Innovating Against European Rigidties Instututions

Innovating against European rigidities

Institutional environment and dynamic capabilities

Magali A. Delmas*

Bren School, University of California-Santa Barbara, 4670 Physical Sciences North, Santa Barbara,

CA 93106-5131, USA

Accepted 15 October 2001

Abstract

European firms are confronted to the paradox of a strong R&D in many areas but a low level of

innovation. Building on the dynamic capability approach, I propose an institutional approach where

innovation is linked to cultural, organizational, and regulatory factors. These include managers attitude

toward risk and uncertainty, the ability to develop capabilities and access complementary assets, and a

favorable regulatory environment. Using European microdata on how 6860 managers perceive factors

hampering innovation, this paper shows that the risk-averse attitude of European firms and their

difficulty to develop dynamic capabilities may explain the weakness of European innovation.

Institutional factors such as pervasive rigidities and distortions that hamper the functioning of markets,

may also prevent innovative responses. The use of managers perceptions seems particularly well suited

in the context of innovation where choices are taken with limited information. Conclusions drawn from

this perspective call for policies that will take into account the system in which innovation can take

place. D 2002 Elsevier Science Inc. All rights reserved.

Keywords: Innovation; Institutional environment; Europe

1. Introduction

One of the most outstanding features of the present era is the pursuit of an accelerated pace

toward the globalization of exchanges, which is accompanied by deregulation whose main

1047-8310/02/$ see front matter D 2002 Elsevier Science Inc. All rights reserved.

PII: S1047 -8310 (01 )00047 -5

* Tel.: +1-805-893-7185; fax: +1-805-893-7612.

E-mail address: [email protected] (M.A. Delmas).

Journal of High Technology

Management Research 13 (2002) 1943

effects are in most cases still to come (Bouin & OConnor, 1997). Given the new competitive

conditions in the global economy, innovation is a determining factor in the ability of firms

and countries both to adapt themselves to new constraints and take advantage of new

opportunities (Cervantes, 1997).

This question is crucial for Europe, which is confronted with the paradox of a strong R&D

in many respects but a low level of innovation. Although Europe has a strong scientific base

(CEC, 1994), it seems that European firms, as compared to their American and Japanese

counterparts, suffer from a difficulty to transform R&D into commercially viable innovations

and new products (Andreasen, Coriat, den Hertog, & Kaplinsky, 1995; Buigues &

Jacquemin, 1998).1

The dynamic capability approach to strategy (Teece, Pisano, & Schuen, 1997) shows

that successful innovative firms in the global market place have been demonstrating timely

responsiveness to market changes, along with the management capability to effectively

coordinate and redeploy internal and external competencies. Even though the business

firm is clearly the leading player in the development and commercialization of new

product and processes, it is important to understand the institutional environment in which

these activities take place. Innovation systems are rooted within a given set of national

and subnational institutions, and the role of supporting institutions, both private and

public, formal and informal, is of crucial importance (Lundvall, 1998; Mowery, 1998;

Nelson, 1993).

In this paper, I propose an institutional approach to explain innovation. I suggest four

dimensions of the institutional environment that facilitate or hamper innovation. The first

one is cultural and includes the attitude of managers toward risk and uncertainty. The second

one is organizational and refers to the ability of firms to acquire and develop new

knowledge. The third dimension refers to the availability of complementary assets such as

access to sources of finance or cooperation with other firms. The fourth one is the regulatory

environment such as property right regimes and taxes.

Using European microdata on how 6860 managers perceive factors hampering innovation,

this paper shows that the risk-averse attitude of European managers and the perceived

difficulty of European firms to develop dynamic capabilities and acquire new knowledge

explain the weakness of European innovation. Institutional factors, such as pervasive

rigidities and distortions that hamper the functioning of markets, may also play a role in

preventing innovative responses.

Most of the studies on the lack of innovation in Europe focus on the cost of R&D and the

difficulty to finance it (Green Paper on Innovation, 1995). However, successful innovation

requires more than basic research and R&D expenditure. Conclusions drawn from an

1 European companies apparently obtain lower returns than US companies on R&D investment, as measured

in terms of ability to leverage R&D into patents and to leverage patents into products for the global market. The

international diffusion rate of patents generated in Europe is only two-thirds that of the US. Between 1984 and

1993, the European Union lost patent share in all sectors apart from aerospace and transport equipment

(Competitiveness Report, 1996).

M.A. Delmas / Journal of High Technology Management Research 13 (2002) 194320

institutional perspective on innovation call for policies that will take into account the system

in which innovation can take place. New technologies will not be fully reflected in

productivity growth until societal constraints are removed allowing companies to undergo

thorough reorganization (Pavitt, 1998).

In Section 2 of this paper, I develop an institutional approach to innovation. Section 3

exposes the data and empirical methods. The measures of factors hampering innovation are

discussed and the Community Innovation Survey (CIS) is described. Sections 4 and 5 of the

paper present the empirical results and a concluding discussion of their implication.

2. An institutional approach to innovation

The dynamic capability approach to strategy emphasizes the key role of strategic

management in appropriately adapting, integrating, and reconfiguring internal and external

organizational skills, resources, and functional competencies toward changing the envir-

onment (Langlois & Robertson, 1995; Teece et al., 1997). However, firms are embedded in a

larger institutional environment, and the behavior of each is governed by regulative, nor-

mative, and cognitive aspects (Scott, 1995). I suggest that specific attention should be given

to the institutional context, which can facilitate or hinder firms dynamic capabilities and

innovative strategies.

There is a flourishing literature on national innovation systems, which stresses that the

flows of technology and information among people, enterprises, and institutions are key to

the innovative process. Innovation and technology development are the result of a complex

set of relationships among actors in the system, which includes enterprises, universities, and

government research institutes (Dosi, Freemand, Nelson, Silverberg, & Soete, 1988;

Lundvall, 1992; Mowery, 1998; Mowery & Oxley, 1995; Nelson, 1993). My approach adds

to this research by pointing out how the cultural, organizational, and regulatory aspects of the

institutional environment impact innovative behaviors.

Here, the institutional context is analyzed at the regional level (in this case, the European

level) instead of the national level. The European Union (EU) integration has a history of more

than 40 years. It has led to the development of a number of simultaneous or lagging

convergences processes, creating a postnational layer of activities for national firms and

governments. European integration is a process towards a coherent institutional setup for

production, trade, and innovation within Europe (Gregersen & Johnson, 1997). There is a

market tending towards unification, regulated by well-defined competition and trade policy

rules with emerging (research, innovation, and regional development) structural policy

institutions (Soete & Weel, 1999).

2.1. Attitude toward risk and uncertainty

First, innovation is a quest into the unknown. It involves taking risks, searching, probing,

and reprobing of technological as well as market opportunities (Kunkel, 1997; Santomero &

Trester, 1998). Second, innovation is about the introduction of novelty by breaking with

M.A. Delmas / Journal of High Technology Management Research 13 (2002) 1943 21

established routines and by overcoming a wide range of social and cultural barriers

(Hargadon, 1998; Tushman & Reilly, 1996).

These elements not only require an entrepreneurial attitude as portrayed by Schumpeter

(1936) with energy of action and will, but also adaptive organizations, which challenge their

current paradigms. The swift-moving environment in which they function makes it critical

that the old fit be consciously disturbed (Chakravarthy, 1982). Organizations can close

themselves to changes in the market and business environment and to new sources of

technology. Individuals in organizations can fall into the trap of adopting a citadel mentality.

Closed systems may be able to hone existing routines but will lose the capacity to engage in

new routines (Nelson & Winter, 1982).

There is also a value in responding rapidity to new demands. In an era of shortened product

life cycles, a competitive advantage is directly linked to how quickly new products can be

developed (Malueg & Tsutsui, 1997). Certain innovative responses are required when time-

to-marker is critical, when the rate of technological change is rapid, and when the nature of

future competition and markets is difficult to determine.

In conclusion, firms must be able to process by trial and errors, to challenge their way of

working, and to respond rapidly to changes in the environment. This requires firms to adopt a

dynamic and entrepreneurial attitude. On the contrary, closed systems with a culture averse to

risk taking will not lead to innovation. The predicted effect of a risk-averse attitude of the firm

can be formalized as follows:

Hypothesis 1: The more the risk-averse attitude toward change, the less the innova-

tion output.

2.2. Ability to acquire new knowledge

Innovation is linked to organizational learning, that is the way firms generate, absorb, and

transmit knowledge (David, 1997; Freeman, 1991; Kogut & Zander, 1992; Pisano, 1994;

Rosenberg, 1976; Sanchez & Mahoney, 1996). Knowledge constitutes input into the learning

process, that is, knowledge transfer in many cases is a means to generate new learning and

among others an agents existing knowledge stock (Foray & Lundvall, 1996).

Cohen and Levinthal have argued that the ability of a firm to recognize the value of new

external information, to assimilate it, and to apply it to commercial ends is critical to the

firms innovative capabilities (Cohen & Levinthal, 1990). This capability, called a firms

absorptive capacity, is largely a function of the firms level of prior related knowledge. The

absorptive capacity is based on employees skills as well as firm organizational design,

which influences the quantity and quality of information exchanged, the level at which

decisions are made, and how organization members monitor the external environment. This

level of knowledge can be embedded in the employees. Alternatively managers can recruit

scientists and engineers to keep a firm adequately up-to-date with scientific knowledge.

Knowledgeable employees will be able to survey what knowledge is available in the world,

detect new developments, and judge what is worthwhile acquiring and learning. Therefore,

if there is a lack of knowledgeable employees within the firm or in the environment of the


firm such as in universities, the firm will lack absorptive capacity and will have more dif-

ficulties to innovate.

The ability to acquire knowledge is not only linked to the firms absorptive capacity but

also to the existing flow of knowledge surrounding firms. For example, external information

on technological innovations or market opportunities difficult to reach maybe even for

knowledgeable employees because of deficient information technologies. The relationship

between the ability to acquire knowledge and innovation can be formalized as follows:

Hypothesis 2: The less the ability to acquire knowledge, the less the innovation output.

2.3. Access to complementary assets

Innovative activity is often the result of dynamic relations between participants rather than

the simple transfer of information or technology (Mastenbroek, 1996). The systemic

characteristics of new technologies have significant implications for the organization of

firms. The more systemic a technology, the closer the cooperation between firms needed to

share and transfer it. Feedback loops between the different players are very important in the

innovation process (Teece, 1996).

Furthermore, linkages to other technologies, to complementary assets and to users must be

established if innovation is to be successful. As firms might lack competence in a number of

technological fields, cooperation with other enterprises creates the necessary complementary

technology unit, enabling these companies to capitalize on economies of scope through joint

efforts (Delmas, 1999; Hagedoorn, 1993; Kogut, 1988; Powell, 1990).

To be successful, innovation requires access to complementary assets such as for example

financing or distribution (Teece, 1986). Collaborative arrangements between firms may be

utilized to access complementary assets supplied by the respective parents. Moreover,

innovation also depends on links between firms and other type of agents such as research

laboratories, industry unions, or public agencies (Ham and Mowery, 1998).

In conclusion, innovation requires that firms develop, adapt, integrate, and reconfigure

internal as well as external organizational skills and resources to match the requirement of a

changing environment. An environment, which hampers the creation of linkages and obstructs

access to complementary assets, should therefore impede the innovation process. The

predicted effect of the difficulty to access complementary competencies on innovation can

be formalized as follows:

Hypothesis 3: The more difficult the access to complementary assets, the less the

innovation output.

2.4. A favorable regulatory environment for innovation

The institutional environmentcomprising the rules of the gamecan influence in

several ways the propensity of firms to innovate (North, 1990). It can be a source not only

of uncertainty but also of rigidities hampering organizational change.


2.4.1. Regulation, risk, and uncertainty

Regulation can put constraints on industrial organization, on the market in which they can

develop, and on the way firms can interact with partners. For example, regulations can

obstruct the innovation process if its timing does not fit the business cycle. In some fast-

moving areas (notably ICT), it is becoming clear that traditional regulation (through its

consensus-finding mechanisms, the need for an extensive public comment period, etc.) is

imposing excessive time constraints. Where product-cycle periods are short, with radical new

developments appearing almost monthly, regulation that takes typically 3 years (often longer)

will be of limited effect in the market.

Obviously, the most documented literature on the link between institutional regulation and

innovation is the literature dedicated to the economics of intellectual property rights and

especially to the economics of the patent and copyright system. Under many legal systems,

the ownership rights associated with technological know-how are often ambiguous, do not

always permit rewards that match contribution, vary in the degree of exclusion they permit

(often according to the innate patentability of copyrightability of the object or subject matter),

and are temporary. Teece (1986), Besen and Raskind (1991), Bessy and Brousseau (1998),

Chang (1995), and Scotchmer (1991) point out the fundamental dilemma between diffusion

and invention. On the one hand, a strong patent protection incites to innovate. On the other

hand, a weak one favors a rapid and wide spread of inventions (that are collective goods).

Most studies therefore point out that licensing may allow firms to reach simultaneously the

two goals and that compulsory licensing is sometimes required to oblige innovators to spread

their inventions. Optimal property rights regimes are therefore identified in various tech-

nological and industrial configurations.

2.4.2. Skills, labor mobility, and innovation

The upgrading of skills throughout the working life is required to improve initial skills and

to keep pace with change. The extent to which national learning systems generate and

maintain a level of skills that allows firms to acquire new knowledge impacts innovative

activities (Heyes, 1993; Williams, 1994).

Labor regulations, which are essential for the protection of workers, can sometimes

discourage innovation by making it more difficult to introduce new technologies or new

approaches to workplace organization (Saint-Paul, 1997, 1998).

2.4.3. Regulation and access to complementary assets

Competition policy is another example of regulation, which influences the ability of

companies to exploit linkages and improve collaboration with their customers and suppliers.

The ability of innovating firms to cooperate, by striking necessary vertical and horizontal

agreements or entering into alliances, often raises issues of antitrust, as do other elements of

business strategy (Jorde & Teece, 1991). As Schumpeter (1942) suggested half a century ago,

the kind of competition embedded in standard microeconomic analysis may not be the kind of

competition that really matters if enhancing economic welfare is the goal. Rather, it is

dynamic competition propelled by the introduction of new products and new processes that

really counts.


The predicted effect of institutional rigidities on innovation can be formalized as follows:

Hypothesis 4: The more the institutional rigidities, the less the innovation output.

In conclusion, innovation requires an attitude open to change and organizational

flexibility. It also requires the ability to acquire new knowledge and access complementary

assets. The institutional environment, through training, legislation, norms, and subsidies, can

hinder or facilitate the adaptability of firms and their access to knowledge and complement-

ary assets. This framework is laid out in Fig. 1. Fig. 1 illustrates the four dimensions of the

institutional environment described above: attitude toward risk and uncertainty, ability to

access knowledge, availability of complementary assets, and regulations. These dimensions

do not impact firms innovative capacity independently. Rather, innovation will vary ac-

cording to a combination of these aspects. These propositions are tested by analyzing the

perceptions of European managers on the dimensions of the institutional environment men-

tioned above.

3. Methods

Over the past two decades, there has been an increasing research effort, which has

significantly advanced both conceptual and empirical understanding of how enterprises,

Fig. 1. The four dimensions of the institutional environment.


economies, and societies innovate and the economic and social effects of such innovation.

However, statistical measures have not kept pace with modern conceptual approaches to

innovation. A dramatic proliferation of innovation surveys has occurred (Archibugi &

Pianta, 1996; Brouwer & Kleinknecht, 1996; Hollenstein, 1996). Industrial associations,

universities, public and private research centers, and statistical offices have produced their

own innovation surveys. However, reviews of the literature show that there has been very

little statistical material at the European level on the resources, which are required for

innovation in different enterprises and industries, on how enterprises access and develop

technology, and on the roles played by innovation in the development of enterprises and in

the evolution of industries.

Recognition of the role of innovation on economic change should therefore be coupled

with an awareness of sharp limitations in the available information. This is especially the case

for information collected in a systematic way at the enterprise level.

3.1. The Community Innovation Survey (CIS)

The CIS is an action of the European Commission (EC) and its Member States. It is the

first time that innovation surveys are carried out at a large scale in a harmonized way in the

12 Member States of the EU (at that time) and Norway, and Iceland. It is also the first time

that microdata of different innovation surveys have been stored in one common database.

The EC harmonized questionnaire was developed on the basis of the Oslo Manual by

Eurostat and the OECD secretariat in cooperation with a team of external experts (OECD &

Eurostat, 1997).

There are essentially two ways of collecting innovation data: the so-called subject

approach and the object approach. In the latter, a single innovation and its sources and

results are studied. In the subject approach, each single firm is studied, including any

innovative project it might have. The last approach is chosen for CIS as recommended

in the Oslo Manual. The method allows aggregation of activity across industries and

countries and allows international comparison if sampling is done properly. Another

advantage is that all innovative activity is included, successes as well as failures. Fi-

nally, firms without innovative activity are included, allowing for comparisons between

those active and those inactive in innovationa matter of great importance for po-

licy making.

There is a general problem of accuracy and reliability when collecting data through survey

questionnaires, in particular when the questions do not match readily available data in the

firms. This is the case with the innovation survey, as most firms do not keep a record of

either innovation inputs or outputs. In effect, the answers cannot be treated as accurate

measures but rather as well-informed estimates by the people responsible in the firms (i.e., as

indicators of the activity going on). In addition, there are several questions asking for

opinions or more qualitative information about the firm and its activities. Such information is

highly dependent upon who the respondent is and what function he or she has in the

organization. On the other hand, many issues relating to innovation are not available as

hard data. Surveying or interviewing may therefore be the best source for collecting more


or less qualitative information. As the same technique has been applied in a series of

countries and most results seem to be relatively consistent across both countries and

industries, I believe them to be a reasonable picture of reality.2

There is no legal basis for the collection of innovation data. Hence, the EC was unable

to impose any demands on Member States and could only compile a list of implementa-

tion and sampling issues, which were presented to Member States as recommendations.

The EC was therefore highly dependent on Member States cooperation. The data trans-

ferred from the Member States to the EC went through a logical consistency check to

verify whether the data were transferred into the appropriate format and position according

to the guidelines.3

3.2. Measurements

Surveys on the hindrances to innovation are quite common, and an attempt to replicate

them would be tedious and of little advantage in the present context. Vickery and

Northcott (1995) give a number of examples of the genre and illustrate the difficulties of

attempting to survey the field. The CIS however is superior to all previous studies in its

breadth and coverage. The questionnaire is developed around eight separate chapters: gen-

eral information, sources of information for innovation, objectives of innovation, acquis-

itions/transfer of technology, R&D activity, factors hampering innovation, cost of

innovation, and impact of innovation activities. This paper is concerned with two chap-

ters of the survey: innovation activity (within general information) and factors hamper-

ing innovation.

3.2.1. Innovative and noninnovative firms

The dependent variable is innovation. The questionnaire is concerned with technological

innovation. A technology is interpreted broadly as the whole complex of knowledge, skills,

routines, competence, equipment, and engineering practice, which are necessary to produce a

product. A new product rests on a change in this underlying technology. More generally,

innovation occurs when a new or changed product is introduced to the market or when a new

or changed process is used in commercial production.

In the CIS questionnaire, two types of innovations are distinguished: significant and

incremental innovations. A significant innovation is a newly marketed product whose

intended use, performance characteristics, technical construction, design or use of materials,

and components are new or substantially changed. Such innovations can involve radically

new technologies or can be based on combining existing technologies in new use. An

incremental innovation is an existing product whose technical characteristics have been

3 Guidelines EC document Doc.Eurostat/D3/REDIS/005 (3rd ECEFTA joint working party on R&D and

innovation statistics, March 1993).

2 For an evaluation of the CIS approach, see Archibugi, Kristensen, and Shaffer (1995).


enhanced or upgraded. This can take two basic forms. A simple product may be improved, in

terms of better performance or lower cost, through use of new components or materials. A

complex product, consisting of a number of integrated technical subsystems, may be

improved by partial changes to one or more of the subsystems.

The dependent variable is derived from the question 1 of the CIS called general

information about innovation activities. Two questions were used to assess the innovative-

ness of the company. The first one asked whether the company had developed or

introduced any technologically changed products (goods or services) during 19901992.

The second one asked whether the company had developed or introduced any technolo-

gically changed processes during 19901992. An innovative firm would be a firm that

answers yes to one of these questions. The dependent variable is coded 1 for innovators and

0 for noninnovators.

3.2.2. Factors hampering innovation

The data for the independent variables are derived from the response to question 12 of

the CIS, concerning factors hampering innovation. Question 12 asked: what have been

the most important difficulties hindering the realization of innovation in your enterprise

Table 1

Variables definition and descriptive statistics

n Mean S.D. Min Max

Attitude toward risk and uncertainty

RISK, Excessive perceived risk 6860 0.354 0.478 0 1

PAYTIME, Pay-off period of innovation too long 6860 0.405 0.491 0 1

COSCONTR, Innovation costs hard to control 6860 0.316 0.464 0 1

RESCHANGE, Resistance to change in the enterprise 6860 0.107 0.309 0 1

UTIME, Uncertainty in timing of innovation 6860 0.155 0.362 0 1

Knowledge acquisition

SKILL, Lack of skilled personnel 6860 0.311 0.462

TECHINFO, Lack of information on technologies 6860 0.142 0.349 0 1

MKTINFO, Lack of information on markets 6860 0.231 0.421 0 1

Access to complementary assets

FINANC, Lack of appropriate sources of finance 6860 0.408 0.491 0 1

COST, Innovation costs too high 6860 0.470 0.499 0 1

EXTSERV, Deficiencies in the availability of external technical services 6860 0.207 0.405 0 1

COOPOP, Lack of opportunities for cooperation with other firms and

technological institutions

6860 0.190 0.393 0 1

Institutional rigidities

COPY, Innovation too easy to copy 6860 0.336 0.472 0 1

REGUL, Legislation, norms, regulations, standards, and taxation 6860 0.311 0.462 0 1

MKTACCES, Lack of customer responsiveness to new products and processes 6860 0.230 0.421 0 1


during 19901992? It includes 15 variables in consistence with the Oslo Manual

(OECD, 1997).4

Using my proposed approach, these variables are classified into four groups: attitude

toward risk and uncertainty, knowledge acquisition, access to complementary assets, and

institutional rigidities. Each variable is on a five-point scale from insignificant to crucial

(Table 1). It is clear that as these variables have not been tailored for this research, they are

used as proxies of the concepts developed in Section 2 of the paper.

3.2.3. Attitude toward risks and uncertainty of innovation

Risks associated with innovation have been proxied by variable RISK, which asked

whether Excessive perceived risk had been a difficulty hindering the realization of

innovation. Concerning uncertainty of innovation, timing was introduced with variable

UTIME Uncertainty in timing of innovation. Cost was introduced as a proxy of

uncertainty with variable COSCONTR Innovation costs hard to control. The rigidity of

companies is assessed by variable RESCHANGE, which represents Resistance to change in

the enterprise.

3.2.4. Knowledge acquisition

In order to approximate the concept of knowledge, two notions are used: (a) the type of

competencies required and (b) the availability of competencies. Human competencies are

approximated by Skilled personnel with variable SKILL on Lack of skilled personnel.

Knowledge is proxied by information and divided in two categories: with variable

TECHINFO on Lack of information on technologies and variable MKTINFO on Lack

of information on markets.

3.2.5. Access to complementary assets

The lack of access to complementary assets is characterized by variable EXTSERV on

Deficiencies in the availability of external technical services and variable COOPOP on

Lack of opportunities for cooperation with other firms and technological institutions.

Access to finance is represented by the difficulty to finance innovation: variable FINANC

Lack of appropriate sources of finance and variable COST on Innovation costs too high.

3.2.6. Institutional rigidities

The difficulty to protect innovation is presented by variable COPY on Innovation too

easy to copy. Regulatory uncertainty is assessed by REGUL, which asked about difficulties

pertaining from Legislation, norms, regulations, standards, and taxation.

The proxy to assess market responsiveness to innovation is represented by variable

MKTACCES on Lack of customer responsiveness to new products and processes.

4 The original survey included 18 variables but several countries did not answer to three of these variables

(12.5 enterprise innovation potential too small, 12.13 lack of technological opportunities, and 12.14 need not

innovate due to earlier innovation). I removed them from the analysis.


The dependent variables (RISK, FINANC, COST, PAYTIME, SKILL, TECHINFO,

MKTINFO, COSCONTR, RESCHANGE, EXTSERV, COOPOP, COPY, REGUL,

MKTACCES, and UTIME) are regressed on innovation activities (product and process

innovations). Both independent and dependent variables are taken from the same ques-

tionnaire. The interpretation should then be: which perceived factors hampering innovation

predicts perceived innovative behavior. Because the variables are categorical, binomial logit

is used for the statistical analysis. The model is estimated using the SAS procedure.

4. Results

The empirical results are summarized in Tables 2 and 3. They provide support for

most of my hypotheses and some results challenge the received wisdom on European

innovation. Table 1 provides descriptive statistics of the independent variables and Table 2

reports the percentage of innovating companies within each country using the estimated

population. The countries included in the analysis are Belgium, Denmark, Germany, Spain,

Ireland, Luxembourg, and Norway. There are 6860 companies in the sample, which re-

present a population of 80,760 companies. Eurostat uses a weighted procedure to estimate

the total population based on industry and size distributions. In each country, the

coefficient of variation between the estimated total population and the sample was less

than 10% (see Appendix A for more details on the methodology). Table 2 provides de-

scriptive statistics on the number of innovators and noninnovators in the sample. Overall,

there are 4453 firms declared being innovative and 2407 noninnovative. When using the

estimated population, there are 47,765 innovative firms and 32,995 noninnovative firms.

The percentage of innovators is higher in Ireland (72%) and Germany (67%) than in the

other European countries that are analyzed in this paper. The percentage is particularly

low for Spain (37%). Table 3 reports the coefficients of the binomial logit. Firms

(n=6860) replied to question 12 on factors hampering innovation out of 42,000, the total

European sample.

Table 2

Percentage of innovators in the estimated population

Innovators based on estimated

population size (%)a Sample size Estimated population size

Belgium 61 600 5959

Denmark 56 638 2944

Germany 67 1994 49,860

Spain 37 2236 18,567

Ireland 72 762 2179

Luxembourg 37 130 171

Norway 53 500 1081

Total 59 6860 80,761a Eurostat uses a weighted procedure to calculate the estimated population within each country (see Appendix A).


Predicted variables represented 63.7% of observed values. It seems to be a remarkable

result in the context of the analysis. Indeed, the model depicts quite well how managers

perceptions differ according to their innovativeness.

The model reads as follows: a negative sign shows that the factor perceived as

hampering innovation does not lead to an innovation outcome. On the contrary, a positive

sign shows that the factor perceived as hampering innovation does not hamper partic-

ipants from innovating. Of all the variables, five show a negative sign: COST (Innovation

costs too high, TECHINFO on Lack of information on technologies), RESCHANGE

(Resistance to change in the enterprise), COOPOP (Lack of opportunities for cooperation

with other firms and institutions) and MKTACCES (Lack of customer responsiveness to

new products).

Table 3

Analysis of maximum likelihood estimates

Dependent variable df

Parameter

estimate

Standard

error Wald c2 Pr >c2Standardized

estimate Odds ratio

Intercept 1 0.8329 0.0196 1800.4938 0.0001RISK, Excessive perceived risk 1 0.0766 0.00768 99.5379 0.0001 0.208703 1.080

FINANC, Lack of appropriate

sources of finance

1 0.0626 0.00655 91.3428 0.0001 0.185935 1.065

COST, Innovation costs too high 1 0.0759 0.00860 77.7829 0.0001 0.224181 0.927PAYTIME, Pay-off period of

innovation too long

1 0.0475 0.00859 30.5642 0.0001 0.134257 1.049

SKILL, Lack of skilled personnel 1 0.0345 0.00707 23.7965 0.0001 0.096034 1.035

TECHINFO, Lack of information

on technologies

1 0.1208 0.00966 156.4799 0.0001 0.280575 0.886

MKTINFO, Lack of information

on markets

1 0.1020 0.00892 130.6848 0.0001 0.257224 1.107

COSCONTR, Innovation costs

hard to control

1 0.1801 0.00801 504.9682 0.0001 0.468013 1.197

RESCHANGE, Resistance to

change in the enterprise

1 0.1712 0.00814 441.9872 0.0001 0.385296 0.843

EXTSERV, Deficiencies in the

availability of external

technical services

1 0.2308 0.0102 510.1094 0.0001 0.573837 1260

COOPOP, Lack of opportunities for

cooperation with other firms and

technological institutions

1 0.2112 0.00902 548.8192 0.0001 0.536622 0.810

COPY, Innovation too easy to copy 1 0.0368 0.00653 31.7862 0.0001 0.105925 1.037

REGUL, Legislation, norms,

regulations, standards, and taxation

1 0.2356 0.00625 1422.2995 0.0001 0.671095 1.266

MKTACCES, Lack of customer

responsiveness to new products

and processes

1 0.0528 0.00734 51.6797 0.0001 0.134938 0.949

UTIME, Uncertainty in timing

of innovation

1 0.1217 0.00814 223.5447 0.0001 0.279839 1.129


4.1. Attitude toward risk and uncertainty of innovation

Hypothesis 1 predicts a negative relationship between a risk-averse attitude and the

innovation output. Variable RESCHANGE representing resistance to change in the enterprise

has a negative and significant sign (0.17). This is consistent with my hypothesis showing the

importance of the aptitude toward change to innovate.

The variable RISK representing excessive perceived risk shows a positive but not very

important coefficient for innovation (0.08). It shows that innovators although aware of the

risk associated with innovation are not afraid of engaging in such a process, revealing a risk-

taking attitude.

On the other hand, COSCONTR representing the difficulty to control costs has a positive

sign with innovation (0.18) as well as UTIME for uncertainty in timing of innovation, which

shows a positive sign for innovation (0.12). The PAYTIME expressing that the pay-off period

of innovation as too long has also a positive sign with innovation (0.04). These three variables

represent the implementation of the innovation process and therefore are more linked to

companies, which are experiencing the innovation process, rather than to noninnovators who

might not be aware of such difficulties.

4.2. Knowledge acquisition

Hypothesis 2 predicts a negative relationship between the ability to acquire knowledge and

innovation. Variable SKILL representing skilled personnel has a very small and positive

coefficient. This variable was maybe perceived as too broad to describe the competencies

necessary for innovation. Variables TECHINFO and MKTINFO representing information on

technology and on market show more important coefficients. Variable TECHINFO, which

represents the lack of information on technology, has a negative and important coefficient for

innovation (0.12). On the contrary, variable MKTINFO, which represents lack of information

on market, has a positive sign for innovation (0.10). This result is particularly interesting,

showing the two sides of innovation: research and technological innovation on the one hand

and its commercialization on the other hand. It indicates that managers perceive they lack the

necessary technological knowledge to innovate. Noninnovators cannot be aware of the

difficulty to market their innovation since this problem appears once technological innovation

has taken place. Innovators on the contrary are fully aware of the difficulty to find a market

for their innovation.

4.3. Access to complementary assets

Hypothesis 3 predicts a negative relationship between the difficulty to access comple-

mentary assets and innovation.

COOPOP characterizing the lack of opportunities for cooperation with other firms and

technological institutions has a negative and important coefficient for innovative firms

(0.21). This is an important finding, which shows the difficulty of European firms to entercooperation with other firms inside or outside Europe.


Variable EXTSERVon deficiencies in the availability of external technical services shows

a positive and very significant sign for innovation (0.23). This reveals that it is not the

availability of external technical services complementary assets that poses a problem to

innovate but the lack of links allowing the access to them. This is therefore consistent with the

finding of variable COOPOP on the lack of cooperative opportunities.

Variable FINANC representing the lack of appropriate source of finance is positive but

shows a low coefficient (0.06). This means that innovators feel that this factor hampers

innovation. On the contrary, variable COST, which represents the cost of innovation, exhibits

a negative sign (0.07). It seems that innovators experience the difficulty to find appropriatesource of finance and that noninnovators feel that their firm cannot support alone the cost

of innovation.

4.4. Institutional rigidities

Hypothesis 4 predicts a negative relationship between regulatory rigidities and innovation.

Variable REGUL representing legislation, norms, regulations, standards, and taxation is

positive with a coefficient of 0.23. This factor is perceived as important only for innovators.

Innovators may face regulatory difficulties, for example, when trying to protect innovation.

Variable COPY representing whether the innovation is to copy also presents a positive sign

for Innovative firms (0.03).

Variable MKTACCES on lack of customer responsiveness to new products and processes

shows a negative sign for innovation. However, the coefficient is not very important

(0.05). This represents the idea that it may be worthless to innovate since the marketwill not be responsive to this innovation. This might be true or false and it is difficult to see

whether the problem resides in managers perceptions of this immovable situation or if

European customers are fixed in their preferences.

4.5. Rankings of the factors hampering innovation by country and size of the company

It is important to check how much these factors vary by country and by size of the

company. The method for the ranking procedure is summarized in Appendix B. The total

sample average ranking for each variable is an average of the ranks allocated by each

country weighted by the number of firms in the sample for each country.

There are minor differences between countries. I consider that there is a variation when a

country has ranked a factor hampering innovation five points below or above the total

average.5 Below are the few variables, which were ranked significantly differently by some

countries. In Germany, the variable TECHINFO is ranked 14 and the average is 9. It means

that for German firms, the lack of information on technologies is not perceived as a problem

hampering innovation when compared to other European firms. The variable REGUL is

5 The number of choices is 15, so a difference of five ranks means 1/3 of the total ranking scale.


ranked 8 as compared to an average ranking of 13. This means that German managers

perceive regulation has a more important factor hampering innovation than do other

European managers. In Spain, the variable COSTCONTR is ranked 11 as compared to an

average of 6. This means that in Spain, innovation costs are not perceived as hard to control

as compared to other European countries. The variable EXTSERV is ranked 7 as compared to

an average of 12. Deficiencies in the availability of external services seem to be a more

important factor hampering innovation in Spain than in other European countries.

In Ireland, COPY is ranked 13 as compared to an average ranking of 8. In Luxem-

bourg, RESCHANGE is ranked 10 as compared to an average ranking of 15, REGUL is

ranked 7 compared to an average ranking of 13, and UTIME is ranked 8 as compared to an

average ranking of 14. In Norway, UTIME is ranked 9 as compared to an average ranking

of 14.

Concerning potential differences in the rankings of factors hampering innovation by the

size of the company, there are also few differences (see Table 4.). Using the same method, I

observe that firms of more than 500 employees rank the variable TECHINF 15 as compared

to an average of 9. Larger firms may indeed have a better access to technological in-

formation than smaller companies. On the contrary, REGUL is ranked 6 compared to a total

ranking of 13. Regulation seems to affect more large firms than smaller firms. UTIME also

ranked 9 as compared to a total ranking of 14, which suggests that uncertainty in timing of

innovation is more important for large firms than small firms. These differences highlight

some variations in perceptions due to the country or the size of the company. However,

there is consistency within the rankings for most of the variables with little variance around

the mean.

Table 4

Ranking of factors hampering innovation by country and size

RISK FINANC COST PAYTIME SKILL TECHINFO MKTINFO

Country

Belgium 3 5 1 2 6 9 7

Denmark 3 4 2 1 5 8 6

Germany 2 3 1 5 7 14 11

Spain 5 2 1 3 4 8 9

Ireland 4 3 1 2 6 7 5

Luxembourg 2 3 1 4 5 13 11

Norway 3 5 1 4 2 8 7

Size

2099 4 2 1 3 5 9 8

100249 3 4 1 2 5 12 8

250499 2 4 1 3 5 12 7

500+ 3 4 1 2 5 15 8

Total sample 4 2 1 3 5 9 7


In conclusion, the hypotheses presented in this paper are confirmed: noninnovative

European firms feel that there is resistance to change in their organization. They lack

technological competencies and have difficulties to access complementary assets and

perceive that customers will not respond positively to the introduction of new pro-

ducts. The situation is slightly different for innovative firms that may face difficulties

during the innovation process: uncertainty of timing of innovation, finding access to

market, and facing regulatory issues. Some of these factors play a more important role

in some countries or according to the size of the company. For example, regulation

seems to be more a burden in Germany and Luxembourg than in other countries and it

is also a problem for firm with more than 500 employees. Firms in Spain seem to have

more difficulties than their European counterparts to access external services. Smaller

firms (2099 employees) have more difficulties than larger firms to access technologi-

cal information.

5. Discussion: toward an institutional approach to innovation

The results show that the most important factors perceived as hampering innovation are

the difficulty to establish cooperation and resistance to change in the enterprise. These

perceptions are linked to real difficulties: cost and rigidities of the European economy.

This pleads for a comprehensive policy approach to the problem, incorporating tech-

nological aspects, training, venture capital development, and the legal and administra-

tive environment.

COSCONTR RESCHANGE EXTSERV COOPOP COPY REGUL MKTACCES UTIME

4 14 15 12 8 13 10 11

9 13 15 14 11 10 7 12

6 15 10 12 4 8 9 13

11 13 7 7 10 14 12 15

8 14 12 9 13 11 10 15

9 10 15 14 12 7 6 8

6 11 14 13 12 15 10 9

6 15 13 11 7 12 10 14

6 15 10 14 7 13 9 14

6 15 14 13 9 10 8 11

7 12 10 14 11 6 13 9

6 15 12 11 8 13 10 14


5.1. Innovation culture and need to foster organizational change

With the increasingly intangible nature of value added, the growing importance of services

and the rise in the application of information technology, organizational flexibility has

become a necessary precondition for companies to offer new products and services. Rigidities

in European company structures appear to work to resist change and impede development of

new products and processes. Many European companies still appear overweight and more

hierarchy-oriented than their American competitors. Integration within and between com-

panies still seems to be more directed toward vertical integration rather than networking or

strategic alliances (CEC, 1996).

The difficulty of firms to engage in thorough reorganization can be explained by several

institutional rigidities as well as the lack of links established to allow firms access to

complementary assets in order to translate their technological investment into marketable

goods and services (Bianchi, 1994; Clark & Guy, 1998).

5.2. High cost and rigidities

The high cost of innovation in Europe can be explained by rigidities and lack of flexibility.

European labor costs in many key sectors are some 3050% higher than in the US.

Flexibility in labor management is restricted by sector-wide wage bargaining, restrictions on

working hours governed by collective agreements, and highly intrusive employment

protection legislation (Kleinknecht, 1998). Prices for key services (e.g., energy, communi-

cations, and transport) remain high in Europe as a result of barriers to entry and restrictive

regulations. With accelerate progress in liberalization elsewhere, the gap between Europe and

its major competitors has been widening.

5.3. Skills shortages

In all EU countries, expenditure on education is substantial and, as a percentage of GDP, is

broadly comparable to that in the US and higher than in Japan (Competitiveness Report,

1996). Despite the increase in general levels of educational attainment, skill shortages are a

common problem for business in many EU countries (Oughton, 1997). Skill shortages can

arise because of restrictions in mobility. This points to inflexibility in education and training

systems and an inability to supply specific skills to meet labor demand (Strange, 1998).

Furthermore, although qualifications are a measure of skills acquired, very often, they are

also the keys to access certain restricted product markets, particularly in services.

All education and training systems in the EU, despite their variety, are based upon

a formal block of concentrated learning at the beginning of employment. The qualifica-

tions system, which as an indicator of how skill levels improve the operation of the labor

market by making it more transparent, is structured around formal initial education and

training systems. This makes access to qualifications, which might improve employ-

ment prospects for workers and respond to employers needs, more difficult at later stages

of employment.


Validating skills, irrespective of how and in which country they were acquired, would also

contribute towards an open EU skills area and support mobility. Many Member States are

reluctant to recognize qualifications gained in other Member States, arguing that the

standards are different and not equivalent.

The opportunity to validate skills acquired in another Member State would enable Member

States to maintain standards but also provide an access route to those trained elsewhere.

It should also be noted that although training arrangements are not harmonized, the

setting of common standards in other areas, such as health and safety and product or

service standards, introduces common elements into the education and training of a wide

range of occupations. These changes are gradually bringing content and standards closer

together. However, it is also increasingly important that employers are able to understand

more readily and easily the content of different qualifications. Systems to improve the

transparency of qualifications should also be examined to contribute to greater mobility

and flexibility. In an environment where technology can quickly change the skills in

demand, systems for rapidly providing adequate new skills to workers are essential (Quinn

et al., 1996).

5.4. Difficulty to access financing

Access to external finance for innovation projects and new technology-based firms appears

to be a major bottleneck for many European entrepreneurs although, recently, special

financial instruments have been developed that aim to channel savings from those who want

to invest in high-risk, high-return projects. Such projects remain underdeveloped as compared

to main European competitors (Boekholt, 1996). For example, in the US, venture capital

plays a significant role in financing innovation. In Europe, it does not. The explanation lies in

part in the different structure of their financial systems. However, it is also due to

administrative and regulatory barriers that have hindered the growth of the European venture

capital industry.

The European venture capital industry has pointed out that it faces important legislative

gaps. In the US, venture capitalists can pool capital in special fund structures. They are

available to investors throughout the US, regardless of their state of residence. In Europe, the

equivalent fund structures do not exist even at the level of the Member States. Many Member

States do not have fund structures that suit local and foreign investors. A pan-European fund

structure is not available.

5.5. A complex regulatory environment

A suitable legal and regulatory environment would nurture innovation. The rules designed

to protect and disseminate innovation (intellectual and industrial property rights and

standards) need to be fully utilized. Cumbersome administrative formalities curb enterprise

formation. Current legal forms do not really facilitate enterprise cooperation and devel-

opment at the European level. Patents play a central role among the different instruments

available for protecting innovation. It is a fact that the patent system has become com-


plicated in Europe, with national patents existing alongside European patents and Com-

munity patents (although the Community patent system has yet to actually come into

operation; Hagedoorn, 1995).

6. Conclusion

Using a logit regression, I find strong support that innovation is linked to the perceptions

of the institutional environment and the organization of competencies internally and between

firms. Research on innovation along with research on organizational change and dynamic

capabilities has been hampered by the lack of measures of managers perceptions. This paper

analyzes innovation output by linking it to the perceptions of managers. The CIS ques-

tionnaire is particularly interesting because it measures how managers perceive factors

hampering innovation. This approach seems particularly well suited in the context of in-

novation where choices are taken with limited information. It shows that managers will direct

their strategies toward innovation in an environment that provides them with access to

complementary assets.

My research confirms and expands the dynamic capability approach to strategy.

Innovation requires, first and foremost, a state of mind combining creativity, entrepre-

neurship, and a willingness to take calculated risks. Innovation requires an attitude open to

change, which is facilitated by organizational flexibility. Building on this approach, I have

proposed that there are four dimensions of the institutional environment that facilitate or

hamper innovation. The first one is the attitude of managers toward risk and uncertainty.

The second one is the ability of firms to acquire new knowledge. It refers to the availability

of skilled personnel and the ease to access information and learn. The third one is the

ability to build interorganizational links and access to complementary assets such as sources

of finance. The fourth one is the regulatory environment, which can favor innovation by,

for example, providing adequate property right regimes and not obstructing the timing of

innovation. The results of this study support these propositions. Firms that (1) perceive

resistance to change within their organizations, (2) feel they lack technological knowledge,

(3) have difficulties to access complementary assets and (4) sense that customers will not

respond positively to the introduction of new products are less likely to innovate.

Innovators may be aware of the risk associated with innovation and emphasize the

institutional factors that hamper the success of innovation such as the difficulty to predict the

timing of innovation, the difficulty to find access to market, and the burden of regulations.

The CIS questionnaire has not been tailored for this specific research. Therefore, some

questions could be adapted to fit the model better. For example, variables concerning

regulation could be more specific. The next CIS, which will provide us with new results in

2001, takes some of these criticisms into account. However, the present CIS data set opens the

way to further analysis. It would be possible to undertake an analysis by country and industry

using NACE code. It would also be possible to test how factors hampering innovation impact

governance structure choices such as alliances as well as to do a comparative analysis

between countries.


Conclusions drawn from this perspective call for policies, which will take into ac-

count the system in which innovation can take place instead of looking at the innovation

output like R&D subsidies. New technologies will not be fully reflected in producti-

vity growth until societal constraints are removed, allowing companies to undergo tho-

rough reorganization.

Traditionally, technology policy has been aimed at the innovation end of the process,

concerning itself almost exclusively with incentives for R&D investments through subsidies

and tax credits or through strong property rights and standards. Research has shown that

R&D policies might not be sufficient to enhance technological innovation and transform

skills into competitive strength (Papadakis, 1995).

This approach has slowly been complemented by a parallel concern for an economic

environment conducive to the diffusion of innovations. A number of countries have put into

place policy measures aimed at encouraging firms to adopt new technologies efficiently,

either by removing regulatory and other obstacles, by using the tax system and fiscal measure

to encourage investment in next machinery, or in assimilation of knowledge developed

elsewhere. Recently, a few public policy measures have been implemented in EU countries to

support new technology-based firms and foster innovation. However, these programs are still

marginal and not included enough into an interdependent system of technological policies

(Storey & Tether, 1998).

Several classes of factors that are important for innovation can be identified: availability of

a labor force with the requisite training and technical skills; decentralized economic

structures that recognize private property and permit considerable autonomy, entrepreneur-

ship, and wealth creation; economic systems that permit and encourage a variety of

approaches to technological and market opportunities; access to venture capital, either

from a firms existing cash flow or from an external venture capital community; good

relationship between the scientific community (especially the universities), the technological

community, users and developers of technology, protection of intellectual property, the

availability of contractual arrangements to enable innovating firms to capture a return from

their investment, and the ability to quickly build or contractually access cospecialized assets

inside or outside the industry. I hope to have made a contribution in showing their

importance as part of the European innovation system.

Acknowledgments

I thank the team of Eurostat for their help on the statistical analysis of this research.

Appendix A. Eurostats method for the weighted procedure

The considering up factors have been calculated as follows:

Consider the breakdown of the enterprises for a particular country by different sizes and

NACE classes.


Let Nx,j be the number of enterprises in size class x and NACE class j in this parti-

cular country.

Let nx,j be the number of enterprises who have answered to the survey in that country.

The weighting factor is (Nx,j)/(nx,j).

Appendix B. Eurostats method for the ranking procedure

Let Q be a question that is divided in, say, four subquestions.

Let Qi be the vector of answers to Q. The elements of the vector are the answer to the

subquestion (Qij=answer of enterprise i to the subquestion j).

For each enterprise, Eurostat ranks these elements according to their values. This

ranking process ranks these values from smallest to largest. Eurostat assigns rank 1 to the

element that has the smallest number, rank 2 to the next largest, and so on up to rank

n, n being the number of elements that has nonmissing values. Two elements that have

the same value are called tied elements. Eurostat gives to those tied elements aver-

age ranks.

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Innovating against European rigiditiesIntroductionAn institutional approach to innovationAttitude toward risk and uncertaintyAbility to acquire new knowledgeAccess to complementary assetsA favorable regulatory environment for innovationRegulation, risk, and uncertaintySkills, labor mobility, and innovationRegulation and access to complementary assets

MethodsThe Community Innovation Survey (CIS)MeasurementsInnovative and noninnovative firmsFactors hampering innovationAttitude toward risks and uncertainty of innovationKnowledge acquisitionAccess to complementary assetsInstitutional rigidities

ResultsAttitude toward risk and uncertainty of innovationKnowledge acquisitionAccess to complementary assetsInstitutional rigiditiesRankings of the factors hampering innovation by country and size of the company

Discussion: toward an institutional approach to innovationInnovation culture and need to foster organizational changeHigh cost and rigiditiesSkills shortagesDifficulty to access financingA complex regulatory environment

ConclusionAcknowledgementsEurostat's method for the weighted procedureEurostat's method for the ranking procedureReferences

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