Internal factors determining a firm’s innovative behaviour

Research Policy 32 (2003) 715–736

Internal factors determining a firm’s innovative behaviour Jesús Galende a,∗ , Juan Manuel de la Fuente b a

Departamento de Administración y Econom´ıa de la Empresa, Facultad de Econom´ıa y Empresa, University of Salamanca, Campus “Miguel de Unamuno”, E- 37007 Salamanca, Spain b University of Burgos, Burgos, Spain Received 30 October 2001; received in revised form 10 April 2002; accepted 20 May 2002

Abstract The present paper investigates the determinant factors in the organisation of a firm’s innovative activities. Set within a theoretical framework combining evolutionary theory and the resource-based view of the firm, the study includes an original proposal to characterise the innovative process and determines the extent to which a firm’s internal resources and factors explain the innovative process. By applying the econometric analyses techniques to a sample of 152 Spanish innovative companies, empirical findings confirm the existence of interesting relations between internal factors and the innovative process. © 2002 Elsevier Science B.V. All rights reserved. Keywords: Innovation; Research and development; Innovative process; Resources and capabilities; Evolutionary theory

1. Introduction In a review of theoretical and empirical literature about innovation, it is customary to find papers that analyse the results of innovation, whether expenditures, staff employed, patents obtained, or innovations generated, often from the point of view of their determinants. These studies consider implicitly that all the firms go through the same innovative process. However, there is actually great diversity in the firm’s innovative activity that can have an effect on the results of innovation. This paper is part of an extensive investigation that analyses a firm’s innovative process from an internal point of view. It tries to open the firm’s black box and to investigate the structure of its innovative process, the factors having an influence on the process, the existing variety in the combination ∗ Corresponding author. Tel.: +34-9-23294400x3509; fax: +34-9-23294715. E-mail address: [email protected] (J. Galende).

of both groups of variables and the innovative result that is finally reached. Specifically, the aim of the present paper is to analyse whether the innovative process, formed by a group of innovative characteristics, is explained by the firm’s internal resources and factors, be they tangible, intangible or strategies. It investigates the dependence relation existing between the innovative behaviour of the Spanish companies and their internal factors. Therefore, it is based initially on the classic analysis of the innovative result determinants, but it is applied to the way in which the innovative activity is developed. The paper tries to answer the two basic problems that Dosi (1988a, p. 1121) recognises in the analysis of innovation: the characterisation in general of the innovative process and the interpretation of the factors that explain the differences among firms in their innovative activity. The aim of the study is to understand the firms’ innovative behaviour. The empirical literature is very scanty concerning the issue, because it the result of innovation directly.

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This paper is structured in the following way. Section 2 defines the theoretical framework of the investigation. Subsequently, the firms’ internal factors and the innovative characteristics that delimit the innovative process are described in Section 3. Sections 4 and 5 present the theoretical model, the hypotheses and the methodology of the study. The empirical test includes two phases: first, Section 6, where an exploratory analysis is carried out. The purpose is to summarise and reduce the extensive variety of data used in the study. Second, Section 7, the explanatory analysis attempts to investigate the incidence of internal resources and factors on the explanation of the innovative process. Finally, the main conclusions derived from the analysis are given in Section 8.

2. Theoretical framework In economics and business management, neoclassical economics is the traditional method of carrying out an innovation analysis. This theory has an excessively simple vision of technology, which is considered as a parameter of the production function, with a static nature, exogenous to the firm and with a uniform distribution among the companies. After the studies of Schumpeter (1934, 1942), technological change began to receive greater attention. The fundamental part played by technology in economic development is taken into account, and the figure of the innovative manager is investigated. This author proposes two factors, the size of the company and the market concentration, as direct determinants of technological progress, factors which will later be taken up by industrial organisation. This approach is key to understanding the influence of external factors on innovation, whether sectoral or public incentives. However, it does not consider other internal factors that also determine the innovative activity, or how the innovative process occurs inside the firm. Other approaches should be considered. Additional perspectives have adjusted the analysis more to reality. Among these approaches, we can refer to transaction cost economics (Williamson, 1975, 1985), the positive theory of agency (Jensen and Meckling, 1976), the evolutionary theory (Nelson and Winter, 1982) and the resource-based view of the firm (Wernerfelt, 1984).

Transaction cost economics points out the imperfections of the innovative activity, such as specificity, uncertainty and information asymmetries. These characteristics hinder the application of the market mechanism and they recommend its internalisation or other intermediate structures. The positive theory of the agency reveals the influence of the divergence of interests among the firm’s economic agents on the innovative activity. Under these conditions and in addition to the existing information problems, the firm’s technological investment can become smaller. The evolutionary theory is centred on the analysis of the way in which firms develop their innovative process. It adopts a dynamic view of the technology, in a context of constant change and evolution, with a tacit, complex and systemic character (Garud and Nayyar, 1994, p. 371) and an accumulative nature (Malerba and Orsenigo, 1990, p. 285). It points out how the process depends on its past history and its irreversible nature with regard to the technological path (Pavitt, 1987, p. 187; Dosi, 1991, p. 354). Unique firm technological capacities which will determine the firm’s future behaviour originate in combination with multiple features of both a formal and informal nature that the theory describes. A base of knowledge is built which is difficult to transfer (Winter, 1987, p. 173), and which is opposed to the concept of public good of classical analysis (Pavitt, 1984, p. 343; Dosi, 1988b, p. 225). The existence of significant differences among firms in terms of technological capacities is underlined. It is a fundamental approach for carrying out a correct characterisation of the innovative process. The resource-based view makes an internal analysis of innovation. It points out that its most important characteristic is that it is information based, and thus can be developed over time (Wernerfelt, 1984, p. 174). This resource forms an important source of competitive advantage for the company (Barney, 1991, p. 110) because it is valuable and scarce, because it does not depreciate with use (Itami, 1987, p. 13) and because it is not easily transferable. It is also because it can frequently be appropriated (depending on its protection, its complexity and on the possession of the complementary assets), and it is difficult to imitate on account of time compression diseconomies (Dierickx and Cool, 1989, p. 1507). The approach reveals the importance, in general, of internal resources, whether physical, financial, human or organisational,

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and therefore, everything must be included in the analysis. The analysis of the five perspectives implies the existence of two models of approach to the innovative process:

Table 1 Factors and variables analysed

Tangible

Size Debt

(1) The industrial organisation model. This carries out a linear analysis of technology, attributing it with a strong information component and considering it as a direct line between science and innovation. From this approach, innovation is fundamentally determined by a firm’s external factors and companies are characterised by their passive behaviour. (2) The evolutionary model. This analyses the innovative process. It considers it in a diverse, dynamic, continuous and accumulative way, and considers knowledge as its main component. The tacit, complex and systemic character of the innovation is highlighted. It undergoes a past-dependent process and has a certain irreversibility with regard to the technological path followed.

Intangible

Human resources Commercial resources Organisational resources

Strategies

Diversification Internationalisation

It is thought that many factors affect the innovative process, not only factors external to the firm, but also its internal resources, hence, the resource-based view will be fundamental. These two approaches form our framework, although the rest of the perspectives may be applied at specific moments.

3. Internal factors and innovative characteristics Given that the aim of the paper is the analysis of how internal determinants affect the firms’ innovative behaviour, it is advisable to carry out a brief review of these factors. Theoretical arguments and empirical studies about the form and intensity of their influence are explained. In accordance with the resource-based view, an extensive group of factors is considered. They are given in Table 1, which also includes some features for characterising the innovative process according to the evolutionary theory. Tangible factors are easily measurable and they have frequently been analysed in a great variety of studies. The size of the firm is what is most contrasted in the literature. The studies of Schumpeter (1934, 1942) had already proposed its influence. With regard to its incidence on the innovative result, arguments exist both

Factors Internal

Generic variables

Innovative characteristics

Methods of generation Sources of information Accumulative nature Objectives Mechanisms for appropriating the results Types of R&D and innovations

Source: own elaboration.

supporting a large size (greater economies, smaller risk, greater market, better appropriation possibilities) and supporting a small size (greater flexibility, better communication, greater specialisation possibilities, informal and strategic controls). In accordance with this theoretical variety, a great empirical disparity can also be observed. Some studies favour a large size (Horowitz, 1962; Lunn and Martin, 1986; Braga and Willmore, 1991; Henderson and Cockburn, 1996; Gumbau, 1997; Arundel and Kabla, 1998) while there are others that have not been able to show its positive influence (Worley, 1961; Mansfield, 1964; Grabowski, 1968; Adams, 1970; Loeb and Lin, 1977; Scherer, 1984; Acs and Audretsch, 1988; Graves and Langowitz, 1993). Also, there are studies that emphasise the better adaptation of intermediate sized firms (Scherer, 1965b; Mansfield et al., 1971; Smith, 1974; Kumar and Saqib, 1996) or of both large and small size at the same time (Rothwell, 1986; Pavitt et al., 1987; Rothwell and Dodgson, 1994). Given this disparity of results, it seems necessary to take into account intermediate variables in the relationship. This was also done in the studies by Mansfield (1981), Pavitt et al. (1987), Busom (1993), Cohen and Klepper (1996), Molero and Buesa (1996), and Yin and Zuscovitch (1998). Another factor of a tangible nature is the level of debt. From a theoretical point of view, transaction cost

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theory and the positive theory of agency must necessarily be taken into account. They argue that debt financing can discourage innovative activities. The first one analyses the high specificity and intangibility of technological investments. This increases transaction costs and seems to dissuade debt financing. The second theory shows the high risk of these activities and the existing information asymmetries, which cause problems with debt financing. Abundant empirical evidence points to this negative influence (Grabowski, 1968; Elliott, 1971; Branch, 1974; Kamien and Schwartz, 1978; Hall, 1990; Long and Ravenscraft, 1993; Giudici and Paleari, 2000). However, some studies have not been able to confirm this (Scherer, 1965a; Lafuente et al., 1985). In any case, some differences are found regarding this influence that may be useful to take into account: the radical or incremental nature of the innovation or the amount of basic R&D. Intangible resources are more difficult to measure, hence empirical literature is limited (Cohen, 1995, p. 233). However, their relationship to innovation can be very significant. Among them, human resources comprise a team of scientists and technicians with suitable qualifications and experience in R&D, and innovative activities. Empirically, the studies of Galende and Suárez (1998, 1999) and Mart´ınez-Ros and Salas (1999) suggest a positive influence on innovation, although this could be different according to the specific characteristics of the process. Other intangible factors are the commercial resources. These are direct determinants of the reputation and image of the firm as regards their users. Hence, they are a part of the complementary resources (Teece, 1987) that permit the appropriation of results and that can provide useful information about the needs and opinions of the users. The “SAPPHO Project” studies, mentioned by Freeman (1973) and Rothwell et al. (1974), point to commercial resources (specifically the correct understanding of the user’s necessities and the better efforts in marketing and publicity) as one of the determinants of the success or failure of the innovation. In the same way, the studies of Doi (1985), Lunn and Martin (1986) and Gumbau (1997) verify a positive influence of these resources on the innovation. However, this incidence differs in degree according to the specific features of the innovative process.

A third intangible factor comprises the organisational resources. As Bughin and Jacques (1994, p. 654) and Dyerson and Mueller (1999, p. 647) point out, these include the efficiency and synergies existing between marketing and R&D, the communication capability within the firm, the managing and organisational excellence, the promoting of the integration of knowledge through teamwork and the fostering of learning from external sources. For this last aspect a suitable capacity for absorbing outside knowledge (Cohen and Levinthal, 1989, 1990) is necessary, which would facilitate the assimilation, improvement and exploitation of the existing information. In the empirical literature, the “SAPPHO Project” studies, mentioned by Freeman (1973) and Rothwell et al. (1974), as well as the studies of Rothwell (1986) and Bughin and Jacques (1994) confirm the impact of organisational capacities on the success of a firm’s innovative activities. The age of the firm is a possible measure of its organisational resources. It represents the experience and knowledge accumulated throughout its history and is related to a better management of communication and of necessary creativity to innovate, and to a more effective capacity for absorption. It is a variable commonly used to measure the experience and the learning of the firms, factors that are organisational resources. The studies by Busom (1993), Kumar and Saqib (1996), Molero and Buesa (1996), Gumbau (1997) or Kuemmerle (1998) use this variable. All of them verify a positive impact of age on innovative activity, except Molero and Buesa (1996), who showed that young companies dedicated more resources to innovation. However, their influence can be seen in diverse ways, which should be taken into account. An alternative measure of the organisational resources is the existence of a formal department of R&D in the company. Although the innovative process can be developed in diverse ways, the existence of this department inside the organisational structure indicates the concession of great importance to the activity and thus the dedication of effort to its organisation. Some studies use this measure. Kleinknecht and Reijnen (1992) show a positive impact on the possibility of using external sources of knowledge. This gives evidence of a relationship between the existence of this department and a better capacity for absorbing outside knowledge, a factor included within the organisational resources.

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A third group of a firm’s internal factors is formed by its strategies. One possible strategy is diversification, and it may become necessary to institute formal and financial controls in order to manage it. These controls can discourage technological activity because they undervalue innovation (Hill et al., 1988; Hitt et al., 1990; Hitt and Hoskisson, 1991). The presence of informal and strategic controls more compatible with the technological investment would be necessary, but this is difficult in a diversified company. Diverse studies exist in the empirical literature, based on the positive theory of agency, which confirms a negative relationship between diversification and innovation (Hoskisson and Hitt, 1988; Baysinger and Hoskisson, 1989; Hoskisson and Johnson, 1992; Hoskisson et al., 1993). However, others verify a positive influence, especially in the case of related diversification and basic research (McEachern and Romeo, 1978; Link, 1982;

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Chen, 1996). This again points out the existence of unexplored aspects in the relationship. A second strategy analysed is internationalisation. It can be related to the development of technological capacities, because it implies greater competitiveness and an increase in market size. The empirical literature shows a positive relationship between exports and R&D and innovation investments. For example, see the studies of Meisel and Lin (1983), Lunn and Martin (1986), Braga and Willmore (1991), Kumar and Saqib (1996) and, in the Spanish case, of Busom (1991), Labeaga and Mart´ınez-Ros (1994) and Galende and Suárez (1998, 1999). Nevertheless, research into the intensity of the relationship according to the specific characteristics of the innovative process could be interesting. Table 2 offers a summary of the main theoretical arguments and empirical studies concerning the effect

Table 2 Internal factors and innovation Factor

Theoretical arguments

Empirical studies

Size

Large: economies, risk, market, appropriation

Large: Horowitz (1962), Lunn and Martin (1986), Braga and Willmore (1991), Henderson and Cockburn (1996), Gumbau (1997), Arundel and Kabla (1998) Small: Worley (1961), Mansfield (1964), Grabowski (1968), Adams (1970), Loeb and Lin (1977), Scherer (1984), Acs and Audretsch (1988), Graves and Langowitz (1993) Intermediate: Scherer (1965b), Mansfield et al. (1971), Smith (1974), Kumar and Saqib (1996) Both: Rothwell (1986), Pavitt et al. (1987), Rothwell and Dodgson (1994)

Small: flexibility, communication, specialisation, informal controls

Debt

Negative: specificity, risk, information asymmetries

Negative: Grabowski (1968), Elliott (1971), Branch (1974), Kamien and Schwartz (1978), Hall (1990), Long and Ravenscraft (1993), Giudici and Paleari (2000) Positive: Scherer (1965a), Lafuente et al. (1985)

Human resources

Positive: qualification, experience Positive: reputation, image, complementary resources, information Positive: co-ordination, communication, integration, absorptive capacity Negative: formal and financial controls

Positive: Galende and Su´arez (1998, 1999), Mart´ınez-Ros and Salas (1999) Positive: Freeman (1973), Rothwell et al. (1974), Doi (1985), Lunn and Martin (1986), Gumbau (1997)

Commercial resources

Organisational resources

Diversification

Positive: Freeman (1973), Rothwell et al. (1974), Rothwell (1986), Kleinknecht and Reijnen (1992), Busom (1993), Bughin and Jacques (1994), Kumar and Saqib (1996), Gumbau (1997), Kuemmerle (1998) Positive: McEachern and Romeo (1978), Link (1982), Chen (1996) Negative: Hoskisson and Hitt (1988), Baysinger and Hoskisson (1989), Hoskisson and Johnson (1992), Hoskisson et al. (1993)

Internationalisation

Source: own elaboration.

Positive: competitiveness, market

Positive: Meisel and Lin (1983), Lunn and Martin (1986), Braga and Willmore (1991), Busom (1991), Labeaga and Mart´ınez-Ros (1994), Kumar and Saqib (1996), Galende and Su´arez (1998, 1999)

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of internal factors on the innovative activity. It is easy to see that the traditional course of theoretical argument and of empirical contrast deals with the direct impact of the internal factors on a firm’s innovative result. This is the aim of the greater part of the studies, and it is the cause of the frequently contradictory empirical evidence. Studies that show a positive impact of the factor coexist with others that seem to indicate a negative influence. It is reasonable to think of the existence of intermediate variables, which may be determined by the characteristics of the innovative process. These could determine the sign and the magnitude of the relationship between resources and internal factors and innovative result, and therefore, they should be considered. This has been carried out only in very few studies, because of the qualitative nature of the statistical data. Specifically, some arguments and studies consider that, before finally affecting the innovative results, size can influence the generation of process innovations (Yin and Zuscovitch, 1998), incremental innovations (Cohen and Klepper, 1996) and the carrying out of basic research (Mansfield, 1981); debt can negatively influence the execution of radical innovations (Kamien and Schwartz, 1978); commercial resources can affect the appropriation of the results by means of complementary resources (Harabi, 1995) and the utilisation of the users as sources of technological information (Freeman, 1973; Rothwell et al., 1974); organisational resources can influence the carrying out of basic and applied research (Busom, 1993) and diversification can also affect the performing of basic research (Link, 1982). The combination of the resources and internal factors can determine the type of innovative process used by the firm. The evolutionary theory is essential for carrying out a specification of the process by means of certain innovative characteristics. These are basic parameters that give evidence of the inadequacy of the traditional model concerning innovation that only analyses superficial factors. In this paper, the following innovative features are considered: • Alternative methods for generating technology: internal method through R&D activities, internal method through other innovative activities, co-operation, and external purchase (Pavitt, 1984; Malerba and Orsenigo, 1990; Buesa and Molero, 1998b).

• Sources of scientific and technological information: internal source of R&D and innovation personnel, internal source of other personnel, external source of suppliers, users, other companies or universities and R&D centres, and analysis of the available information (Pavitt, 1984; Busom, 1993; Veugelers and Cassiman, 1999). • The accumulative nature of the innovative activity (Malerba and Orsenigo, 1995; Buesa and Molero, 1998a). • General objectives of the innovation: objectives of process, objectives of product, objectives of entry into new markets, and objectives of penetration into the current markets (Busom, 1993; Buesa and Molero, 1998b). • Mechanisms for appropriating the results: patents, industrial secrecy, cost and time for imitation, continuous innovation, and complementary resources (Pavitt, 1984; Malerba and Orsenigo, 1990; Molero and Buesa, 1996). • Type of R&D and innovations: basic research, applied research, technological development, product innovations, process innovations, radical innovations, and incremental innovations (Pavitt, 1984; Busom, 1993; Molero and Buesa, 1996). These innovative characteristics are used to show the variety of technological activity. The integration of the innovative characteristics into an explanatory model of the innovative process is proposed with the aim of clarifying the analysis.1 Fig. 1 represents this model.

4. Model and hypotheses The theoretical framework and the analysis of internal factors and innovative characteristics have been dealt with in previous sections. Now we shall propose our theoretical model, represented in Fig. 2. The arrows represent the interaction and mutual dependence among the different types of internal factors, although testing these relations is not the aim of the present paper. The relationships analysed are the shaded ones: 1 Busom (1993, p. 61) points out, within the limitations of the study, the necessity for the development of formal models that consider different variables and factors of R&D expenditures and the market structure.

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Fig. 1. An explanatory model of the innovative process. Source: own elaboration.

the influence of the whole group of factors on the innovative characteristics. In relation to the formulation of the hypotheses, it is necessary to take into account the limited previous empirical evidence and the great variety of variables analysed. Hence this study contains a general proposition which seeks to carry out exploratory work on the topic under study. It proposes that internal factors can indeed determine the characteristics of a firm’s innovative activity. P: “Internal resources and factors affect the configuration of the firm’s innovative process” Nevertheless, this initial premise is divided into several hypotheses, which seek to show the specific impact of internal factors on the innovative characteristics. In the first place, greater size can mean that the

innovative activity will be more accumulative because of the greater possibility of steadily using a larger quantity of resources over time. On the contrary, a small company must carry out more occasional innovations when the opportunity arises, and the accumulation is less. The study by Buesa and Molero (1998a) confirms this for the case of innovative regularity related to this accumulative nature. These arguments lead us to pose the following hypothesis: H1 : “Greater size increases the accumulative nature of the innovative activity.” The second tangible factor is the level of debt. The availability of internal funds can allow greater risk of radical innovations to be confronted in a more effective way. On the contrary, debt financing must be closely connected with incremental innovations.

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Fig. 2. Internal determinants of the innovative process. Source: own elaboration.

In the same way, the availability of internal funds can make it possible to overcome the opportunistic problems connected with revealing to the market the important technological information of the completely new innovations. On the other hand, debt financing can compel the limitation of risk through incremental innovations. Furthermore, radical innovations possess a lower liquidation value than incremental ones. The latter contain a previously developed physical component. This again reinforces the relationship between debt and incremental innovations. The relationship between equity capital and radical innovations is verified in the study by Kamien and Schwartz (1978). These arguments lead us to pose the following hypothesis: H2 : “Debt financing determines the generation by the firm of a high proportion of incremental innovations.” In relation to the intangible factors, a high stock of qualified human capital, composed of a good team of scientists and engineers, can be related to a greater accumulative nature of the innovation. Qualified personnel can carry out more intense and continuous research work, because of their training. These employees

have assumed the obligation of constantly innovating over time, on occasion owing to their very profession. For this reason, we must relate these resources to the constant development of innovations, that is to say, to the variable of the accumulative nature of the innovative activity. The proposed hypothesis is the following: H3 : “The possession of superior human resources increases the accumulative nature of the innovative activity.” Investment in commercial resources may indicate that the company fundamentally makes product innovations. The firm tries to achieve the greatest possible profitability internally through its differentiation with marketing variables. This relationship between differentiation and innovation is verified partially, depending on the size of the firm in the study by Gumbau (1997). Furthermore, commercial resources are an important complementary resource. Harabi (1995) notes that they are the most effective way to appropriate the results of product innovations. This fact may also imply a more intense utilisation of users as a source of technological information. This is in

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fact possible because of the possession of superior commercial resources. To summarise, the hypothesis regarding the relationship between a firm’s commercial resources and its innovative characteristics is the following: H4 : “The possession of superior commercial resources is strongly related to an intense development of product innovations, with a greater significance of complementary resources as a form of appropriation of the results and with a greater utilisation of users as sources of technological information.” Organisational resources mainly stem from the firm’s experience formed over time, which entails better organisation and a certain consolidation of its innovative activity. This can imply the development of innovations over a long period, that is to say, a greater accumulative nature of the innovative process. Furthermore, it can encourage the use of internal methods of technology generation. Organisational resources can also allow the firm to take advantage of internal and external sources of technological information. This is verified in the “SAPPHO Project” studies, mentioned by Freeman (1973) and Rothwell et al. (1974). In the same way, they can be related to greater investment in basic and applied research, because they require greater experience and accumulated knowledge than technological development. This is confirmed by Busom (1993). Therefore, a new hypothesis can be deduced: H5 : “The possession of greater organisational resources implies a greater accumulative nature of the innovative activity, a greater use of an internal method of technology generation, a greater use of internal and external sources of technological learning and greater investment in research than in technological development.” In relation to the strategies, high diversification can determine greater investment in basic research, because of its extremely variable results. Diversified firms are in a better position to take advantage of this internally. This internal exploitation of the basic research is also necessary because of the opportunistic problems connected with the use of the market. The relationship between diversification and basic research is argued by Nelson (1959). Empirically, Link (1982) verifies a positive influence of diversification on the effort dedicated to basic research. From this we deduce a new hypothesis:

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H6 : “A firm’s high degree of diversification encourages the dedication of a high percentage of the R&D investments to basic research.” The strategy of internationalisation can be related to a greater emphasis on market objectives for the innovation, specifically with the aim to enter new markets. Several objectives can be pursued by the company in its internationalisation, but the extension of the current markets is the fundamental one. Furthermore, in the Spanish case, internationalised firms are strongly committed to technological activities. This may be related to a greater accumulative nature of the innovative process. The study by Buesa and Molero (1998a) verifies this for the degree of innovative regularity, which is a characteristic highly related to this accumulation. The following hypothesis can thus posed: H7 : “A higher level of internationalisation positively affects the accumulative nature of the innovative process and the entry into new markets as an objective of the activity.” Table 3 summarises the general exploratory proposition and the seven working hypotheses of the present paper.

5. Methodology The whole population used for testing the hypotheses, and hence, the theoretical model, is formed by firms carrying out innovative activities in Spain. These activities consist of internal R&D and investments in other technical innovative activities. The database of the Industrial Technological Development Centre (CDTI) of Spain was used as the source for primary information.2 This database has already been used in some studies, such as Buesa and Molero (1998a), Molero and Buesa (1996) and together with other databases in Busom (1993). As Buesa and Molero (1998a, p. 113) argue, the CDTI has granted credits to the most of the Spanish innovating firms and it also has a rigorous process of selection of the financed projects. For this reason, 2 The CDTI is a public organisation, dependent on the Ministry of Science and Technology aiming at promoting the innovation and the technological development of Spanish companies. Its database offers a directory of firms which this organisation recognise are carrying out innovative activities, mainly because they have applied for grant of a Spanish or European innovative project.

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Table 3 Proposition and hypotheses Hypothesis

Independent variable

Dependent variable

Relation

H1 H2 H3 H4

Size Debt Human resources Commercial resources

Accumulative nature Incremental innovations Accumulative nature Product innovations Appropriation through complementary resources Source of information of users

+ + + + + +

H5

Organisational resources

Accumulative nature Internal method of generation Internal and external sources of information Basic and applied research

+ + + +

H6 H7

Diversification Internationalisation

Basic research Accumulative nature Objectives of entry into new markets

+ + +

P

Internal resources and factors affect the configuration of the firm’s innovative process

Source: Own elaboration.

the innovating firms of the CDTI database constitute a good approach to the universe of Spanish firms that have technology investments. In fact, the R&D statistic of the Spanish National Statistic Institute (INE) has been formed with firms that have received public financing to carry out this activity at some moment. Therefore, the CDTI’s database includes most of the Spanish innovating firms and the study is tested on a valid and reliable population. It is a dynamic database since firms are continuously introduced into the database in the year the CDTI has knowledge of that they carry out innovative activities. This makes it difficult to determine the exact number of innovating firms of the database, although we estimated about 3000 companies at the moment of realisation of our empirical study. A population of 472 Spanish innovative companies was randomly selected from the CDTI database, although an additional criterion was applied: these firms should have technological importance. This restriction was specified by requiring from firms in the selected population to fulfil at least one of the two following conditions: (a) They have been carrying out innovative activities for not less than 5 years. This implies that at the current time, the companies in the sample have a long innovative trajectory, and have been able to consolidate this activity.

(b) They have participated in two or more high demanding innovative programmes, for example, the European Community Framework Programme, Eureka or the Spanish National R&D Plan. It implies that the companies are characterised by a high technological activity, since this is a indispensable requirement to participate in such programs. The available data in the database were very scanty and had diverse time references. For this reason, it was necessary to use secondary sources. The questionnaire technique was, therefore, applied by means of a meticulous design process in order to obtain the most objective information. Special attention was paid to the necessary data for approaching the factors described in Section 3 (internal factors and innovative characteristics). After an analysis of the possible alternative measures, the approaches defined in Table 4 were used. Additionally, 14 dummy industry variables were also included in the analysis to control for interindustry differences in factors, such as technological and economic opportunity, appropriability of the results or market concentration. The variables allow us to identify the following industrial sectors: agriculture, energy, metal industry, non-metallic products, chemical industry, mechanical industry, transport material, food and tobacco products, textile industry, paper and printing, other industries, civil building,

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Table 4 Approaches for factors and characteristics Name Size Debt Human resources

Variable SALES FINAN QUALIF DIFFER AGE DEPRD

Definition Sales (% mean sales of the sample) Financial expenditures (% sales) Qualification of the employees: personnel expenditures (% number of employees) Level of differentiation: publicity expenditures (% sales) Firm’s age (% mean age of the sample) Existence of a formal department of R&D (yes/no)

Commercial resources Organisational resources

Metric Metric Ordinal

Diversification Internationalisation Methods of generation

DIV EXP INTGENRD INTGENINN COOP EXTPURC

Number of industrial sectors (one/several) Amount of exports (% sales) Internal method through R&D activities (intervals) Internal method through other innovative activities (intervals) Co-operation (intervals) External purchase (intervals)

Ordinal Metric Ordinal Ordinal Ordinal Ordinal

Sources of information

INFINNPER INFPER INFSUPP INFUSERS INFFIRMS INFCENT INFAVAIL

Internal source of R&D and innovation personnel (intervals) Internal source of another personnel (intervals) External source of suppliers (intervals) External source of users (intervals) External source of other companies (intervals) External source of universities and R&D centres (intervals) Analysis of the available information (intervals)

Ordinal Ordinal Ordinal Ordinal Ordinal Ordinal Ordinal

Accumulative nature Objectives

INNAGE OBJPROC OBJPROD OBJNEWMARK OBJCURMARK

Innovative Objectives Objectives Objectives Objectives

Ordinal Ordinal Ordinal Ordinal Ordinal

Mechanisms for appropriating the results

APRPAT APRSEC APRCOST APRCONT APRCOMPL

Patents (intervals) Industrial secret (intervals) Cost and time for imitation (intervals) Continuous innovation (intervals) Complementary resources (intervals)

Ordinal Ordinal Ordinal Ordinal Ordinal

Types of R&D and innovations

BASRES APPLRES TECHNDEV PRODINN PROCINN RADINN INCRINN

Basic research (% R&D expenditures) Applied research (% R&D expenditures) Technological development (% R&D expenditures) Product innovations (% total innovations) Process innovations (% total innovations) Radical innovations (% total innovations) Incremental innovations (% total innovations)

Ordinal Ordinal Ordinal Metric Metric Metric Metric

age (intervals) of process (intervals) of product (intervals) of entry into new markets (intervals) of penetrating the current markets (intervals)

Scale Metric Metric Metric

Source: own elaboration.

trade and hotel business, transport and communications, and other services. This last category was considered as a reference. After carrying out the habitual pre-tests, the questionnaire was sent to 472 innovative companies. After phone support, 152 valid answers were obtained. Thus, the response rate was 32.20%, which is very acceptable both in absolute and relative terms. In absolute numbers, the size of the sample is larger than 150 firms. This involves that a power higher than 80% can

be reached at significance levels of even 0.01, provided that the size effect is not very small. Even reduced effects can be detected at higher significance levels. In relative numbers, the representativeness of the sample of 152 companies over the selected total population of 472 firms is revealed by means of the sample error, obtained for α = 0.05, by means of the formula E = ((N − n)/n(N − 1))1/2 , “N” being the population size and “n” the sample size. In this way, the maximum error is 6.68% for a level of confidence of 95%.

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Table 5 Population and sample size by industrial sector Industrial sector

Population Number of firms

Sample Percentage

Number of firms

Answer rate Percentage

Agriculture Energy Metal industry Non-metallic products Chemical industry Mechanical industry Transport material Food and tobacco products Textile industry Paper and printing Other industries Civil building Trade and hotel business Transport and communications Other services

11 15 13 20 69 163 16 37 10 9 22 7 12 6 62

2.33 3.18 2.75 4.24 14.62 34.53 3.39 7.84 2.12 1.91 4.66 1.48 2.54 1.27 13.14

3 3 6 8 22 53 5 10 4 2 8 2 4 0 22

1.97 1.97 3.95 5.26 14.47 34.87 3.29 6.58 2.63 1.32 5.26 1.32 2.63 0.00 14.47

0.27 0.20 0.46 0.40 0.32 0.33 0.31 0.27 0.40 0.22 0.36 0.29 0.33 0.00 0.35

Total

472

100.00

152

100.00

0.32

Source: own elaboration.

Furthermore, the sample is representative for industrial sectors. Table 5 shows the different industrial sectors, the firms of each sector that are included in the population and in the sample and the answer rate for each sector. It is easy to confirm that practically all the sectors are accurately represented, although, as was to be expected, they are not in a homogeneous way. Their indexes range between 20 and 46%. The best represented sectors are metal industry with 46% and non-metallic products and textile industry with 40%, and the worse represented are energy with 20% and paper and printing with 22%. Only one sector, transport and communications is represented in the population and it is not in the sample. But this sector have only six firms, and it was not possible to obtain a valid questionnaire of any of them. Therefore, a bias could exist in this respect, although this must be low because of the scarce weight of the sector in the population, with only the mentioned six firms. With the purpose of confirming the previous statements statistically, a χ2 -test was applied to all the sectors represented in the sample. The aim was to test if the sectoral division of the sample is representative of the population. The χ2 -value was 3.028, so that the significance level was 0.998. The results are evident and with α = 0.05, the null hypothesis that the sectoral distribution of the firms of the sample is not

significantly different from the sectoral distribution of the firms of the population cannot be rejected. Therefore, for all but transport and communications sector that is not present in the sample, the sectoral distribution of the sample is representative of the population. Information obtained is for 1999.

6. Exploratory analysis: data summary and reduction A data summary and reduction was carried out because of the extensive information available for characterising the innovative process. With this aim, a factor analysis (component analysis) was applied in an exploratory way. The purpose was to obtain some underlying dimensions or factors that explain the original variables with a minimum loss of information.3 The results of the rotated solution are given in Table 6. 3 The size of the sample, both in absolute and relative terms in relation to the number of variables, is appropriate for the application of the method. Additionally, the usual tests to determine the suitability of its application were carried out. The number of factors was calculated by means of the combination of the criterion of latent root (Eigen value), percentage of variance and scare test. An orthogonal factor rotation method (VARIMAX) was applied and the reduction of data was carried out by means of factor scores.

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Table 6 Innovative characteristics matrix of rotated components Variables

OBJCURMARK OBJNEWMARK TECHNDEV APRCOMPL APRCONT APRCOST INFUSERS OBJPROD INTGENINN INTGENRD INNAGE APRPAT INFINNPER APRSEC APLRES BASRES INFFIRMS INFSUPP INFCENT INFAVAIL COOP PRODINN PROCINN OBJPROC INCRINN RADINN EXTPURC INFPER Variance (%) Eigen value

Components

Communalities

1

2

3

4

5

0.769 0.701 0.600 0.536 0.470 0.468 0.463 0.450 0.424 0.231 5.240E−02 −7.994E−03 9.772E−02 0.113 3.880E−02 −0.179 0.140 0.239 4.628E−02 0.123 −9.109E−02 0.157 −4.786E−02 0.409 0.111 3.974E−02 −0.150 0.134 11.53 3.23

−0.105 −2.592E−02 −9.136E−02 0.276 0.291 0.274 0.108 0.205 0.360 0.678 0.665 0.573 0.503 0.486 0.472 0.403 6.810E−02 0.211 0.136 0.215 −0.169 3.552E−02 0.121 0.143 5.049E−02 0.302 0.179 0.247 10.39 2.91

0.118 4.458E−02 0.103 −5.922E−02 −0.183 0.165 0.370 1.770E−02 4.327E−02 8.762E−02 4.633E−02 3.416E−02 0.150 4.477E−02 6.288E−02 9.145E−02 0.759 0.628 0.577 0.526 0.517 2.165E−03 −1.057E−02 0.214 −5.283E−02 −7.376E−02 0.256 0.230 8.20 2.30

−1.546E−02 −1.534E−02 −6.392E−02 0.237 3.737E−02 5.590E−02 0.215 0.250 −2.910E−02 6.820E−02 5.703E−02 −7.429E−02 −2.354E−02 −8.014E−02 0.305 −0.189 0.205 −0.116 −9.435E−02 4.162E−02 −8.381E−02 0.915 −0.880 −0.450 5.934E−04 9.699E−02 −1.419E−02 0.163 8.03 2.25

2.990E−02 6.736E−02 2.608E−02 −5.052E−02 0.125 −0.159 −0.103 3.829E−02 0.154 −1.973E−02 0.226 −0.180 −0.147 0.128 0.189 −0.189 0.121 0.260 −6.431E−02 0.285 −0.180 2.420E−02 4.759E−02 0.330 0.858 −0.726 0.294 0.289 7.23 2.02

0.618 0.498 0.383 0.427 0.356 0.350 0.420 0.309 0.336 0.525 0.501 0.367 0.308 0.274 0.357 0.274 0.657 0.577 0.366 0.421 0.343 0.863 0.794 0.545 0.753 0.635 0.207 0.242 45.38

Source: own elaboration.

The existence of a good number of significant factor loadings, over 0.45 (minimum level according to the characteristics of the research) is confirmed. In the same way, acceptable communalities exist. This indicates an appropriate representation of the variables. Based on this information, the matrix of factors was interpreted and five factors were extracted. These can be seen in Table 7 and their interpretation is as follows. First, “internal strength close to market” (INTMARKET) represents an innovation made very close to the market. It includes an internal generation method through other innovative activities different from R&D and technological development, an external source of information based on users, market and product objectives for the innovation and appropria-

tion of the results through the most informal forms. A second factor, “internal strength close to science” (INTSCIENCE), represents an innovation that is close to science, as it gives greater importance to internal generation through R&D activities, specifically basic and applied research, an internal source of information, based on R&D and innovation personnel, an appropriation of the results through more formalised forms, especially patent rights and experience in innovation, with these activities being carried out over a long period of time. A third term, “search for external supports” (EXTSUPP), includes intense co-operation with other firms and the use of external sources of information (from other companies, suppliers, universities and

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Table 7 Final variables extracted from factor analysis of innovative characteristics Variable

Name

Description (original variables)

INTMARKET

Internal strength close to market

Market and product objectives Technological development Appropriation of the results through complementary resources, continuous innovation and cost and time for imitation Technology information based on users Internal generation method through other innovative activities different from R&D

INTSCIENCE

Internal strength close to science

Internal generation method through R&D activities Accumulative nature Appropriation of the results through patents and industrial secret Technology Informaci´on based on R&D and innovation personnel Basic and applied research

EXTSUPP

Search for external supports

Technology information based on other companies, suppliers, universities and R&D centres and available information Co-operation with other firms

PRODUCTS

Focused on products

Product innovations Low process innovations Low process objectives

IMPROVE

Continuous improvement

Incremental innovations Low radical innovations

Source: own elaboration.

R&D centres and the analysis of the available information). Fourth, “focused on products” (PRODUCTS), includes (positively) the carrying out of product innovations and (negatively) the existence of process innovations and process objectives. The final factor, “continuous improvement” (IMPROVE), represents incremental innovations, the continuous realisation of innovations that make it possible to improve the competitive position of the firm because this variable loads very high and positively; on the other hand, the carrying out of radical innovations also loads very high but negatively.

7. Explanatory analysis: the impact of resources and internal factors on the innovative process The aim of the study is to identify and quantify the impact of the resources and internal factors of the firm on its innovative process. Therefore, it is an explanatory type analysis and multiple regression is an appropriate statistical method. This technique allows us to explain a dependent variable by means of the values

of several independent variables. The relative importance of each explanatory variable for the dependent variable can be determined (amount and direction) together with the relationships existing among the independent variables. The correlation coefficients were examined prior to the application of the regression analyses. The independent variables should have a high correlation with the dependent variable in order to obtain a better explanation of the latter, but a low correlation to avoid multi-collinearity problems that reduce the explanatory power of new independent variables. Table 8 summarises the descriptive statistics for continuous variables and the correlations among all variables relating to internal factors, as well as among these variables and the five extracted factors of the factor analysis that summarise the innovative characteristics. The matrix of independent variables suggests little collinearity. All correlations among independent variables are low. The two highest coefficients are between AGE and SALES (0.263) and between DEPRD and AGE (0.246). Furthermore, the tolerance index and the variance inflation factors (VIF) were examined.

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Table 8 Descriptive statistics and correlations

SALES FINAN QUALIF DIFFER AGE DEPRD DIV EXP INTMARKET INTSCIENCE EXTSUPP PRODUCTS IMPROVE

MEAN

S.D.

1.00 2.74 4757.37 2.02 1.00

4.45 2.76 2375.51 2.07 0.71

32.32 0.00 0.00 0.00 0.00 0.00

30.59 1.00 1.00 1.00 1.00 1.00

SALES

FINAN

QUALIF

DIFFER

AGE

DEPRD

DIV

EXP

−0.093 0.027 −0.096 0.263∗∗ 0.090 0.014 0.016 −0.035 0.242∗∗ 0.065 −0.127 0.045

−0.035 0.121 0.067 0.110 −0.059 −0.164∗ −0.036 0.067 0.135 0.004 0.153

0.132 0.041 −0.068 0.055 0.186∗ 0.058 0.090 −0.129 0.148 0.086

0.031 0.028 −0.028 −0.154 0.043 0.059 −0.049 0.244∗∗ −0.084

0.246∗∗ −0.122 0.108 0.085 0.321∗∗ 0.078 −0.081 0.097

−0.033 0.184∗ −0.026 0.443∗∗ 0.272∗∗ 0.136 0.091

−0.175∗ −0.005 −0.021 −0.026 0.056 0.031

0.296∗∗ 0.242∗∗ −0.009 −0.053 0.004

Source: own elaboration. ∗ P < 0.05. ∗∗ P < 0.01.

No significant multi-collinearity problems were found among the independent variables. On the contrary, there were significant correlations among dependent and independent variables. Hence, outstanding results can be obtained from multiple regression analyses. Given that five factors relating to the characteristics of the innovative process were deduced from factor analysis, five multiple regression analyses were carried out, one regression for each factor because they constitute the dependent variables of the regression models. The aim was to verify the hypotheses, provided in Section 4, concerning the influence of the internal factors on the innovative process. The results of the five regression models4 are given in Table 9. As can be seen, the regression models applied according to the different innovative characteristics explain variable percentages of their total variance. The characteristic INTSCIENCE is the best explained. Its determination coefficient is 30.5%. The other characteristics are explained in percentages close to 10%. All the tests of significance of the model (F-values) are positive, with a significance level of 0.01. This 4 The size of the sample, both in absolute and relative terms in relation to the number of variables, is sufficiently large. The regression models were specified through a sequential search method (step-wise estimation), although very similar results were obtained with the application of other sequential and confirmatory methods. The residuals were analysed in order to verify the assumptions of regression analysis for the overall relationship.

confirms that the firm’s internal resources and factors affect the configuration of its innovative process. The general proposition can be accepted (P): “Internal resources and factors affect the configuration of the firm’s innovative process”. Certain relationships among internal factors and innovative characteristics that correspond with those proposed by the hypotheses are proved. Specifically, the first innovative characteristic, INTMARKET represents an “internal strength close to market”. It includes an internal generation method through innovative activities other than R&D and technological development, an external source of information based on users, market and product objectives for the innovation and an appropriation of the results through the most informal forms (complementary resources, continuous innovation and cost and time for imitation). The variable EXP, indicative of the level of internationalisation of the firm, is significant at 0.01. Therefore, the positive influence of a high level of internationalisation on the existence of an objective for the innovation of entry into new markets seems to be confirmed. The firms go out into external markets with the purpose of expanding their current markets and they also guide all their activities in this same direction, especially technological activity, in view of its impact on competitiveness. Therefore, a part of the seventh hypothesis is confirmed (H7 ): “A higher level of internationalisation positively

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Table 9 Multiple regressions results Innovative characteristics

Variables

Coefficients

T-value

INTMARKET

Constant EXP SECTOR6 R2 Adjusted R2 F-value

−0.399 7.994E−03 0.402 0.122 0.110 10.351∗∗∗

−3.406∗∗∗ 3.068∗∗∗ 2.414∗∗

INTSCIENCE

Constant DEPRD AGE SALES EXP SECTOR1 R2 Adjusted R2 F-value

−1.178 0.877 0.256 3.636E−02 5.353E−03 0.872 0.305 0.281 12.805∗∗∗

−6.284∗∗∗ 4.966∗∗∗ 2.465∗∗ 2.263∗∗ 2.321∗∗ 1.753∗

EXTSUPP

Constant DEPRD R2 Adjusted R2 F-value

−0.525 0.665 0.074 0.068 12.003∗∗∗

−3.078∗∗∗ 3.464∗∗∗

PRODUCTS

Constant DIFFER SECTOR2 DEPRD SECTOR3 R2 Adjusted R2 F-value

−0.450 9.824E−02 −1.120 0.383 −0.729 0.117 0.093 4.887∗∗∗

−2.452∗∗ 2.578∗∗ −1.999∗∗ 1.999∗∗ −1.804∗

IMPROVE

Constant SECTOR4 FINAN SECTOR3 R2 Adjusted R2 F-value

−0.232 0.870 5.647E−02 0.797 0.083 0.064 4.447∗∗∗

−2.040∗∗ 2.471∗∗ 1.980∗∗ 1.977∗∗

Source: own elaboration. ∗ P < 0.10. ∗∗ P < 0.05. ∗∗∗ P < 0.01.

affects entry into new markets as an objective of the activity.” The second innovative characteristic, INTSCIENCE represents an “internal strength close to science”. It gives greater importance to an internal generation method through R&D activities, specifically basic and applied research, carried out over a long period of time, an internal source of information based on R&D

and innovation personnel, and an appropriation of the results through more formalised forms, especially patent rights and, alternatively, industrial secrecy. The variables DEPRD and AGE, both representative of the organisational resources of the firm, are significant, the first at 0.01 and the second at 0.05. This result allows several relationships posed by our hypotheses to be proved. There seems to be a positive relationship between the possession of greater organisational resources and strong support for internal methods of technology generation, specifically based on R&D activities. These resources also seem to have a positive influence on a more intense use of internal sources of information, specifically on the use of information coming from the innovation personnel, and on the existence of a greater accumulative nature in the technological process, allowing a more continuous development of innovative activities over time. Furthermore, organisational resources seem to give rise to more intense basic and applied research in relation to technological development. Investment in these activities indeed seems to be favoured by the greater accumulated experience and knowledge that the possession of superior organisational resources entails. Therefore, a great part of the fifth working hypothesis is accepted (H5 ): “The possession of superior organisational resources implies a greater accumulative nature of the innovative activity, a greater use of an internal method of technology generation, a greater use of internal sources of technological learning and a greater investment in research than in technological development.” Another significant variable at 0.05 is SALES, indicative of the firm’s size. Therefore, the positive influence of size on the accumulative nature of the innovative activity seems to be corroborated. In fact, it seems that greater size provides a greater possibility to use resources for innovation continuously over time, undoubtedly because, in general, time is needed to reach a greater size. The result obtained supports the first hypothesis (H1 ): “Greater size increases the accumulative nature of the innovative activity.” A last significant variable at 0.05 is EXP, representative of the firm’s internationalisation strategy. This result confirms a positive association between the level of internationalisation of the firm and the accumulative nature of the innovative process. Because of the demands of external markets, internationalisation involves a stronger commitment to innovation, which is

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manifested through a greater accumulative nature of the activity. Thus, the other part of the seventh hypothesis (H7 ) is confirmed: “A higher level of internationalisation positively affects the accumulative nature of the innovative process.” A third representative factor of innovative characteristics is EXTSUPP, which refers to the great importance of the “search for external supports” in the firm’s innovative activity. It includes intense co-operation with other firms and the use of external sources of information (from other companies, suppliers, universities and R&D centres and the analysis of the available information). The only variable that seems to encourage the carrying out of an innovative process based on external supports is DEPRD. It is significant at 0.01 and it represents the firm’s organisational resources. The influence of organisational resources on the intense use of external sources of scientific and technological information seems to be corroborated. This result completes the previously commented one for this type of resources and jointly they seem to confirm that organisational resources indeed allow the company to be in a better position to take advantage of internal and external sources of information. The rest of the fifth hypothesis (H5 ) is thus accepted: “The possession of greater organisational resources implies a greater use of external sources of technological learning.” The fourth innovative characteristic, PRODUCTS, represents an innovative process “focused on products”. It includes very intense carrying out of product innovations, low investment in process innovations and scarce presence of process objectives. Two internal variables were significant in the regression model for this innovative characteristic, both with a level of significance of 0.05: DIFFER, representative of commercial resources, and DEPRD, indicative of organisational resources. In relation to our hypotheses, the significance of the first variable is interesting. It seems to indicate that commercial resources have an impact on the intense generation of product innovations. The firm carries out this type of innovations and attempts to apply marketing variables in order to differentiate itself from other companies and achieve a greater competitive advantage. This result supports a part of the fourth hypothesis (H4 ): “The possession of many commercial resources is

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strongly related to an intense development of product innovations.” The fifth and last representative factor of innovative characteristics is IMPROVE, which means the carrying out of a process of “continuous improvement” in the firm. It represents an intense generation of incremental innovations and, on the contrary, a very low generation of radical innovations. One variable affects the carrying out of an innovative process based on continuous improvement. This is FINAN, significant at 0.05 and representative of the firm’s level of debt. This result seems to indicate that high financial debt in the company has an impact in the sense that more incremental innovations are generated than radical ones. The lack of financial resources compels firms to reduce their risk through the generation of incremental innovations, because they also have a previously developed physical component that permits debt financing. Therefore, the second hypothesis (H2 ) is confirmed: “Debt financing determines the generation by the firm of a high proportion of incremental innovations.” On the contrary, it has not been possible to confirm some of the hypotheses, although it must be mentioned that no evidence of relationships opposed to the direction of our hypotheses has been obtained. First, the influence of qualified human capital on a greater accumulative nature of the innovative activity has not been verified. The results of the regression model for INTSCIENCE indicates that the variable QUALIF is not significant. A positive relationship exists but it is not strong enough to confirm the third hypothesis. Thus, a significant relationship between the possession of superior commercial resources and the use of complementary resources as a way to appropriate the results and users as a source of technological information has not been shown. The variable DIFFER is not significant in the regression model for INTMARKET. The rest of the fourth hypothesis cannot be confirmed. Finally, no evidence concerning the influence of diversification on greater investment in basic research has been found. The results of the regression model for INTSCIENCE denote no significance of the variable DIV. The sixth hypothesis, thus, cannot be accepted. The coefficients of 14 control variables used to capture the possible inter-industry differences in the firm’s innovative behaviour are significant on certain occasions (see Table 9). Although neither the

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Table 10 Confirmed hypotheses Hypothesis

Independent variable

Dependent variable

Relation

Type of regression (dependent variable)

H1 H2 H4 H5

Size Debt Commercial resources Organisational resources

Accumulative nature Incremental innovations Product innovations Accumulative nature Internal method of generation Internal and external sources of information Basic and applied research

+ + + + + + +

INTSCIENCE IMPROVE PRODUCTS INTSCIENCE INTSCIENCE INTSCIENCE/EXTSUPP INTSCIENCE

H7

Internationalisation

Accumulative nature Objectives of entry into new markets

+ +

INTSCIENCE INTMARKET

Source: own elaboration.

intensity nor the direction of the influence of internal factors on innovative activity has changed, a certain impact of sectoral factors on the innovative process should be recognised. The industrial sector does not exert directly this influence, rather it is revealed indirectly because of different sectoral variables. Such as industrial conditions of technological opportunity (Scherer, 1965b, 1967), of economic opportunity (Schmookler, 1962, 1966), of market concentration (Horowitz, 1962; Levin et al., 1985) and of sectoral possibilities of appropriation of the results (Levin et al., 1985). It seems reasonable that all these variables also influence the firm’s innovative process. However, the analysis of this impact exceed the aim of this paper, dedicated to the analysis of the influence of firm’s internal factors on its innovative activity.5 Table 10 summarises the confirmed hypotheses together with the innovative characteristic that has been used as a dependent variable. These relationships allow the following to be confirmed: • The companies that opt for an internal method of technology generation have greater organisational resources (H5 ). • The internal sources of scientific and technological information are used by firms with greater organisational resources. These resources also induce 5 In another unpublished study, some relationships have been verified. It is worth pointing out the relation of the sectoral possibilities of appropriation of the results with the use of an internal method for generating technology; of the economic opportunity with the investment in technological development; or, of the market concentration with the generation of process innovations and of incremental innovations.

•

• • •

an important use of external sources of information (H5 ). The accumulative nature of the innovative activity, determined by the innovative age of the company, is increased by the firm’s size, by the possession of greater organisational resources and by the firm’s level of internationalisation (H1 , H5 and H7 ). The objectives for the innovation related to the entry into new markets is more frequent in internationalised firms (H7 ). Companies that invest a greater proportion of their R&D activities in basic and applied research possess greater organisational resources (H5 ). The generation of a greater proportion of product innovations is characteristic of the companies with high commercial resources, and the intense development of incremental innovations is carried out by debt financing firms (H2 and H4 ).

8. Conclusions This paper analyses the internal resources and factors that can determine the firms’ innovative process. The aim is not to explain the final innovative result of the companies, but how they manage their innovative activity. The theoretical framework combines the evolutionary theory and the resource-based view of the firm. The paper includes an original proposal of a model to analyse firms’ innovative activity. This model proposes a particular way to characterise firms’ innovative process through six qualitative innovative features (methods of generation, sources of information, accumulative nature, general objectives,

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mechanisms for appropriating the results and types of R&D and innovations). It also includes seven internal factors of the firm that are potential determinant of the innovative process (size, debt, human resources, commercial resources, organisational resources, diversification and internationalisation). The model was applied to a sample of 152 Spanish innovative companies. In spite of the typical diversity of the innovative process, evidence was found concerning the extent to which firms’ innovative activities are explained by their internal resources and factors. The general proposition seems to be reasonable and the internal factors affect the configuration of the firm’s innovative process. Nevertheless, a different impact is obtained according to the specific innovative feature taken into account. Therefore, a part of the innovative behaviour of the Spanish firm, defined in terms of methods of technology generation, sources of information, accumulative nature of the process, general objectives, mechanisms for appropriating the results and types of R&D and innovations, can be explained through a firm’s internal factors. Specifically, they are direct determinants of the use of an internal generation method, of support from internal and external sources of information, of the greater accumulative nature of the activity, of the posing of objectives of entry into new markets, of investment in basic and applied research and of the generation of product innovations and incremental innovations. The paper has some limitations. First, the approach used to measure some of the factors used in the analysis may be less precise than desired. This could reduce the testing capacity for some of our hypotheses. However, the qualitative and intangible nature of many factors should be taken into account. This makes the limitation difficult to avoid. Secondly, it was not possible to carry out a dynamic analysis of the innovative process because of the lack of panel data on this activity. The obtaining and application of this type of data constitute an interesting future topic of research. Finally, the influence of other factors external to the firm (sectoral or public incentives) on innovative activity should be analysed. In fact, our study presents some evidence in relation to sectoral factors, which can be approached through the study of technological variables (technological opportunity and sectoral possibilities of appropriation of the results) and economic

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variables (economic opportunity and market concentration). This could also be an interesting future topic of research. Despite these limitations, we believe that the empirical findings are important, in view of the diversity and complexity of the data used, and particularly that their economic interpretation is acceptable and contributes to the confirmation of the hypotheses and the utility of the model. It is possible to affirm that the study implies an advance in the analysis of firms’ innovative processes, given the small number of studies in the empirical literature which explain, not the final innovative result of the firms, but the characteristic features of this process. For this reason, the study is of special interest.

Acknowledgements The authors are grateful for the finance received from the State Research Office of the Ministry of Science and Technology of Spain, in the research project SEC2001-1756. Likewise, the authors benefited from the comments of Isabel Suárez and Javier González-Benito and the anonymous referees of the journal. The authors alone are responsible for any omissions or other errors. References Acs, Z., Audretsch, D., 1988. Innovation in large and small firms: an empirical analysis. American Economic Review 78, 678– 690. Adams, W.J., 1970. Firm size and research activity: France and the United States. Quarterly Journal of Economics 84, 386–409. Arundel, A., Kabla, I., 1998. What percentage of innovations are patented? Empirical estimates for European firms. Research Policy 27, 127–141. Barney, J.B., 1991. Firm resources and sustained competitive advantage. Journal of Management 17, 99–120. Baysinger, B.D., Hoskisson, R.E., 1989. Diversification strategy and R&D intensity in large multiproduct firms. Academy of Management Journal 32, 310–332. Braga, H., Willmore, L., 1991. Technological imports and technological effort: an analysis of their determinants in Brazilian firms. Journal of Industrial Economics 39, 421–432. Branch, B., 1974. Research and development activity and profitability: a distributed lag analysis. Journal of Political Economy 82, 999–1011. Buesa, M., Molero, J., 1998a. La regularidad innovadora en empresas españolas. Revista de Econom´ıa Aplicada 6 (17), 111–134.

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