Elsevier

Research Policy

Volume 33, Issue 8, October 2004, Pages 1185-1199
Research Policy

Complementarities between obstacles to innovation: evidence from France

https://doi.org/10.1016/j.respol.2004.06.004Get rights and content

Abstract

This paper investigates obstacles to innovation faced by French manufacturing firms. Using CIS2 data, we distinguish between obstacles in postponed projects and obstacles in abandoned projects. First, we highlight the most important barriers to innovation faced by firms, and find that lack of skilled personnel is one of these. Second, based on descriptive analysis, correspondence analysis and multivariate probit models, we explore factors explaining the perception of obstacles, and study complementarities between those obstacles. We show that while adopting a package of policies increases the pace of innovation, a more targeted choice among policies is needed to encourage firms to persevere in their innovative efforts.

Introduction

Innovation is the key factor of competitiveness in firms and nations. Many studies have been devoted to the determinants of innovation and of research and development (R&D). The most frequently examined factors are size and type of the firm, technological opportunities, degree of competition, and capacity of appropriation of the innovation benefit (see Cohen and Levin, 1989, Freeman, 1990, Cohen, 1995, Encaoua et al., 2000, Kleinknecht and Mohnen, 2001). 1 However, an alternative approach which studies obstacles to innovation has been marginalized. 2 In this paper, we pursue this latter approach.

Innovation survey data (CIS2) is used to investigate obstacles to innovation faced by French manufacturing firms. By using an econometric approach based on a multivariate probit model a new feature is introduced. The data used allow us to distinguish between obstacles in postponed projects and obstacles in abandoned projects. Compared to previous studies, this distinction is new.

The aim of this paper is twofold. First, the general perception of obstacles by French firms is examined and the most important barriers to innovation faced by them are highlighted. Further, obstacles encountered by firms according to their size, technological intensity, group membership and activities dedicated to innovation (internal and external R&D, training and cooperation) are investigated. The data allow us to respond to the following questions: what are the types of obstacles perceived by firms during the process of innovation? do these include excessive risk, lack of financial support, shortage of qualified personnel or internal resistance to change? does lack of information, too much red tape, excessive regulation or lack of market opportunities constitute important barriers to innovation?

Second, complementarities between the above obstacles are studied, and highlighted in order to establish groups of impediments. For example, high costs perceived as an obstacle to innovation are probably linked to a perceived lack of private financing or outside capital. Moreover, a lack of private financing can be expected to be associated with a lack of outside capital since inadequate capital stocks can alter the conditions of financing. In particular, in the risk area of innovation, capital outlay on the part of innovators is desirable or even required in order to find funding (CGP, 1999).

Likewise, shortage of qualified personnel and organizational rigidities can be expected to lead to problems for the feasibility and eventual success of innovations. Since innovation first takes place in the minds of imaginative people, innovative firms can be viewed as a knowledge-based organizations (Dodgson and Rothwell, 1994, Tidd et al., 1997). Consequently, highly skilled personnel and scientific experts are important since they constitute a prerequisite for innovation (OECD, 2000, OECD, 2001). Organizational arrangements have to be capable of creating, sharing and transferring knowledge via adequate internal communications between various departments (R&D, marketing, production). Therefore, a lack of skilled personnel may lead to internal rigidities according to the dynamics of innovation. Innovation can therefore be described as a coupling process which integrates a skilled work force and an adequate organization.

Further, lack of information on technologies, lack of information on markets, and lack of customer responsiveness can reinforce uncertainty as far as innovation is concerned. This involves a process of matching technical possibilities and market opportunities (Freeman and Soete, 1997). In other words, it involves, on the one hand, the recognition of the needs of potential users or, more precisely, a potential market for new products or processes, and, on the other hand, technical knowledge, which may be generally available, but often may also include in new scientific and technological knowledge. Therefore, firms which neglect the specific requirements of potential markets or costs of their innovation in relation to the market are likely to fail as innovators. Moreover, firms which lack the necessary scientific competence to develop a satisfactory product or process will fail as innovators, no mater how good their appreciation of the market is. Finally, other institutional obstacles can hamper the successful outcome of an innovation project.

These complementarities provide some insights about innovation policy. If some obstacles are interdependent or reinforce each other, it will be futile to combat them individually. Interdependence is one reason why it is meaningful to apply a system’s perspective. Moreover, sub-optimizing and neglecting important couplings between policy areas is especially problematic in an economy characterized by rapid change. This implies a need to adopt a system approach. An innovation system is based on a number of rules, legislation, regulations, institutions, types of funding, organizations, choices of location, networks of actors, and educational and training programs. In short, an innovation system is based on a set or arrangement of components so related or connected as to form a unity or organic whole linked to innovation (Andersen et al., 2002). The use of the innovation system’s concept permits us to demonstrate the need to integrate and coordinate different policy areas that do not tend to be seen as separate and independent. This paper highlights the components of such a system as well as its limits.

This paper is organized as follows: Section 2 describes the data; Section 3 presents a descriptive analysis of obstacles to innovation according to a number of explanatory variables; Section 4 analyzes complementarities between obstacles using a correspondence analysis method and an econometric approach based on a multivariate probit model, and then the main results are presented and discussed; Section 5 is a conclusion.

Section snippets

Data

The data used for this paper come from the second French “Community Innovation Survey”, “L’Innovation Technologique dans l’Industrie” (CIS2) over the period 1994–1996, carried out by the SESSI. 3 This survey belongs to the Community Survey 4 on technological innovation (for a detailed description, see François and

Obstacles to innovation: descriptive analysis

The nine obstacles to innovation are given in Table 1. As stated above, the originality of the data enables us to distinguish between obstacles to postponed projects and obstacles to abandoned projects. In this section, the most important obstacles faced by firms are identified, and firms’ general perceptions of obstacles according to their size, technological intensity, group membership and innovation activities are examined.

Table 1 highlights the various difficulties which appear during

Complementarities between obstacles to innovation

In this section, possible interrelationships and complementarities between obstacles to innovation are studied. We seek to know which obstacles go hand-in-hand and what are the possible groupings. Initially, binary correlations between obstacles are examined, and then, a correspondence analysis is carried out in order to identify groups of obstacles to innovation. Finally, using an econometric approach based on a multivariate probit model, the factors explaining the perception of obstacles are

Conclusion

During the process of innovation, firms encounter various obstacles. Using the French CIS2 data, we analyze the original distinction between obstacles to innovation in postponed projects and in abandoned projects. The two main results of this paper are the following.

First, we examine the general perception of obstacles and highlight the most important barriers to innovation perceived by French manufacturing firms. We show that firms postponing projects are more prone to face obstacles linked to

Acknowledgments

We are grateful to G. Ballot, D. Encaoua, G. Eliasson, S. Lhuillery, S. Lotz, J. Mairesse, P. Mohnen, P. Sevestre, and two anonymous referees for their helpful comments. We also thank participants to: 2001 Onzièmes Journées du SESAME; ERMES Seminar; Paris I Workshop Economics of Innovation; 2002 DRUID Summer Conference; 2002 AFSE Congress. The usual disclaimer applies.

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