organizational practices which constitute four binary choice equations. We use a multivariate
Probit model which includes four equations estimating the four organizational practices.
Since it is our interest to explore the varying determinants of organizational innovation
between the practices, we include each explanatory variable as presented above in all four
equations. This is in order to test whether some variables impact organizational innovation of
one practice but not another. This method also allows us to investigate the correlation
between organizational practices conditional on a set of explanatory variables. The fifth
dependent variable is organizational innovation, a binary variable measured as the
introduction of at least one of above organizational practices during the period 2004-2006.
For this binary choice equation, a standard Probit model will be used.
4. Results and discussion
In this section, we present two sets of result, namely those for the totality of the sample and
those according to the sectors. In each set of results, both organizational innovation as an
aggregated measure and individual practices will be considered.
4.1. Motives for organizational innovation
Table 1 presents the results of the multivariate Probit model for the complete sample of 561
observations without divisions of sectors. First of all, this Table provides an overview of the
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motives of firms to introduce organizational innovation. From this estimation, the conditional
pair-wise correlations among the residuals of the four practices are computed (Table 2). We
note that the correlation coefficients, after controlling for firm-specific effects, are positive and
highly significant. These results are quite similar for unconditional correlations between the
four practices (see Appendix B). The correlation coefficient is particularly high between
“business practices” and “knowledge management” or between “workplace organization” and
“knowledge management”. Overall, these results provide some suggestive support of the
interdependence between the decisions to adopt certain organizational practices, which may
be influenced by the complementarity in the practices of organizational innovation, but also
by omitted firm-specific factors affecting all practices (Belderbos et al., 2004; see Nguyen-Thi
et al. (2008) for more results on complementarities between different types of organizational
innovation). The results also show that the estimated coefficients differ substantially across
equations, indicating that it is appropriate to differentiate different organizational practices.
As regard to the motives of organizational innovation, results for the firms‟ market and
networks factors show that the competition intensity of the firms‟ main market is likely to
motive firms to introduce organizational innovation. However, as far as individual practices
are concerned, this result is verified only for knowledge management. That is, on the market
where the competition is intensive, firms seem more likely to adopt new knowledge
management practices that help to better use external information and internal skills, which
could allow firms to face competition as they reinforce firms‟ flexibility and adaptability. This
result is in line with the findings of Nickell et al. (2001) or Pil and MacDuffie (1996) indicating
that firms are motivated to invest more in reorganization when the real output price or
performance is declining - which can be due to increased competition both domestically and
internationally.
Incoming spillovers of all types do not have any effect on organizational innovation as
aggregated measure, while some positive associations between incoming spillovers and
individual organizational practices are found. The institutional and suppliers incoming
spillovers are shown to have a strong impact on knowledge management practice. Firms
which consider that information stemming from suppliers and universities, other higher
education institutions or governments or public research institutes constitute crucial sources
of information for technological innovation are more likely to adopt new knowledge
management systems to better use or exchange information, knowledge, skills within the firm
or to collect and interpret information from outside the firm.
Surprisingly, the estimation results show that the perception of market-related obstacles to
innovation has significant and negative impact on the adoption of organizational practices. In
other words, the perception of this type of obstacles, i.e. the domination by well established
firms on the market and the uncertainty about the demand for innovative goods and services
discourages the firm‟s decision to engage in organizational innovation.
As for financial and human resources, we note, first of all, that the perception of knowledgerelated obstacles to innovation is positively associated with the introduction of organizational
innovation and all organizational practices. Firms which face the lack of organizational
resources, i.e. qualified personnel, of information on technology, of information on market or
the difficulty in finding cooperation partners for innovation are more likely to invest in
organizational innovation than those firms not facing such problems. Within the innovation
process, some firms may decide to introduce new organizational practices which could result
in improvements in organizational flexibility, which could lead in turn to better communication,
knowledge sharing within the firm as well as better absorption of knowledge and abilities
which they lack. Cost-related obstacles variable is significantly positive in organizational
innovation equation but surprisingly no evidence of such an association between this type of
obstacle and both organizational practices.
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A second finding is that the qualified personnel variable has a positive and significant impact
on organizational innovation, but there are differences between organizational practices. The
skill level of the employees is an important determinant for the introduction of business
practices, knowledge management and external relations with the largest impact on business
practices. On the contrary, we see any association between qualified personnel and
workplace organization. Overall, the findings indicate the importance of skills for the capacity
of firms to undertake organizational innovation as well as adopt various practices of
organizational innovation. These results are in line with our expectations and previous
empirical studies (Lynch, 2007).
When considering firms‟ internal characteristics, we find no evidence of the belonging to a
group variable on organizational innovation compared to non-group belonging firms. Internal
knowledge flows is significantly positive in the knowledge management and workplace
organization equations. As regard to the firm’s size, the results show that large firms are
more likely to adopt organizational innovation than small and medium firms. However, when
dividing organizational innovation into individual practices, we note that size has a positive
and significant effect only on business practices, in the sense that the larger the firm, the
greater the propensity to undertake practices for organizing work and procedures such as
supply chain, business re-engineering, lean production or quality management. This may be
explained by the fact that firms with a higher fraction of production workers and larger
production scale are more likely to adopt some specific types of organizational innovation. By
contrast, firm size is not important in explaining the implementation of other types of
organizational innovation. The hypothesis that firms in sectors with high technological
complexity and change engage more frequently in organizational innovation than those in
sectors with a low technological complexity and change is not confirmed. All technological
intensity variables do not have any significant impact on respective organizational practice.
This is in line with recent research in strategic management: the firm‟s organizational
strategy does not depend on the sector-level but rather on firm-specific characteristics which,
in turn, influence the incentives and ability to innovate.
4.2. Motives for organizational innovation in services and manufacturing
Table 3 and 4 presents estimation results of the multivariate Probit estimation for the five
dependent variables. As stated above for the full sample, the correlation coefficients for both
services and manufacturing, after controlling for firm-specific characteristics, are positive and
highly significant. The correlation coefficient is particularly high between business practices
and knowledge management or between workplace organization and knowledge
management. Overall, these results provide some suggestive support of the
interdependence between the decisions to adopt certain organizational practices, which may
be influenced by the complementarity in the practices of organizational innovation. As
already stated for the full sample, we observe that there are evidences of the heterogeneity
in the motives of decision to engage in organizational innovation in services and
manufacturing. This is in line with our expectations and justifies the need to separate
services from manufacturing.
Results for firms‟ market and networks factors show that the competition intensity plays a
positive role for organizational innovation in services while this variable has a positive impact
only for knowledge management practices in manufacturing. Our analysis provides evidence
that supports the hypothesis that the effect of market competition on innovation is not alike
for all practices of innovation. Thus, although the impact of competition on innovation varies
with the type of innovation, other factors seem to have a stronger impact on the incentives to
innovate.
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Among the various incoming spillovers variables, we note notable differences between
services and manufacturing. While information sources coming from customers have a
positive impact on organizational innovation in manufacturing, such an association is not
found for services. On the contrary, institutional incoming spillovers have a significant and
positive effect on knowledge management and workplace organization equations in services,
while no evidence was carried out for manufacturing. Moreover, we note that supplier
incoming spillovers spur organizational innovation as well as business practices, knowledge
management and external relations in the sector of services, while this type of specific
sources has a significant and positive impact only on knowledge management in
manufacturing. Competitors and public incoming spillovers have any effect on organizational
innovation and individual organizational practices either. Overall, the results support partially
the hypothesis that the importance of information sources coming from (formal or informal)
partners should play a positive role in inciting firms to introduce new organizational practices.
For services, the most important information sources are suppliers and R&D institutions,
while for manufacturing; the most crucial sources of information are customers. Theoretically,
suppliers, customers and competitors are usually seen as crucial sources of information for
technological innovation (Tether, 2003). Our findings suggest that in terms of types of
innovation, i.e. technological and non-technological innovation, source-specific incoming
spillovers do not have the same influence.
As observed for the complete sample, we find, rather surprisingly, that the perception of
market-related obstacles is negatively associated to organizational innovation, especially for
business practices in both services and manufacturing. This suggests that those firms which
consider that their innovation activities are hampered by important uncertainty of demand for
innovative goods and services or by important domination of established firms on the market
are less likely to undertake new or improved methods of business practices such as supply
chain, re-engineering, lean and quality management. This is not consistent with our
expectations. Indeed, in today‟s economic environment, where preferences and demands of
customers change rapidly, the introduction of new business practices could enhance the
visibility of new products as well as shorten the period of time that could pass between the
invention of new products and its effective commercialization on the market (Häusler et al.,
1994; Hagedoorn, 1994; Dodgson; 1992). However, our result might be accounted for by two
factors: the dominance of small firms in our sample (86% are Small and Medium Enterprises,
SMEs) and the substantial time lag usually associated with the return on investment of such
long term organizational strategies. Indeed, most SMEs have limited resources and may not
be able to dedicate financial or human resources to both internal organizational
improvements. Thus, firms facing these obstacles could be discouraged to adopt new
organizational tools.
Concerning financial and human resources factors, the perception of cost-related obstacles
(lack of funds or high innovative costs) is strongly and positively associated to the
organizational innovation in services, particularly to the business practices. A closer look at
the descriptive details shows that this type of obstacle is reported as being very important by
22% of innovating firms, but only by 9% of non-innovating firms (these figures are,
respectively, 26% and 13% for knowledge-related obstacles, 24% and 21% for marketrelated obstacles). These statistics indicate that, regardless of the type of obstacles,
innovating firms perceive more frequently than non-innovating firms the obstacles impeding
their innovation activities (Mohnen and Röller, 2005). Therefore, our result for service firms
could suggest that cost-related obstacles encourage firms, in particular those that innovate,
to introduce organizational innovation that could lead, in turn, to higher capacity of
technological innovation. No evidence was found for manufacturing firms.
The knowledge-related obstacles variable, as for the complete sample, is significantly
positive in organizational equation for services as well as manufacturing, as expected. This
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tends to corroborate the idea that firms seek through organizational innovation to reinforce
firms‟ flexibility and adaptability and thereby be able to remedy the lack of information on
technology, market and potential R&D cooperation partners. When considering individual
practices, we note that the perception of this lack motives firms in services to engage in
workplace organization and those in manufacturing to engage in workplace organization and
business practices.
Among firms‟ internal characteristics, the internal knowledge flows has a positive and
significant impact on organizational innovation, business practices and workplace
organization for manufacturing firms, in line with expectations, while such an association is
not observed for firms in services. We also find that the qualified personnel have no impact
on organizational innovation in manufacturing. In services, however, this variable is found to
have a positive and significant effect for organizational innovation as aggregate measure and
business practices. Firm’s size has no impact in manufacturing. On the contrary, large firms
in services are more likely to be able to invest in organizational innovation, business
practices and external relations in comparison with small firms. Concerning the being part of
a group variable, except for knowledge management equation for firms in services where
there is a positive association, no evidence is found both for services and manufacturing.
This result is not in line with the empirical study carried out by Lynch (2007). No evidence on
the relationship between organizational practices and technological intensity was carried out.
5. Conclusion
The objective of this paper was twofold. First, we tried to understand what factors influence
the firm‟s decision to implement organizational innovation. Second, we wondered whether
and how the motives of such a strategy may differ depending on whether the firms operate in
the manufacturing or service industries. For this purpose, we make use of a systemic
approach integrating in the same model services and manufacturing. Using the firm-level
dataset drawn from the Luxembourgish Community Innovation Survey (CIS2006), we
performed a multivariate Probit estimation model. We made use of three groups of
explanatory variables, namely firms‟ market and networks factors, financial and human
factors, and firms‟ internal characteristics factors.
As regards to the motives of organizational innovation, the results for the complete sample
suggest that firm‟s market and networks factors play an important role in motivating firms to
engage in various organizational practices. There is a positive relationship between
organizational innovation and competition intensity. Particularly, firms are more likely to
invest in knowledge management when competition on the product market is intense. The
incoming spillovers of all partners do not have any effect on organizational innovation as
aggregated measure, while some positive associations between incoming spillovers and
individual organizational practices are found. The perception of the lack of information related
to the market, technology seems to discourage firms to introduce various organizational
practices. The results also highlight the positive impact of human resources and the lack of
financial resources as they tend to spur the adoption of organizational innovation. Rather
unexpectedly, we find no evidence on the relationship between technological intensity and
organizational changes.
As we separated services and manufacturing, the results show firms‟ market and networks
factors matter for organizational innovation, whether in services or manufacturing. Thus,
there is a positive relationship between competition and organizational innovation. We note
almost that whether in services or manufacturing, competition intensity has a positive impact
on knowledge management. Overall, we find that the effect of market competition on
organizational innovation is not alike for all practices. Concerning the incoming spillovers,
important differences between services and manufacturing are found. Information sources
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coming from customers as formal or informal partners matter for manufacturing while those
coming from R&D institutions are more likely to be important for services. As regard to
financial and human resources factors, we also observe some differences in the
determinants of different practices of organizational changes. While the perception of costrelated obstacles constitutes a motive for organizational innovation in services, this
perception has no incidence on firm‟s organization. As expected, the skill level of employees
seems to be more important for services than manufacturing in the organizational fields. One
more time, we do not find any evidence of the technological intensity. The hypothesis that
large firms are more likely to invest in organizational innovation is confirmed only for services
sector.
Overall, this paper provides strong evidences of the heterogeneity in the motives of firms‟
decision to engage in organizational innovation. On the one hand, differences arise when we
consider the determinants of various organizational innovations. This indicates the
appropriateness to differentiating different practices of organizational innovation rather than
using an aggregated measure of organizational innovation. On the other hand, the
determinants vary according to the type of industry, even though the similarities are not
negligible. This result suggests that theoretical and empirical works on the determinants of
innovation, on the impact of innovation on firm‟s performance and, more generally, on
economic wealth, should use a systemic approach integrating in the same model services
and manufacturing.
11
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Table 1 : Results of multivariate Probit model for organizational innovation (all firms)
Variables
Organizational
Business practices
Knowledge
innovation
management
Medium size
0.115(0.111)
0.137(0.135)
0.088(0.137)
Large size
0.580(0.164)***
0.560(0.161)***
0.190(0.162)
Sub-sector dummies included
yes
yes
yes
Group
0.0201(0.125)
0.0107(0.128)
0.0831(0.129)
Cost-related obstacles
0.375(0.182)**
0.219(0.158)
0.070(0.156)
Knowledge-related obstacles
0.432(0.146)***
0.306(0.147)**
0.352(0.145)**
Market-related obstacles
-0.329(0.143)**
-0.385(0.152)**
-0.322(0.150)**
Internal knowledge flows
0.176(0.150)
0.163(0.140)
0.253(0.142)*
Competitor incoming spillovers
0.008(0.245)
0.162(0.199)
0.134(0.191)
Customer incoming spillovers
0.256(0.179)
0.179(0.163)
0.226(0.160)
Supplier incoming spillovers
0.339(0.246)
0.279(0.161)*
0.345(0.162)**
Institutional incoming spillovers
0.425(0.289)
0.309(0.224)
0.560(0.224)**
Public incoming spillovers
0.154(0.183)
0.173(0.161)
0.185(0.161)
Competition intensity
0.144(0.087)*
0.114(0.080)
0.168(0.083)**
Qualified personnel
0.505(0.257)**
0.611(0.200)***
0.381(0.199)*
Speed of technological change
0.533(2.486)
-0.005(2.113)
-0.463(2.159)
Constant
-1.734(0.307)***
-1.840(0.345)***
-2.035(0.355)***
Observations
561
561
Log likelihood
-326.76
-1067.68
95.31(.000)***
168.28 (.000)***
Wald 2
Workplace
organization
0.019(0.131)
0.244(0.157)
yes
-0.105(0.126)
0.037(0.151)
0.390(0.144)***
-0.302(0.143)**
0.381(0.140)***
0.228(0.192)
0.273 (0.158)*
0.002(0.159)
0.343(0.217)
0.021(0.158)
0.110(0.094)
0.151(0.195)
0.006(2.084)
-1.427(0.337)***
External relations
-0.131(0.150)
0.241(0.165)
yes
-0.034(0.138)
0.042(0.166)
0.310(0.148)*
0.0327(0.154)
0.0151(0.153)
0.165(0.193)
0.133(0.166)
0.290(0.162)*
0.028(0.213)
0.240(0.160)
0.141(0.089)
0.417(0.211)*
0.270(2.270)
-2.264(0.378)***
Notes: *, ** and *** denote significance at the level of 10%, 5% and 1%.Standard errors in parentheses
14
Table 2 – Conditional correlation between organizational practices
Business
Knowledge
practices
management
Workplace organization
Business practices
External relations
1.000
Knowledge management
0.723***
1.000
Workplace organization
0.644***
0.724***
1.000
External relations
0.533***
0.555***
0.647***
1.000
15
« Luxembourg 2020 » Colloquium – December 7-9, 2010
Table 3 : Results of multivariate Probit model for organizational innovation (services)
VARIABLES
Organizational
Business practices
Knowledge
innovation
management
Medium size
0.345(0.201)
0.071(0.191)
-0.110(0.199)
Large size
0.778(0.252)***
0.914(0.247)***
0.239(0.258)
Sub-sector dummies included
yes
yes
yes
Group
0.179(0.149)
0.228(0.180)
0.321(0.184)*
Cost-related obstacles
0.500(0.235)**
0.520(0.230)**
-0.0411(0.207)
Knowledge-related obstacles
0.369(0.210)*
0.054(0.218)
0.182(0.218)
Market-related obstacles
-0.258(0.205)
-0.448(0.199)**
-0.392(0.195)**
Internal knowledge flows
0.0786(0.259)
-0.315(0.215)
0.132(0.218)
Competitor incoming spillovers
0.144(0.321)
0.280(0.298)
0.195(0.308)
Customer incoming spillovers
0.185(0.268)
0.195(0.262)
0.043(0.258)
Supplier incoming spillovers
0.711(0.288)**
0.700(0.250)***
0.421(0.247)*
Institutional incoming spillovers
0.414(0.432)
0.396(0.326)
1.080(0.324)***
Public incoming spillovers
-0.006(0.253)
-0.133(0.257)
-0.080(0.258)
Competition intensity
0.262(0.108)**
0.069(0.107)
0.218(0.115)*
Qualified personnal
0.618(0.255)**
0.761(0.263)***
0.390(0.251)
Speed of technological change
-1.861(3.947)
1.401(1.743)
-2.944(3.448)
Constant
-2.163(0.501)***
-1.823(0.490)***
-1.759(0.472)***
Observations
354
354
Log likelihood
-196.10
-2051.13
90.23(.000)***
168.70(.000)***
Wald 2
Notes: *, ** and *** denote significance at the level of 10%, 5% and 1%.Standard errors in parentheses
Workplace
organization
-0.063(0.194)
0.281(0.231)
yes
0.215(0.174)
0.134(0.216)
0.346(0.205)*
-0.339(0.192)*
0.254(0.216)
0.315(0.272)
0.322(0.240)
0.220(0.234)
0.566(0.324)*
-0.312(0.265)
0.085(0.106)
0.053(0.254)
-1.562(3.422)
-1.366(0.457)***
Table 4 : Results of multivariate Probit model for organizational innovation (industry)
Variables
Organizational
Business practices
Knowledge
Workplace
innovation
management
organization
Medium size
0284(0.250)
-0.057(0.238)
0.159(0.251)
-0.09(0.241)
Large size
0.536(0.338)
0.193(0.283)
0.426(0.273)
0.029(0.293)
Sub-sector dummies included
yes
yes
yes
yes
Group
-0.252(0.235)
-0.182(0.242)
-0.232(0.240)
-0.284(0.234)
Cost-related obstacles
0.234(0.256)
0.326(0.275)
0.039(0.318)
0.352(0.273)
Knowledge-related obstacles
0.564(0.312)*
0.474(0.264)*
0.424(0.267)
0.581(0.272)**
Market-related obstacles
-0.508(0.258)**
-0.741(0.230)***
-0.039(0.297)
-0.513(0.294)*
Internal knowledge flows
0.414(0.252)*
0.451(0.255)*
0.275(0.284)
0.656(0.266)**
Competitor incoming spillovers
-0.179(0.577)
0.158(0.404)
0.189(0.357)
0.411(0.377)
Customer incoming spillovers
0.485(0.264)*
0.311(0.264)
0.192(0.257)
0.424(0.247)*
Supplier incoming spillovers
0.002(0.309)
0.255(0.296)
0.469(0.267)*
0.315(0.311)
Institutional incoming spillovers
0.341(0.541)
0.720(0.427)
0.388(0.388)
0.447(0.431)
Public incoming spillovers
0.314(0.322)
-0.127(0.296)
-0.019(0.255)
-0.064(0.296)
Competition intensity
-0.069(0.170)
-0.063(0.142)
-0.243(0.134)*
-0.174(0.143)
Qualified personnal
-0.012(0.522)
0.010(0.516)
-0.015(0.505)
-0.174(0.504)
Speed of technological change
1.252(2.369)
1.702(3.325)
1.025(2.526)
-2.252(2.800)
Constant
-0.964(0.770)
-0.659(0.627)
-0.672(0.671)
-0.238(0.633)
Observations
207
207
Log likelihood
-122.56
-489.91
36.07(0.001)***
105.81(.000)***
Wald 2
Notes: *, ** and *** denote significance at the level of 10%, 5% and 1%.Standard errors in parentheses
External relations
0.120(0.218)
0.603(0.242)**
yes
0.105(0.199)
0.171(0.221)
0.087(0.226)
0.078(0.218)
-0.336(0.214)
0.175(0.312)
0.144(0.259)
0.835(0.236)***
-0.0221(0.306)
-0.170(0.233)
0.048(0.128)
0.392(0.284)
-1.285 (3.331)
-2.014(0.506)***
External relations
-0.440(0.246)*
0.021(0.323)
yes
-0.320(0.258)
0.0712(0.301)
0.158(0.268)
-0.400(0.264)
0.167(0.274)
0.429(0.365)
0.542(0.296)*
0.105(0.316)
0.410(0.445)
0.325(0.306)
0.178(0.194)
-0.125(0.510)
-1.208(3.253)
-2.180(0.789)***
Appendix A : Definition of variables
Variables
Description
Organizational innovation
Business practices
Knowledge management
Workplace organization
External relations
Equal to 1 if introduced new business practices for organizing work or procedures (i.e. supply chain, business reengineering, lean production, quality management), 0 otherwise
Equal to 1 if introduced new knowledge management systems to better use or exchange information, knowledge,
skills within the firm or to collect and interpret information from outside the firm), 0 otherwise
Equal to 1 if introduced new methods of workplace organization for distributing responsibilities and decision
making (team work, decentralization, integration or de-integration of departments), 0 otherwise
Equal to 1 if introduced new methods of organizing external relations with other firms or public institutions
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« Luxembourg 2020 » Colloquium – December 7-9, 2010
Organizational innovation
(partnerships, outsourcing, sub-contracting), 0 otherwise
Equal to 1 if at least one of four above organizational practices during the three years 2004 to 2006, 0 otherwise
Incoming spillovers
Competitor incoming
spillovers
Customer incoming
spillovers
Supplier incoming
spillovers
Institutional incoming
spillovers
Public incoming spillovers
Internal knowledge flows
Equal to 1 if the score of importance of competitors as sources of information is “crucial” for the firm‟s innovation
process, 0 otherwise
Equal to 1 if the score of importance of customers as sources of information is “crucial” for the firm‟s innovation
process, 0 otherwise
Equal to 1 if the score of importance of suppliers as sources of information is “crucial” for the firm‟s innovation
process, 0 otherwise
Equal to 1 if the score of importance of universities or other higher education institutions or governments or public
research institutes as sources of information is “crucial” for the firm‟s innovation process, 0 otherwise
Equal to 1 if the score of importance of patents, databases, trade literature and fairs as sources of information is
“crucial” for the firm‟s innovation process, 0 otherwise
Importance of other group firms as source of knowledge for the firm‟s innovation process (scores between 0
(unimportant) and 3 (crucial))
Obstacles to innovation
Cost-related obstacles
Knowledge-related
obstacles
Market-related obstacles
Equal to 1 if the score of importance of at least one of three following obstacles (scores between 0 (unimportant)
and 3 (crucial)) is “crucial”: (1) lack of funds within your enterprise; (2) lack of finance from sources outside your
enterprise; (3) innovation costs too high, 0 otherwise
Equal to 1 if the score of importance of at least one of four following obstacles (scores between 0 (unimportant)
and 3 (crucial)) is “crucial”: (1) lack of qualified personnel; (2) lack of information on technology; (3) lack of
information on market, (4) difficulty in finding cooperation partners for innovation, 0 otherwise
Equal to 1 if the score of importance of at least one of two following obstacles (scores between 0 (unimportant)
and 3 (crucial)) is “crucial”: (1) market dominated by established enterprises; (2) uncertain demand for innovative
goods or services, 0 otherwise
Others
Size
Competition intensity
Speed of technological
change
Group belonging
Sectors
Qualified personnel
Logarithm of the number of employees
Nature of the market in which firm is operating: No effective competition, not very intense, quite intense, very
intense
Sum of sales of firms in the two-digit industry that stated that they had introduced products (goods or services)
new to the industry, divided by sum of sales of all firms in the industry
Equal to 1 if no part of group (reference); equal to 2 if part of a national enterprise group; equal to 3 if part of an
European enterprise group; equal to 4 if part of extra-European enterprise group
Manufacturing and services (Transport and communication; Financial intermediation; Computer activities; R&D –
Engineering activities and consultancy, Technical testing and analysis and Wholesale trade)
Number of employees with higher education (include post-secondary college diplomas and university graduates,
i.e. diplomas over baccalauréat, abitur, etc.)
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Appendix B: Unconditional binary correlations between organizational practices
Business practices
Knowledge
management
Workplace
organization
External relations
Business
Knowledge
Workplace
External
practices
management
organization
relations
1.00
0.54
1.00
0.47
0.48
1.00
0.32
0.26
0.35
1.00
18