determinants of r&d investment: strategic and

― 13 ―

1. Introduction

The creation and growth of new fi rms is recog-nised as imperative, not least because they are a manifestation of entrepreneurship and a source of economic growth. New technology-based fi rms (NTBFs), in particular, play a signifi cant role in productivity growth and job creation in the na-tional economy, and are associated with a sizable share of new technological innovations. Several studies, using either panel or cross-sectional data across a broad range of fi rm sizes, attest to the idea

that smaller fi rms account for a disproportionately large share of innovations relative to their size, and that R&D productivity (i.e., innovations per unit of R&D) tends to decline with increasing fi rm size.

NTBFs have distinct characteristics that distin-guish them from larger, established fi rms and which shape the challenges that their management face. For example, the newness and small size of these fi rms, the uncertainty of their endeavour, as well as the dynamics of their environment are all chal-lenges for managers in the pursuit of business op-portunities. In order to develop an understanding of

† The author wishes to thank Professor Ray Oakey and participants of the 21st International High-Technology Small Firms conference, held at the University of Manchester, England, on 30-31 May 2013, for their comments on a version of this paper presented at the conference.

Determinants Of R&D Investment:

Strategic And Entrepreneurial Characteristics

In Japanese New Technology-Based Firms†

Michael J. LynskeyFaculty of Global Media Studies, Komazawa University1-23-1 Komazawa Setagaya-ku Tokyo 154-8525 JAPAN

[email protected]

Abstract

The aim of this paper is to examine the determinants of R&D investment in Japanese new technology-

based fi rms (NTBFs) by considering several strategic and entrepreneurial characteristics thought

to be causative factors. It uses original data from a questionnaire survey conducted in Japan. We fi nd

that, at the strategic level, fi rms’ technological capability, the availability of internal funds, and several

factors associated with universities have a positive effect on R&D investment. At the entrepreneurial

level, a CEO’s human capital and prior business experience in an R&D role are positively related to

R&D investment. One aspect of these results is that universities play a quantifi able role in fi rms’ R&D

investments; the former result is a direct effect of higher education, while the latter implies at least a

tertiary education in order to have such prior R&D experience. The results for these two variables, coupled

with the fi nding that joint R&D projects with universities is positively related to R&D investment, lead

us to conclude that universities impact on R&D investments in NTBFs, both directly and indirectly, with

implications for small fi rms’ innovative activities.

Key words: Strategic Characteristics; Japan; Entrepreneurial Characteristics; New Technology-Based

Firms; R&D Investment, Universities.

JEL Classifi cation: L20, M21, O32

Journal of Global Media Studies Vol. 13

― 14 ―

the challenges associated with the evolution of such fi rms, researchers have developed models that de-pict their development. Though these models give insights on various challenges, they typically fail to differentiate between those tasks that are operation-al in nature and those that are of more strategic im-portance. Moreover, they generally focus on ‘hard’, tangible factors and neglect the personal character-istics of the entrepreneur, which play a particularly important role in NTBF success.

In Japan, considerable emphasis has been placed on the creation of NTBFs in the anticipation that they will contribute to the growth of the economy (Imai and Kawagoe, 2000). This has been refl ected in the introduction of various governmental reforms (see Boltho and Corbett, 2000; Eshima, 2003) and legislation to generate institutional change condu-cive to entrepreneurship and the growth of such fi rms (Lynskey, 2006).

Despite this expectation that NTBFs will become more important to Japan economically, surprisingly few empirical studies (e.g. Harada, 2004; Honjo, 2004) have considered the innovative activities of such fi rms, or the effectiveness of policies to sup-port such activities.

The purpose of this paper is to help address this gap by considering the determinants of R&D investment in Japanese NTBFs. In order to do so, we apply an integrative perspective and examine several strategic and entrepreneurial characteris-tics. Generally, studies have not undertaken such a comprehensive examination with respect to Japan; and even in the West, few studies have explicitly examined both factors together. This is surprising, because investment in R&D is clearly an important input measure of R&D capability and innovation, and a driver of future competitive advantage. Also, small- and medium-sized enterprises (SMEs) make up almost all businesses in Japan. Until recently, however, SMEs were regarded as ‘weak enterprises’ and afforded little credence, even among Japanese policymakers, or they were simply ignored.

2. Extant Research

Prior research on determinants of R&D invest-

ment has mainly considered strategic factors, such as a fi rm’s industry, corporate strategy and institu-tional shareholders. These studies, however, have examined R&D investment only in large, multina-tional or diversifi ed fi rms, and they have not includ-ed entrepreneurial characteristics as determinants.

Other studies have specifi cally considered R&D investment in small technology-based fi rms, but again have taken only strategic factors into account, such as the impact of regulatory measures, produc-tivity, and factors such as size, industrial sector, ownership and location (e.g., Shefer and Frenkel, 2005).

Separate from this stream of research, fewer studies have examined R&D investment in fi rms through another lens: from the perspective of en-trepreneurial characteristics. The relative paucity of such research is surprising, since decisions on the allocation of R&D investment reside with the chief executive offi cer (CEO) and senior managers of fi rms (Green, 1995). Moreover, since R&D invest-ment represents a long-term allocation of resources with which there is associated risk and uncertainty, the CEO invariably monitors closely such invest-ment and adjusts it according to his preferences and the strategic direction of the fi rm (Zahra, 1999b). CEOs and senior managers inevitably play a role in strategic decisions on the deployment of organi-sational resources and the conversion of these re-sources into valuable products to confer managerial rents and competitive advantage (Lado et al., 1992). Penrose (1959: 5) emphasised the importance of “the productive services available to a fi rm from its own resources, particularly the productive ser-vices available from management with experience within the fi rm”. Thus, entrepreneurial characteris-tics, such as prior experience, are likely to impact on fi rm performance (Castanias and Helfat, 2001).

Those studies that have considered entrepre-neurial characteristics as determinants of R&D in-vestment have been confi ned mainly to large fi rms. Among other things, these have revealed that CEO characteristics vary according to the industry, and that those fi rms in high-technology sectors, where R&D investment is greater, have different CEO pro-fi les than fi rms in low-technology sectors. A study

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Determinants Of R&D Investment: Strategic And Entrepreneurial Characteristics In Japanese New Technology-Based Firms(Michael J. Lynskey)

by Daellenbach et al. (1999) examined how entre-preneurial characteristics varied with R&D invest-ment in 52 fi rms within two industries. While more generalisable than earlier single-industry studies, the study of only two industries limits application to a broader context.

Studies specifi cally examining the entrepreneuri-al characteristics of small fi rms have been far fewer. In one, Deeds et al. (2000) considered the relation-ship between the number of new products and R&D management capabilities - captured by educational background, such as doctorate qualifi cations - by using data from biomedical start-up fi rms. Howev-er, few, if any, studies have examined the strategic and entrepreneurial determinants of R&D invest-ment in Japanese NTBFs.

3. Theoretical Perspective

Our theoretical perspective is that a fi rm’s invest-ment in R&D is determined by factors at the stra-tegic level and the entrepreneurial level. As men-tioned above, much of the literature considers only attributes associated with the strategy of the fi rm; while other literature adopts the contrary approach, and considers human capital characteristics of the founder or CEO, while disregarding strategic char-acteristics of the fi rm in which the CEO operates (and, indeed, which s/he may have founded). We contend that neither approach is satisfactory, since it provides only a partial picture. The optimal meth-odology is to consider elements from both perspec-tives. In doing so, we were guided by the literature from both strategic-level and entrepreneurial-level perspectives as to which variables to consider.

The literature associated with fi rm strategy con-siders several factors. These include the availability of internal funds (e.g., Lach, 2000); the effective-ness of venture capital funding (e.g., Kortum and Lerner, 1998, 2000); geographic location (e.g., Audretsch and Feldman, 1996), and the economic benefi ts of university research on industrial R&D, particularly for new fi rms (e.g., Henderson et al., 1995; Mansfi eld and Lee, 1996).

The literature on entrepreneurial-level perspec-tives suggests that a fi rm’s strategies and effective-

ness are associated with the values and cognitive bi-ases of senior management, and examines features such as the CEO’s age, education and prior experi-ence.

We refer to both of these streams of study below, when we outline hypotheses about the association between R&D investment by fi rms and various stra-tegic and entrepreneurial characteristics.

4. Econometric Model

Perhaps the greatest obstacle to understanding the role of innovation in economic processes has been the lack of meaningful measures of innovation in-puts and outputs. One measure that is used as an indicator of innovative activity is the intensity of a fi rm’s expenditure on R&D. Accordingly, then, we consider the following R&D equation:

iiii uYXconstr

The dependent variable ri denotes the natural loga-rithm of company-fi nanced annual R&D expendi-ture in fi rm i. Since many of our data on R&D take the value zero, we employ a Tobit regression model, instead of using Ordinary Least Square analysis.1 In running regressions, we transform the depend-ent variable RD into (RD+1)*10 by using the loga-rithmic linear transformation. The Tobit censoring boundary is set to correspond to a zero observation (Acs et al., 1994a).

On the right-hand side of the equation, there are two categories of variables that we propose deter-mine the level of R&D investment. The fi rst catego-ry is represented as a vector of the strategic charac-teristics, X; and the second category is represented as a vector of the entrepreneurial characteristics, Y. These variables and the hypotheses related to them are discussed below. The complete set of variables is shown in Table 1.

1 Tobit regression assumes the data are truncated, or censored, above or below certain values, and is used to handle the truncation at zero. See Greene (1997: 959-963).


― 16 ―

5. Explanatory Variables and Hypotheses

5.1 Strategic Variables

Technological Capability

First, we propose that a fi rm’s level of ‘techno-logical capability’ is likely to affect the extent of R&D investment. We defi ne technological capabili-ty as the potential for fi rms “to undertake a set range of productive tasks aimed at improving their ability to operate specifi c functions and compete in specifi c markets and industries” (Lynskey, 1999). Techno-logical capability provides the basis for in-house innovation and competitive advantage (Cohen and Levinthal, 1990). Specifi cally, it is seen as the re-source that enables a fi rm to generate innovations in products, process and engineering projects. As such, technological capability is regarded as a stra-tegic resource enabling fi rms to achieve competitive advantage within their industry. Those fi rms with superior technological capability can secure greater effi ciency gains and deliver innovation in response to the changing market environment.

Several studies (e.g., Afuah, 2002; Schoenecker and Swanson, 2002) employ R&D expenditure as the core measurement indicator of technological capability; this is not surprising, since a fi rm’s tech-nological capability correlates signifi cantly with the development, absorption and application of techno-logical knowledge. Moreover, technological capa-bility has been shown to be a determinant of perfor-mance in technology-based venture fi rms (e.g., Lee et al., 2001).

Here we denote technological capability by the independent variable TC, defi ned as the number of R&D personnel to total employees. We expect that R&D investment in a fi rm will increase if techno-logical capability increases; hence, the coeffi cient of TC is predicted to be positive in our regressions. 2

H1: R&D investment is positively related to 2 Naturally, there may be other elements of firms that

might make up their technological capability, e.g. physical assets such as laboratories and computer resources.

the technological capability of a fi rm.

Internal Funds

Theoretical reasons for the existence of capital market imperfections in the fi nancing of R&D are well known. The nature of R&D is typically charac-terised by substantial sunk costs and is accompanied by a great deal of uncertainty, such that it is diffi cult to evaluate the outcome of R&D, and predict the in-vestment value precisely, which prevents fi rms from borrowing to fi nance R&D projects. Thus, equity fi -nance or debt-based fi nance often becomes diffi cult to attract, especially for start-up fi rms that have no reputation in the market (Hall, 2002). Additionally, the traditional low levels and late-stage provision of venture capital in Japan, coupled with the reluc-tance of venture capital fi rms to invest in start-up fi rms, compounds the diffi culties faced by Japanese NTBFs (Lynskey, 2004, 2006). Moreover, the fi rm may seek secrecy for strategic reasons and prefer internal fi nancing of R&D. These factors tend to result in R&D investment being fi nanced through internal funds and bank loans, at least in the early stages.

Here, the independent variable SALES is defi ned as the natural logarithm of fi rms’ sales in the previ-ous year. This is a plausible proxy for the availabil-ity of internal funds, a fraction of which is allocated to R&D in the successive year.3 Hall (1992) notes that fi rms fi nance most R&D from their internal funds; and other studies (e.g. Himmelberg and Pe-tersen, 1994; Mulkay et al., 2001) provide further empirical evidence of a signifi cant positive relation-ship between R&D and available internal funding. Moreover, a fi rm’s probability of undertaking R&D activities and its R&D expenditure increase with market power (Gonzáles and Pazó, 2004). Hence, we predict that there is a positive relationship be-tween R&D investment and sales.

H2: R&D investment is positively related to the availability of internal funds.

3 The variable SALES may also be interpreted as a proxy for demand. See, for example, Cohen and Klepper (1996).

― 17 ―


Venture Capital

The amount of venture capital funding in Japan is one of the lowest among developed countries. Although a series of legislations and modifi cations to the investment system have been enacted in re-cent years to encourage risk capital investments, the amount of venture capital funding in Japan remains small compared to Europe and the USA. The main impediment to venture capital funding in Japan lies in the risk-averse nature of its investors and the practice of portfolio investment rather than true venture capital investment (Schaede, 2008).

Although venture capital fi rms in Japan exhibit several differences in their funding strategy when compared to similar fi rms elsewhere (see Kuem-merle, 2001; Mayer et al., 2003), we test if venture capital funds stimulate R&D investment in our sam-ple of fi rms, as one might suppose from studies of venture capital fi rms in the West (e.g. Kortum and Lerner, 2000). One might reasonably expect ven-ture capital funding to stimulate R&D investment in Japanese NTBFs, if they can attract such fund-ing. We introduce the variable VC, which we defi ne as the share of venture capital fi nancing to the total initial funds available to a fi rm.

H3: R&D investment is positively related to venture capital funding.

Business Planning

The literature is divided as to whether business planning is an important precursor to action in new fi rms, or if it impedes the efforts of the founders of such fi rms. Rue and Ibrahim (1998) investigated the relationship between planning and business per-formance, and in their review of the literature they stated that, “the literature strongly supports the ar-gument that, in small business, planning is a key is-sue”. Their own results, however, were statistically inconclusive, except for the fi nding that fi rms with no written plans exhibited slower growth rates than those with sophisticated planning. Later research (e.g., Perry, 2001; Delmar and Shane, 2003, 2004) supported the idea that planning produces desirable

outcomes, and that it enhances both product and venture fi rm development.

Other literature, however, contends that it is likely that NTBFs do not - and perhaps cannot - al-locate suffi cient resources to business planning. Ac-cording to these studies, the uncertainty and pace of entrepreneurial situations undermine the value of business planning, so founders should move di-rectly to action (Carter et al., 1996). Research by Bhidé (2000) on start-ups fi rms indicates that they do not formulate elaborate business plans because they must make decisions quickly in response to changing circumstances, thereby making redundant previously formulated plans. Indeed, Allinson et al. (2000) contend that entrepreneurs should rely more on their intuition, rather than engage in planning and risk using information that is likely to be in-accurate or out-of-date. Moreover, data from Japan claims that over 40 percent of Japanese SMEs make business plans purely for ‘negative’ reasons, such as their inability to attract investment without such a plan, or because outsiders have advised them to do so. This is consistent with fi ndings elsewhere. In such cases, planning is merely symbolic: it is seen as desirable because it lends legitimacy to a venture; or, by emulating the practices of successful fi rms, ventures hope to become imbued with the same quality.

Despite these ambiguous results, we concur with several researchers (e.g., Szakonyi, 1990; Zantout and Tsetsekos, 1994) that it is incumbent on fi rms to articulate a business plan, and that this clarifi es the allocation of investment in R&D. We introduce a bi-nary dummy variable, B_PLAN, which is assigned a value of one if a fi rm makes a business plan, and zero otherwise.

H4: R&D investment is positively related to making a business plan.

R&D with Universities

Universities are recognised as a repository of public knowledge, and knowledge emanating from them has become important, owing to the develop-ment of new and improved products depending on


― 18 ―

academic research (David, 1994; Hall et al., 2000). University research often stimulates and enhances the power of R&D done in industry, rather than provides a substitute for it. Consequently, academic and business research should be seen as overlapping and interacting, with the former augmenting the ca-pacity of the latter to solve an increasing range of complex questions.

Empirical studies show that strategic-level ef-fects induced by university knowledge occur on two levels (Stephan, 1996). First, internalising scientifi c knowledge leads to the expansion of fi rms techno-logical capabilities (mentioned previously) for de-veloping new or improved products (Jaffe, 1989; Cockburn and Henderson, 1997), which becomes manifest in an improvement of technological know-how and skills. Secondly, knowledge generated in universities improves fi rms’ research effi ciency. Such knowledge accelerates the lead-time of inno-vations and increases the rates of return of R&D.

After the pioneering work of Jaffe (1989), econo-mists have investigated who best utilises university knowledge to achieve industrial innovations. Ac-cording to their empirical results, university knowl-edge is thought to benefi t NTBFs in particular, by enabling them to compensate for their competitive disadvantage due to their size (Acs et al., 1994a; Cohen and Klepper, 1996a, b). Small high-technol-ogy fi rms that engage in university-based research are likely to exhibit a higher rate of return to R&D and have an advantage compared with larger fi rms in exploiting university research (Lee et al., 2001). Mansfi eld (1991) also asserts that smaller fi rms have an advantage in commercialising the results of university research. Acs et al. (1994a) revealed that external knowledge contributes more to the innova-tion process in small fi rms than in large fi rms, which tend to rely more on their in-house R&D activities. Small fi rms have more to learn from external sourc-es of knowledge, and have greater potential for growth stimulated by collaborative R&D linkages with universities than do their larger counterparts (Sakakibara, 1997). Thus, university knowledge is part of the total stock of externally available and rel-evant technological knowledge available to start-up innovative fi rms (Mansfi eld, 1995), especially those

that have not accumulated enough R&D assets through their own in-house efforts, as is the case with start-up fi rms (Santoro and Chakrabatri, 2002).

In addition to this literature referring to research from Europe and the USA, similar results are re-ported from empirical studies conducted in Japan. In an examination of Japanese manufacturing fi rms undertaking R&D, Motohashi (2004) reports that small fi rms have increasingly become involved with university linkages, and newer fi rms are likely to engage in joint research with university-based sci-entists. Moreover, based on the exploitation of uni-versity knowledge through collaborative research, newer fi rms were found to achieve more technical and commercial success in innovations, measured as patent productivity and value-added growth, respectively. Elsewhere, it was reported that new and small fi rms are likely to achieve higher sales growth on the basis of university-industry collabo-ration (JSBRI, 2003). Furthermore, analysis of lon-gitudinal data suggests that small fi rms are likely to exploit university knowledge in an attempt to op-timise the use of relatively few internal resources to enhance their core competence (Nakayama et al., 2003).

Here, we examine the effect of collaborative R&D projects with universities on R&D investment made by NTBFs. The independent variable JRDU is defi ned as the number of joint R&D projects that a fi rm undertakes with universities. We expect that a fi rm’s R&D investment is positively related to JRDU. This follows from the idea that a NTBF needs to conduct additional R&D in order to absorb and suffi ciently utilise scientifi c knowledge that is transferred from universities, in accordance with the concept of absorptive capacity (Cohen and Lev-inthal, 1989, 1990).

H5: R&D investment is positively related to the number of R&D projects with universities.

Location

March and Simon (1958) suggested that ‘borrow-ing’ is the catalyst in most innovation; as such, in-novation is dependent on a fi rm’s ability to be aware

― 19 ―


of and associate with such sources of knowledge, together with its capacity to assimilate and apply such knowledge to R&D (Lynskey, 1999). Such ‘borrowing’ is easier where the benefi ts of agglom-eration economies, such as knowledge spillovers, labour pooling and specialised suppliers, come into effect and provide fi rms in a localised cluster with a competitive advantage over fi rms located outside the cluster. ‘Technological externalities’ or knowl-edge spillovers (Marshall, 1949; Porter, 1990; Krugman, 1991; Saxenian, 1994; Audretsch and Feldman, 1996; Feldman, 1999) are associated with ‘hot spots’ - the concentration of similar fi rms in close geographic proximity (Pouder and St. John, 1996; von Burg and Kenney, 2002).

Empirical studies on knowledge spillovers sug-gest that knowledge tends to be localised (Jaffe et al., 1993; Audretsch, 1998). Since such knowledge enhances the ‘technological capabilities’ of fi rms, those fi rms in close proximity to one another should exhibit benefi ts. For example, Deeds et al. (2000) show that the concentration of same-sector fi rms in a biotechnology fi rm’s geographic area is positively related to the number of new products developed by the fi rm. The benefi ts of location have also been explored in other technology sectors, such as com-puter software and optoelectronics. Moreover, the overall level of R&D investment is an important factor associated with geographic location (Acs et al., 1994b).

In addition to knowledge spillovers from other fi rms in a location, fi rms may enjoy externalities from proximity to universities or research institutes (Jaffe, 1989; Link and Rees, 1990; Acs et al., 1992; Acs et al., 1994a; Lissoni 2001; Lynskey, 2008). The rationale for this is that, since some of the knowledge of university-based scientists required for industrial innovation is not codifi ed, the transfer of tacit knowledge requires fi rms to maintain face-to-face interactions with such scientists (see Beise and Stahl, 1999; Nooteboom, 1999). Mansfi eld (1995) contends that proximity is signifi cant when the knowledge that is transferred is applied rather than basic. This has been supported in more recent studies by Autant-Bernard (2001) and Acs et al. (2002). Zucker and Darby’s (1998, 1999) notion of

‘star scientists’ are examples of university biomedi-cal specialists whose proximity to, or close collabo-ration with, biotechnology fi rms is thought to assist the commercialisation of academic research and im-pact favourably on fi rm creation and growth.

Owing to the centralised nature of Japanese academia and society, R&D activities are focused largely on Tokyo (see Masser, 1990; Kubo and Harada, 2001; Suzuki, 2001; Lynskey, 2006). In addition, the recipient fi rms of new and follow-on venture capital investments in Japan are also con-centrated in Tokyo, with 47.5 percent of new and follow-on investments by amount, and 46.8 percent by number, directed to fi rms in Tokyo.

For the purpose of this study, therefore, we look specifi cally at Tokyo, and defi ne TOKYO as a bi-nary dummy variable that takes the value 1 when a fi rm is located in Tokyo, or zero otherwise. We expect this variable to be positively related to R&D investment because of the presence of agglomera-tion economies.

H6: R&D investment is positively related to the location of the fi rm.

Age of the Firm

The fi nal fi rm-level variable, F_AGE, is a control variable defi ned as the number of years that have elapsed since a fi rm was established. We consider fi rm age because research suggests that fi rm growth and the probability that a fi rm will fail decrease with fi rm age (Evans 1987). This variable partly refl ects the macroeconomic conditions that prevailed in the year when a fi rm was founded. Highfi eld and Smi-ley (1987) suggest that macroeconomic factors are one of two factors (the other one being microeco-nomic factors) that infl uence the rate of creation of new fi rms. One of the incentives for an entrepreneur to establish a NTBF and engage in research is to commercialise the results of R&D and to seek rents thereby from doing so (Kirzner, 1973; Lynskey, 2002). The macroeconomic conditions prevailing in the year when a fi rm is established have some ef-fect on the rent-seeking activities of the fi rm, how-ever, and infl uence its subsequent development and


― 20 ―

R&D expenditure. Since such effects might bias the regression results, we control for these macroeco-nomic effects by using the variable F_AGE.

5.2 Entrepreneurship Variables

In addition to these strategic characteristics, we propose that R&D investment in NTBFs is affected also by entrepreneurial characteristics, such as hu-man capital. Entrepreneurship here is used in the sense of Schumperterian types, as well as the mana-gerial types who manage their business and com-pete for market share. The following refer to the entrepreneurial variables shown in Table 1.

Education – Direct Effect

Human capital (education) is one of the funda-mental variables explaining entrepreneurship (Ev-ans and Leighton, 1989; Kim et al., 2006). We con-sider the tertiary-level education of the founder or CEO of the NTBF to be an important factor in the level R&D investment, because discernment of the value of R&D and its capabilities requires special-ised knowledge acquired through higher education. Studies (Hitt and Tyler, 1991; Wally and Baum, 1994) suggest that more educated managers have greater cognitive complexity. It is generally as-sumed that such cognition provides greater ability to absorb new ideas and accept innovations. Stud-ies also indicate a positive effect between education and self-employment (Robinson and Sexton, 1994; Reynolds, 1997b). Bates (1995), who controlled for differences in industry when examining the role of education, also found a positive relationship be-tween education and self-employment.

Studies suggest that education is a key differenti-ating factor between high-technology entrepreneurs and the general population of entrepreneurs, since the former exhibit high levels of educational attain-ment (Klandt and Szyperski, 1988; Roberts, 1991; Westhead and Storey, 1994). Studies have also found that CEOs with higher levels of education lead more innovative fi rms (Kimberly and Evani-sko, 1981; Bantel and Jackson, 1989; Thomas et al., 1991). Klandt and Szyperski’s (1988) study found

that 88 percent of the founders of new technology based fi rms had attended university, compared to 32 percent of founders in general and 7.5 percent of employees. In their study, Westhead and Storey (1994) revealed that 84 percent of high technology entrepreneurs have a degree and 48 percent have a higher degree, while only 20 percent of entrepre-neurs in general are educated to degree level and only 2 percent have a post-graduate qualifi cation. Bhidé (2000) revealed that more than 80 percent of the entrepreneurs in his study had a university education. Thus, education appears to have a posi-tive impact on self-employment, at least in some (knowledge-intensive) industries.

Studies also report a positive relationship be-tween education and fi rm growth (e.g., Van de Ven et al., 1984; Roberts, 1991; Jo and Lee, 1996; Al-mus and Nerlinger, 1999; Wilbon, 2000), although this does not appear to be straightforward. Van de Ven et al. (1984) and Jo and Lee (1996), for exam-ple, fi nd a direct and linear relationship between ed-ucation and performance. The relationship between performance and education beyond degree level is not supported, however, in Almus and Nerlinger (1999); and Roberts (1991) does not fi nd a relation-ship between performance and education beyond master’s degree level. Almus and Nerlinger (1999) examine the impact of degree type on performance in technology-based new fi rms, and fi nd that fi rms established by entrepreneurs with technical degrees grow more rapidly than those with other qualifi ca-tions. This may be because science and engineering degrees create managers that have a more thorough understanding of technology and a more positive attitude to innovation (Tyler and Steensma, 1998). Almus and Nerlinger (1999) also affi rm that neither postgraduate business education, in the form of an MBA, nor the combination of an MBA and a tech-nical degree, impact on growth. This supports fi nd-ings that MBA programmes do little to develop in-novative or risk-taking skills in students (see Ham-brick and Mason, 1984; Finkelstein and Hambrick, 1996). Stuart and Abetti (1990) fi nd a negative, though not signifi cant, relationship between educa-tion and performance, resulting primarily from the relatively poor performance of PhDs. Likewise a

― 21 ―


study by Roberts (1991) reveals that education be-yond master’s degree level is negatively linked to success. In other words, while entrepreneurs with degrees generally outperform those without de-grees, entrepreneurs with PhDs do not perform as well as those with master degrees. Roberts (1991) suggests that the association between education and success in high technology fi rms is most likely to represent an ‘inverted “U” relationship’ rather than any statistically signifi cant direct relationship. Here, we consider a CEO’s tertiary-level education to be a determining factor in the level of R&D investment in NTBFs. Since the proportion of CEOs with fi rst degrees is very high in Japan, we decided that an ap-posite measure is how many CEOs have postgradu-ate degrees.

Education – Indirect Effect

In addition to this direct effect, human capital (educational background) is also likely to have an indirect effect on R&D investment in NTBFs. It helps to overcome barriers in obtaining credit/eq-uity, as well as fostering social networks, which in turn help to reduce transactions costs (Williamson, 1971; Nanda and Sorenson, 2007). Bates (1990), for example, shows that entrepreneurs with higher educational qualifi cations can raise money from capital markets more easily, and can survive in the market longer. Similarly, Scherer and Huh (1992) make a link between senior managers’ education and the level of R&D investment. In such cases, educational credentials appear to signify the entre-preneur’s potential in managing a successful fi rm. Here, UNIV_G denotes a dummy variable that takes the value 1 when a CEO has graduated from a post-graduate programme, and is otherwise zero.

H7: R&D investment is positively related to the CEO’s educational background.

Prior Experience in R&D

In an early study on the infl uence of managers’ career experiences, Dearborn and Simon (1958) ar-gued that experience of a particular business func-

tion in a fi rm causes managers to perceive and in-terpret information in ways that are consistent with and replicate their functional training. Later studies suggest that CEOs with signifi cant career experi-ence in output functions (i.e. R&D/engineering and marketing/sales) favour innovation strategies because these functions emphasise growth through discovering new products and markets (Hambrick and Mason, 1984; Finkelstein and Hambrick, 1996). Consequently, CEOs with output function career experience are likely to favour higher R&D invest-ment as part of their focus on innovation. Indeed, Thomas et al. (1991) found that fi rms in the com-puter industry pursuing strategies of product and market innovation had CEOs whose primary career experience was in output functions.

Determining the appropriate level of R&D in-vestment is likely to require a CEO to have practi-cal knowledge that can only be gleaned from actual business experience in an R&D function. In contrast to the explicit or codifi ed knowledge gained through formal education, and accounted for above under education, this type of knowledge is tacit in nature (Polanyi, 1958). It may be evident, for example, in the know-how needed to allocate proper resources to R&D, to organise research projects, and in other ‘hands-on’ tasks. Hills et al. (1999) suggest that be-tween 50–90 percent of start-up ideas derive from prior work experience. Such fi ndings lend support to Stinchcombe’s (1965) notion of the ‘liability of newness’, and the argument that fi rms tend to be es-tablished in those fi elds of previous relevant experi-ence to the founder. Therefore, a CEO’s prior expe-rience in an R&D capacity will impact on a NTBF’s ability to grow and be innovative, and may in part substitute for its lack of a track record. We assume that this prior experience is essential in conducting R&D effi ciently in NTBFs, and in determining the appropriate level of R&D investment in such fi rms. Here, EXP_RD is a binary dummy variable that is set to one when a CEO has such prior experience before founding his own fi rm, but is otherwise zero.

H8: R&D investment is positively related to a CEO’s prior experience in an R&D role.


― 22 ―

Next, we consider the effects of overt ‘entrepre-neurship’ on the level of R&D investment. Entre-preneurship is a notoriously diffi cult concept to measure, and researchers from different disciplines have attempted to capture it using different con-structs (Lynskey, 2002). Here, we attempt to exam-ine entrepreneurship by four variables that attempt to capture ‘entrepreneurship experience’.

CEO as Firm Founder

We assume that the CEO who is also the founder of the fi rm will tend to exhibit greater fl exibility and swiftness in decision-making, which we see as a quality of entrepreneurship in new fi rms be-cause the position still has novelty and is challeng-ing. The founder-CEO is likely to be a leader with both a clear entrepreneurial vision and the means to implement it (Penrose, 1959; Greiner, 1972). The founder-CEO is likely to have a ‘self-set’ goal (e.g., to create a new product) rather than a relative goal (e.g., to make more money than other fi rms), and as a result his motivation to reach his goal is likely to be higher. Moreover, those fi rms where the founder is still the CEO have most likely not yet reached the stage of ‘bureaucratic sclerosis’ or the ‘entre-preneurial paradox’ signifi ed by a fi rm in which bureaucracy impedes innovation and individual ac-tion (Schumpeter, 1942). Nor have they reached the level identifi ed by Chandler (1962) where profes-sional managers replace the founding entrepreneur.

Since the NTBFs under consideration in this study are by nature new fi rms, they are unlikely to have CEOs of long tenure. Studies on the ten-ure of CEOs suggest that long-tenured CEOs tend to make fewer changes in strategy as their tenure increases (Grimm and Smith, 1991). Hambrick and Fukutomi (1991) asserted that this lack of change occurs because, with increasing length of tenure, CEOs became more strongly committed to imple-menting their own paradigm for how a fi rm should be run. Hambrick and Fukutomi (1991) also argued that longer-tenured CEOs might lose interest in implementing organisational changes as their out-side interests increase and the novelty of a CEO’s job decreases. Moreover, Miller (1991) argued that

longer-tenured CEOs may lose touch with their fi rms’ environments and may not make the changes and investments necessary to keep the fi rm evolv-ing over time. Given such fi ndings, longer-tenured CEOs may have little interest in pursing strategies of innovation through higher R&D investment.

On the other hand, we expect that NTBFs with a founder-CEO react quickly to changes in the busi-ness environment and pursue a business model of higher R&D investment. It is interesting that Graber (2003) found an inverse relationship between turn-over of senior management in technology-based fi rms, especially the CEO, and R&D expenditure, and that this was particularly pronounced in small fi rms. Here, ENTRE denotes whether the current CEO is also the founding entrepreneur of the fi rm; this dummy variable takes a value of 1 if the current CEO is the founder of a fi rm, and is otherwise zero.

H9: R&D investment is high in a fi rm whose CEO is also the founder.

Age of the CEO

The subsequent variable, M_AGE, denotes the age of the CEO. Cressy (1996) suggests a model that assumes the probability of a new fi rm’s survival is an increasing function of an entrepreneur’s age. According to Harada (2003), however, an entrepre-neur’s age is negatively related to entrepreneurial success in Japan. In this study, we assume that a younger CEO is likely to be more entrepreneurial, in terms of having ‘energy, drive and a willingness to accept change’ (Child, 1974: 181), and being more comfortable with ambiguity and uncertainty - a quality recognised by Bhidé (2000) - than an older CEO, whom, we assume, is likely to be more cautious and risk averse. This is in agreement with several empirical studies, which have shown that older CEOs follow lower-growth strategies (Child, 1974), and tend to be more conservative (Hambrick and Mason, 1984) and risk averse (MacCrimmon and Wehrung, 1986). In terms of R&D investment, research by Dechow and Sloan (1991) showed that CEOs often reduce R&D investment in the years leading up to their exit, while younger CEOs are

― 23 ―


more risk tolerant in increasing R&D investment because their career and fi nancial security con-cerns have a longer time horizon. Gwynne (2003: 13) suggests that, ‘It may be logical for older CEOs to focus on short-term goals rather than long-term R&D investment’.

H10: R&D investment is negatively related to the age of the CEO.

Prior experience in the role of CEO

Similar prior experience, as a CEO or a founder of a start-up fi rm, plays a prominent role in success-ful opportunity recognition processes in entrepre-neurs (Hills and Shrader, 1998; Shane, 2000; Shep-herd and De Tienne, 2001; Ardichvili et al., 2003), and provides the most relevant experience for new fi rm managers. Ronstadt (1988) proposed the no-tion of the ‘corridor principle’ to account for mul-tiple venture formation by the same entrepreneur. This concept suggests that the act of having estab-lished a venture fi rm moves an entrepreneur down a venture corridor that allows him to see intersect-ing corridors leading to new venture opportunities that he could neither see, nor take advantage of, until he had started his initial venture. The fi rst time entrepreneur subsequently sees more attractive op-portunities after the initial venture is launched; new venture ‘corridors’ open to him, often because more is known or discovered about relevant contacts, reli-able suppliers, viable markets, product availability, competitive resources and response time. The es-sential point here is that this knowledge and the op-portunities they reveal most often emerge only after one establishes a business. Venkataraman (1997) uses similar imagery, and suggests that each person develops a knowledge corridor that enables one to see the potential benefi t in an opportunity because one has an existing frame of reference with which to interpret it. Stuart and Abetti (1990) fi nd a strong positive correlation between entrepreneurial experi-ence and performance, and rank prior experience as an owner manager as the highest level of manage-ment experience attainable in their study. Such prior experience enables CEOs to avoid the ‘liability of

newness’ in adjusting to a new role (Stinchcombe, 1965), and thus avoid one of the diffi culties to which a new organisation is exposed.

Thus, those CEOs that have experience of run-ning other companies, including previous ventures, before founding and/or running their current fi rm are more likely to possess better know-how about management in technology start-ups. The penulti-mate variable, EXP_CEO, is a dummy variable that signifi es the CEO’s similar prior experience, as a CEO in another fi rm. This takes the value of 1 if the current CEO has previous experience of managing other fi rms, and is otherwise set to zero.

H11: R&D investment is positively related to the CEO’s prior experience in running other fi rms.

CEO’s participation in networks

The fi nal management variable, NWK, is a dum-my variable that represents whether the CEO is en-gaged in a social network with other entrepreneurs and researchers, including university researchers (Aldrich and Zimmer, 1986; Saxenian, 1990, 1991; Dubini and Aldrich, 1991; Burt, 1993). The advan-tages of being a member of such a network are that the CEO has established socially embedded strong and weak ties (Granovetter, 1973), redundant and non-redundant ties (Burt, 1992b) and direct and non-direct ties (Ahuja, 2000) to the sources where useful information is likely to arise, and has reli-able channels to convey such knowledge from those sources. Such kinds of networks could bring useful information on, for example, new technology and competing businesses, and also permit the CEO to obtain resources cheaper than they could be ob-tained on markets and to secure resources that would not be available on markets at all, such as reputation and customer contacts (Witt, 2004). Network rela-tionships with various actors also positively affect innovation performance and productivity (Pittaway et al., 2004). In the case of small fi rms, innovation appears to be related to the extent to which they are embedded locally in networks (Freel, 2003). NWK is set to 1 if the CEO is actively engaged in such a network.


― 24 ―

H12: R&D investment is positively related to the CEO’s extent of networking.

Finally, since differences among industries may have an effect on the innovative activities of NTB-Fs, we introduce six industry dummies based on the Standard Industrial Classifi cation of Japan (SICJ) to treat these differences. Table 1 lists the complete set of variables and their defi nitions.

6. Data

The data for this study is from an original data-base compiled from a questionnaire survey sent to fi rms in several sectors: (1) chemical, (2) metal-working machinery, (3) special industrial machin-ery, (4) electrical machinery, (5) motor vehicles and associated parts, and (6) precision instruments. An identical follow-up survey was sent to fi rms in the information technology and biotechnology sectors. Our sample, representing a response rate of 27.9 percent, were fi rms classifi ed into one of eight sec-tors, and which had been established for 10 years or less. Regarding the distribution of the ages of the fi rms, 36.2 percent of the fi rms were formed in the initial three years, but this ratio declined later; only 6.9 percent of the fi rms were formed in the fi nal three years. Table 1 shows a list of the variables we consider, and Table 2 shows the summary statistics of our sample fi rms.

7. Empirical Results

We conducted fi ve regressions depending on the combination of ‘entrepreneurship’ variables. The estimated results are reported in table 3. This shows that the pseudo R-squared is 0.14, indicating a valid regression model.4 The following discusses the re-sults of our estimations for each of the independent variables.

As expected, the coeffi cient of TC shows a signif-icantly positive sign in each regression. This indi-cates that a fi rm’s technological capability is an im-

4 Pseudo R-squared is an indicator used to check the fi tness of non-linear regression models such as Tobit.

portant determinant of R&D and augments the level of R&D investment, confi rming hypothesis H1. Table 3 also shows that SALES is signifi cantly and positively related to current R&D investment. Tak-ing into account the existence of both information asymmetries and capital market imperfections, it is often diffi cult for start-ups to raise funds for R&D from outside the fi rm. This suggests that our sample fi rms had to depend substantially on internal funds such as suffi cient cash fl ows; and, indeed, this has invariably been the case with venture fi rms in Japan (Lynskey, 2004, 2006). Conversely, one could also interpret SALES as a proxy for demand (Cohen and Klepper, 1996a,b).5 An increase in demand enables a fi rm to appropriate some of its R&D expenditure, in which case R&D is positively related to demand. In any case, our results corroborate hypothesis H2.

The coeffi cients of VC are positive, confi rming hypothesis H3, but insignifi cant in the regressions. Table 2 shows that the mean of the variable VC is only about 0.0008, which implies that venture capital funds were almost negligible in our sample fi rms and not an important determinant of R&D in-vestment. This appears to be an accurate refl ection of the situation in Japan (Lynskey and Yonekura, 2001). Unlike venture capital fi rms in the USA or Europe, venture capital in Japan has tended to be invested later - at, or just before, an initial public offering (IPO), when a fi rm is already looking suc-cessful. Moreover, the scale of venture capital in-vestment in Japan has been much less than that in Europe or the USA. Since many Japanese venture capital fi rms are subsidiaries of banks or securities companies, their primary goal was not to achieve the highest return on investment but, instead, to in-crease the business of their parent company. They have also lacked the expertise to assess technology projects and have been risk-averse in providing funds for R&D in NTBFs.

The coeffi cient of the variable B_PLAN is posi-tive, supporting hypothesis H4, but insignifi cant. This is consistent with the results gleaned for small

5 SALES is also a proxy for the firm size. Estimated results show that elasticity of sales is below unity. This means that innovative activities are simply proportional to fi rm size.

― 25 ―


fi rms in the USA by Perry (2001), who found a posi-tive relationship between planning and fi rm failure, although the explanatory power of the relationship was weak. Perry (2001) makes the observation that there is likely to be some minimum employment level, perhaps in the range of fi ve to 15 employees, below which formal (written) planning has marginal value. For businesses below this threshold, the lim-ited scope, scale and complexity of a business are conducive to simple and intuitive planning, and the communication of plans may not require documen-tation, since so few people are involved. We surmise that in Japan, small, start-up fi rms, typically with very few employees, rarely undertake formal, writ-ten planning. Indeed, it may have limited value and utility, even for technology-based ventures, since, generally, they have not been required to develop an elaborate and sophisticated business plan in order to attract fi nance or to establish commercial credit with lenders (Bhidé, 2000). Our results are consist-ent with other fi ndings from Japanese SMEs, which indicate that approximately 70 percent of those with fewer than 20 employees, and nearly two-thirds of those with fewer than 100 employees, make no business plan whatsoever. Moreover, 18.9 percent of Japanese SMEs make a business plan merely be-cause, otherwise, they are unable to borrow capi-tal; and a further 22.2 percent do so only because of the advice from outsiders (SMEA, 2000). The value of business planning, therefore, appears to be ‘context dependent’ (Castrogiovanni, 1996). In ad-dition, of course, there is a distinction between the actual writing of a business plan and the process of planning – which may not result in a business plan. Moreover, it is likely not business planning per se, but the quality and content of the business plan that is important (Matherne, 2004).

The coeffi cient of JRDU is positive and signifi -cant in the estimations, validating hypothesis H5. These results suggest that joint R&D projects with universities augment fi rms’ in-house R&D and stimulate them to increase R&D investment. As previous studies (e.g., Cohen and Levinthal, 1989, 1990; Cockburn and Henderson, 1997) suggest, fi rms may have to develop their own technological capabilities by means of in-house R&D to assimi-

late and apply knowledge from universities, which may be especially important for technology-based new fi rms.

The variable TOKYO is insignifi cant in our equa-tions. We were unable to fi nd evidence that the sam-pled NTBFs located in Tokyo enjoy positive exter-nalities from their location in a concentration of oth-er similar fi rms. Moreover, despite our introducing a new dummy variable METRO, which was set to one when a fi rm was located in Tokyo or Osaka, we could not derive a signifi cantly positive coeffi cient from this variable. This may be because the number of NTBFs has to attain a critical value before the effect of knowledge spillovers and other attributes of agglomeration economies set in. Indeed, this may also help to explain why venture capital has not been as prominent in Japan as in other advanced economies. Studies imply that the scarcity of liquid-ity events in Japan, such as IPOs and acquisitions of new ventures, impacts negatively on the forma-tion of new ventures in metropolitan areas such as Tokyo. Since access to venture capital has hitherto been unimportant for Japanese start-up fi rms, which instead have relied on infusions of capital from per-sonal wealth or traditional banks, and since there are few IPOs and acquisitions of new ventures, lo-cation in a concentration of similar fi rms provide few agglomeration economy benefi ts.

Turning to the entrepreneurial characteristics, both UNIV_G and EXP_RD show signifi cantly positive coeffi cients in the regressions, corroborat-ing hypotheses H7 and H8. The former result im-plies that a CEO with a higher level of formal edu-cation more successfully manages the innovative activities of technology start-ups. Likewise, the fact that EXP_RD also shows positive signs suggests that experience in an R&D function before found-ing one’s own technology-related fi rm is useful to founder-CEOs after starting up their fi rms. Hence, R&D management capability described in terms of educational background or previous experience in an R&D role is an important factor in technology-based start-ups.

On the other hand, we could not derive signifi -cant results from the four variables designated for entrepreneurship. First, ENTRE did not show sig-


― 26 ―

nifi cant signs in the regressions, suggesting that it is unimportant if the current CEO is the founder of the fi rm. This implies, from our initial speculations, that a fl exible decision-making process is not crucial to R&D and R&D investment in technology start-ups. This is perhaps reasonable given the exploratory and long-term nature of much R&D. It may be more important, however, for ‘output functions’ other than R&D, such as engineering, marketing or sales. M_AGE was also insignifi cant in our results, sug-gesting that the age of a CEO is irrelevant to the R&D management of such fi rms. One of the reasons for this may be that R&D management is affected, not by the general experience captured by M_AGE, but by the special experience captured by EXP_RD, which was signifi cantly positive in our results. An-other explanation is that the CEOs in our sample fi rms were relatively old, with an average age of 51, and we did not have enough younger CEOs in our sample.6 Indeed, studies suggest that the found-ing entrepreneurs of NTBFs are relatively old in Japan. Similarly, the variable NWK did not show a signifi cant sign in our regressions. Networking with university researchers may well be an impor-tant element in R&D activity, but it does not appear to be an indispensable element in R&D investment; or else JRDU, which was signifi cant in our results at the fi rm-level, may have absorbed the effects of this variable. The variable EX_CEO was also insig-nifi cant in the regressions. This may be because the entrepreneurial characteristic captured by EX_CEO is an aggregation related mainly to management of the fi rm as a whole, and is either too broad to cap-ture R&D management per se, or is irrelevant to it.

8. Conclusion

This study attempted to examine empirically the determinants of R&D investment in Japanese new technology-based fi rms, using fi rm data compiled from an original questionnaire survey. We pro-posed that R&D investment in NTBFs are likely to

6 We tested whether there is a non-linear relationship between age of the manager and R&D intensity, introducing the square term of M_AGE, but we did not fi nd signifi cant results from these models.

be affected both by strategic characteristics, such as technological capability or the availability of in-ternal funds, and by entrepreneurial characteristics, such as university education.

Three of the seven strategic variables we selected (technological capability, sales and the number of joint R&D projects with universities) show statis-tically signifi cant signs in our models. Technologi-cal capability shows a signifi cantly positive sign in each regression, suggesting that it augments the lev-el of R&D investment. Sales also show signifi cantly positive signs in our results, implying that the avail-ability of internal funds is an important determinant of R&D investment in Japanese NTBFs. This is par-ticularly so since venture capital funding in the ear-ly stage of a fi rm’s development is diffi cult to attract in Japan. Indeed, our results showed that venture capital funding is insignifi cant in our regressions, suggesting that venture capital is not important in stimulating R&D investment in new Japanese fi rms. This has been borne out in several other studies. Re-search with universities, however, is positively re-lated to company fi nanced R&D. This suggests that joint R&D with universities and in-house R&D are complementary, and a fi rm may have to conduct ad-ditional R&D to absorb knowledge effi ciently from universities. Surprisingly, the variable TOKYO did not show statistically signifi cant signs in our regres-sions. We could not fi nd evidence that technology start-ups enjoy positive externalities from their lo-cation where many fi rms concentrate. This may be owing to the relatively small number of fi rms in our sample (145), or because there is a tendency for such technology-based fi rms to collaborate instead with universities, which we were able to capture in our regressions.

Regarding the entrepreneurial characteristics, a CEO’s educational background and prior experi-ence in an R&D function both show signifi cantly positive coeffi cients in the regressions. These re-sults suggest that universities play a role in fi rms’ R&D investments; the former result is a direct ef-fect of higher education, while the latter implies at least a tertiary education in order to have such prior R&D experience. The results for these two vari-ables, coupled with the fi nding that joint R&D pro-

― 27 ―


jects with universities is positively related to R&D investment, lead us to conclude that universities im-pact on R&D investments in NTBFs, both directly and indirectly.

Finally, we refer to limitations in our analysis. Firstly, we were unable to examine the determinants of R&D investment in fi rms that did not conduct such investments in the year under consideration. Reports from the Japanese government indicate that many small fi rms in Japan do not conduct in-house R&D – usually undertaking collaborative R&D in-stead - because of the lack of managerial resources and fi nance. Unfortunately, the results of our survey did not allow us to examine what differences there are between research-based fi rms and those less inclined to pursue research activities. This may be a topic for future examination when data on such fi rms becomes available. Secondly, our defi nition of new technology-based fi rms may be too broad. As such, we were unable to consider the effects of industry characteristics on R&D investment, one of which is the degree of appropriability in each indus-try. How these differences between industries alter

the level of R&D investment in start-up fi rms may also be an interesting topic for further research.

Another limitation, which we recognise, is that the R&D variable measures only inputs to the R&D process, not intermediate-stage outputs such as pat-ents or the commercialisation of products. If venture capital fi nancing is generally beyond the seed stage, and R&D is an input to the innovation process, and therefore occurs early, it is more likely that venture capital will be linked to later stage innovation vari-ables like product introductions. R&D investment may even lead to venture capital fi nancing, because such fi rms are more attractive to venture capital companies. In addition, location may provide ad-vantages for later-stage outcomes, such as product introductions, for example, because of proximity to partnering fi rms or suppliers.

Nevertheless, we have made an attempt to exam-ine some strategic and entrepreneurial character-istics of NTBFs in Japan, a fi eld that has hitherto been largely unexplored because of insuffi cient up-to-date data.

Table 1 List of Variables

Variable Defi nition

Stra

tegy

- lev

el

RD Natural logarithm of R&D expenditure in year Yn

TC Technological capability: researchers to total employees in year Yn-1

SALES Natural logarithm of sales in year Yn-1 (in ¥ millions)

VC Share of venture capital funds in total initial funds

B_PLAN Dummy variable: = 1 if a fi rm makes business plans

JRDU Number of joint R&D projects with universities

TOKYO Geographical dummy: = 1 if a fi rm is located in Tokyo.

F_AGE Number of years passed since a fi rm was founded

Entre

pren

euria

l- le

vel UNIV_G Set to 1 if CEO graduated from a post-graduate programme

EXP_RD Dummy variable: = 1 if CEO has experience working in R&D

ENTRE Dummy variable: = 1 if CEO is also the founder of the fi rm

M_AGE Age of current CEO

EXP_CEO Dummy variable: = 1 if CEO has prior experience running other fi rms

NWK Dummy variable: = 1 if CEO engaged in network with other researchers


― 28 ―

Table 2 Summary Statistics

No. of Obs. Mean S.D. Min. Max.

RD 145 2.290329 1.720286 0 9.047821

TC 145 .1638196 .1681251 0 1

SALES 145 5.39249 1.452815 1.791759 10.74628

VC 145 .0008276 0099655 0 .12

B_PLAN 145 .262069 .4412843 0 1

JRDU 145 .8 2.036473 0 15

TOKYO 145 .2206897 .4161491 0 1

F_AGE 145 5.537931 2.6823 0 9

UNIV_G 145 .0482759 .2150915 0 1

EXP_RD 145 .5517241 .4990412 0 1

ENTRE 145 .8413793 .3665883 0 1

M_AGE 145 51.67586 8.018107 22 76

EXP_CEO 145 .1448276 .3531468 0 1

NWK 145 .3862069 .4885666 0 1

― 29 ―


Table 3 Estimated Results: Tobit Regressions

(1) (2) (3) (4) (5)

TC .2.658***

(.7275) 2.665***

(.7462) 2.613***

(.7470) 2.636***

(.7553) 2.659***

(.7569)

SALES .6609***

(.0995) .6590***

(.0961) .6397***

(.1021) .6598***

(.1045) .6562***

(.1048)

VC16.68

(12.68)15.54

(12.54)15.58

(12.49)17.25

(12.66)16.42

(12.81)

B_PLAN.5008

(.3022).5259*(.3000)

.4812(.3034)

.4381(.3159)

.4677(.3242)

JRDU .1835***

(.0616) .1882***

(.0616) .1811***

(.0618) .1575***

(.0671) .1552***

(.0673)

TOKYO.2127

(.3135).2058

(.3195).1492

(.3225).1733

(.3253).1662

(.3255)

F_AGE-.0126(.0512)

-.0053(.0513)

-.0130(.0514)

-.0135(.0522)

-.0111(.0525)

UNIV_G 1.399***

(.5697) 1.413***

(.5723) 1.427***

(.5710) 1.331**

(.5864) 1.322**

(.5864)

EXP_RD .5393**

(.2664) .4804**

(.2649) .5375**

(.2467) .5331**

(.2740) .5447**

(.2753)

ENTRE-.3319(.3680)

--.3504(.3694)

-.3255(.3768)

-.3249(.3763)

M_AGE- .0132

(.0164).0152

(.0166).0141

(.0168).0130

(.0169)

EXP_CEO - - - -.1529

(.3818)

NWK - - -.2816

(.3072).2697

(.3084)CONST -2.724***

(1.152) -3.774***

(1.275) -3.377**

(1.367) -3.506***

(1.389) -3.450***

(1.394)Industry Dummies

YES YES YES YES YES

Pseudo R^2 0.145 0.143 0.146 0.148 0.148

No. of Obs. 149 150 148 145 145

Note: The logarithmic transformation of the dependent variable (R&D) uses a linear transformation of ((RD+1)*10). The Tobit censoring boundary is set to correspond to a zero observation. Standard error is in parentheses. *, ** and *** show statistical signifi cance at the 10 percent, 5 percent and 1 percent levels.


― 30 ―

References

Acs ZJ. 1999. Are Small Firms Important? Their Role and Impact (Boston, MA: Kluwer Academic Publish-ers).

Acs, Z. J. and Audretsch, D. B. (1988) Innovation in large and small fi rms: An empirical analysis, Ameri-can Economic Review, 78 (4): 678-690.

Acs, Z. J. and Audretsch, D. B. (1990) Innovation and Small Firms (Cambridge, MA: MIT Press).

Acs, Z. J. and Audretsch, D. B. (1991) R&D, fi rm size, and innovative activity. In Innovation and Technical Change: An International Comparison, Acs, Z. J. and Audretsch, D. B. (eds). New York: Harvester Wheat-sheaf.

Acs, Z. J., Audretsch, D. B. and Feldman, M. P. (1992) Real effects of academic research: Comment, Ameri-can Economic Review, 82 (1): 363-367.

Acs, Z. J., Audretsch, D. B. and Feldman, M. P. (1994a) R&D spillovers and recipient fi rm size, Review of Economics and Statistics, 76 (2): 336-340.

Acs, Z. J., Audretsch, D. B. and Feldman, M. P. (1994b) R&D spillovers and innovative activity, Managerial and Decision Economics, 15 (2): 131-138.

Acs, Z., Anselin, L. and Varga, A. (2002) Patents and innovation counts as measures of regional production of new knowledge, Research Policy, 31 (7): 1069-1085.

Afuah, A. (2002) Mapping technological capabilities into product markets and competitive advantage: the case of cholesterol drugs, Strategic Management Journal, 23, 171.

Ahuja, G. (2000) Collaboration networks, structural holes, and innovation: A longitudinal study, Adminis-trative Science Quarterly, 45 (3): 425-455.

Aldrich, H. and Zimmer, C. (1986) Entrepreneurship through social networks. In The art and science of entrepreneurship, Sexton, D. L. and Smilor, R. W. (eds). Cambridge, MA: Ballinger, 3-23.

Allinson, C., Chell, E. and Hayes, J. (2000) Intuition and entrepreneurial behavior, European Journal of Work and Organizational Psychology, 9 (1): 31-43.

Almus, M. and Nerlinger, E. A. (1999) Growth of new technology-based fi rms: Which factors matter?, Small Business Economics, 13 (2): 141-154.

Ardichvili, A., Cardozo, R. and Ray, S. (2003) A theory

of entrepreneurial opportunity identifi cation and de-velopment, Journal of Business Venturing, 18 (1): 105-123.

Audretsch, D. B. (1995) Innovation and Industry Evolu-tion (Cambridge, MA: MIT Press).

Audretsch, D. B. (1998) Agglomeration and the location of innovative activity, Oxford Review of Economic Policy, 14 (2): 18-29.

Audretsch, D. B. and Feldman, M. P. (1996) R&D spill-overs and the geography of innovation and produc-tion, American Economic Review, 86 (3): 630-640.

Autant-Bernard, C. (2001) Science and knowledge fl ows: Evidence from the French case, Research Pol-icy, 30 (7): 1069-1078.

Bantel, K. A. and Jackson, S. E. (1989) Top manage-ment innovations in banking: Does the composition of the top team make a difference?, Strategic Man-agement Journal, 10 (Special Issue): 107-124.

Bates, T. (1990) Entrepreneur human capital inputs and small business longevity, Review of Economics and Statistics, 72 (4): 551-559.

Bates, T. (1995) Self-employment entry across industry groups, Journal of Business Venturing, 10 (2): 143-156.

Baysinger, B. and Hoskisson, R. E. (1989) Diversifi -cation strategy and R&D intensity in multiproduct fi rms, Academy of Management Journal, 32 (2): 310-332.

Baysinger, B. D., Kosnik, R. D. and Turk, T. A. (1991) Effects of board and ownership structure on corporate R&D strategy, Academy of Management Journal, 34 (1): 205-214.

Beise, M. and Stahl, H. (1999) Public research and in-dustrial innovations in Germany, Research Policy, 28 (4): 397-422.

Bhidé, A. V. (2000) The Origin and Evolution of New Businesses (Oxford: Oxford University Press).

Boltho, A. and Corbett, J. (2000) The assessment: Ja-pan’s stagnation – can policy revive the economy?, Oxford Review of Economic Policy, 16 (2): 1-17.

Breschi, S. and Lissoni, F. (2001) Knowledge spillovers and local innovation systems: A critical survey, In-dustrial and Corporate Change, 10 (4): 975-1005.

Burt, R. (1992a) The social structure of competition. In Networks and Organizations: Structure, Form and Act, Nitin N, Eccles RG (eds). Boston, MA: Harvard

― 31 ―


Business School Press.Burt, R. (1992b) Structural Holes (Cambridge, MA:

Harvard University Press). Burt, R. (1993) The network entrepreneur. In Explora-

tions in Economic Sociology, Swedberg, R. (ed). Rus-sell Sage Foundation.

Carter, N. M., Gartner, W. B. and Reynolds, P. D. (1996) Exploring start-up event sequences, Journal of Busi-ness Venturing, 11 (3): 151-166.

Castanias, R. P. and Helfat, C. E. (2001) The managerial rents model: theory and empirical analysis, Journal of Management, 27 (6): 661-678.

Castrogiovanni, G. J. (1996) Pre-startup planning and the survival of new small businesses: Theoretical linkages, Journal of Management, 22 (6): 801-822.

Caves, R. E. (1998) Industrial organization and new fi ndings on the turnover and mobility of fi rms, Jour-nal of Economic Literature, 36 (4): 1947-1982.

Chandler, A. D. (1962) Strategy and Structure: Chap-ters in the History of the Industrial Enterprise (Cam-bridge, MA: MIT Press).

Child, J. (1974) Managerial and organizational factors associated with company performance – Part I, Jour-nal of Management Studies, 11 (3): 175-189.

Cockburn, I. and Henderson, R. (1997) Public–private interaction and the productivity of pharmaceutical re-search, NBER Working Paper, No. 6018. Cambridge, MA: National Bureau of Economic Research.

Cohen, W. M. and Klepper, S. (1996a) Firm size and the nature of innovation within industries: The case of process and product R&D, Review of Economics and Statistics, 78 (2): 232-243.

Cohen, W. M. and Klepper, S. (1996b) A reprise of size and R&D, Economic Journal, 106 (437): 925-951.

Cohen, W. M. and Levinthal, D. A. (1989) Innovation and learning: The two faces of R&D, Economic Jour-nal, 99 (397): 569-596.

Cohen, W. M. and Levinthal, D. A. (1990) Absorptive capacity: A new perspective on learning and innova-tion, Administrative Science Quarterly, 35 (1): 128-152.

Cressy, R. (1996) Are business start-ups debt rationed?, Economic Journal, 106 (438): 1253-1270.

Daellenbach, U. S., McCarthy, A. M. and Schoenecker, T. S. (1999) Commitment to innovation: The impact of top management team characteristics, R&D Man-

agement, 29 (3): 199-209.Datta, D. K. and Guthrie, J. P. (1994) Executive succes-

sion: Organizational antecedents of CEO characteris-tics, Strategic Management Journal, 15 (7): 569-577.

David, P. A. (1994) Positive feedbacks and research pro-ductivity in science: Reopening another black box. In Economics of Technology, Granstrand, O. (ed). Am-sterdam: Elsevier Science, 5-89.

Dearborn, C. C. and Simon, H. A. (1958) Selective per-ception: A note on the department identifi cations of executives, Sociometry, 21: 140-144.

Dechow, P. and Sloan, R. (1991) Executive incentives and the time horizon problem, Journal of Accounting and Economics, 14 (1): 51-89.

Deeds, D. L., DeCarolis, D. and Coombs, J. (2000) Dy-namic capabilities and new product development in high technology ventures: An empirical analysis of new biotechnology fi rms, Journal of Business Ventur-ing, 15 (3): 211-229.

Delmar, F. and Shane, S. (2003) Does business planning facilitate the development of new ventures?, Strate-gic Management Journal, 24 (12): 1165-1185.

Delmar, F. and Shane, S. (2004) Planning for the mar-ket: Business planning before marketing and the con-tinuation of organizing efforts, Journal of Business Venturing, 19 (6): 767-785.

Dubini, P. and Aldrich, H. (1991) Personal and extended networks are central to the entrepreneurial process, Journal of Business Venturing, 6 (5): 305-313.

Eshima, Y. (2003) Impact of public policy on innovative SMEs in Japan, Journal of Small Business Manage-ment, 41 (1): 85-93.

Evans, D. S. (1987) The relationship between fi rm growth, size, and age: Estimates for 100 manufactur-ing industries, Journal of Industrial Economics, 35 (4): 567-581.

Evans, D. and Leighton, S. (1989) Some empirical as-pects of entrepreneurship, American Economic Re-view, 79: 519-535.

Feldman, M. P. (1999) The new economics of innova-tion, spillovers and agglomeration: A review of em-pirical studies, Economics of Innovation & New Tech-nology, 8 (1/2): 5-25.

Finkelstein, S. and Hambrick, D. C. (1996) Strategic Leadership: Top Executives and their Effects on Or-ganizations (St. Paul, MN: West Publishing Com-


― 32 ―

pany).Freel, M. S. (2003) Sectoral patterns of small fi rm inno-

vation, networking and proximity, Research Policy, 32 (5): 751-770.

Gavron, R., Cowling, M., Holtham, G. and Westhall, A. (1998) The Entrepreneurial Society (London: Insti-tute for Public Policy Research).

Gonzáles, X. and Pazó, C. (2004) Firms’ R&D Dilem-ma: To Undertake or Not to Undertake R&D, Applied Economics Letters, 11 (1): 55-59.

Graber, R. S. (2003) Management turnover and under-investment in R&D: An agency theory explanation for under-investment in research and development in some corporations, Journal of Social Political and Economic Studies, 28 (3): 295-324.

Granovetter, M. (1973) The strength of weak ties, Amer-ican Journal of Sociology, 78 (6): 1360-1380.

Graves, S. B. (1988) Institutional ownership and corpo-rate R&D in the computer industry, Academy of Man-agement Journal, 31 (2): 417-427.

Green, S. (1995) Top management support of R&D projects: A strategic leadership perspective, IEEE Transactions on Engineering Management, 42 (3): 223-234.

Greene, W. H. (1997) Econometric analysis, 3rd edition (Upper Saddle River, NJ: Prentice Hall).

Greiner, L. E. (1972) Evolution and revolution as or-ganizations grow, Harvard Business Review, 50 (4): 37-46.

Grimm, C. M. and Smith, K. G. (1991) Management and organizational change: A note on the railroad in-dustry, Strategic Management Journal, 12: 557-562.

Gwynne, P. (2003) How CEO characteristics affect R&D spending, MIT Sloan Management Review, 44 (2): 13.

Hall, B. (1992) Investment and research and develop-ment at the fi rm level: Does the source of fi nancing matter?, NBER Working Paper, No. 4096, Cambridge, MA: National Bureau of Economic Research.

Hall, B. (2002) The fi nancing of research and develop-ment, Oxford Review of Economic Policy, 18 (1): 35-51.

Hall, B. H., Link, A. N. and Scott, J. T. (2000) Universi-ties as research partners, NBER Working Paper, No. 7643, Cambridge, MA: National Bureau of Econom-ic Research.

Hambrick, D. C. and Fukutomi, G. D. S. (1991) The seasons of a CEO’s tenure, Academy of Management Review, 16 (4): 719-742.

Hambrick, D. C., Black, S. and Fredrickson, J. W. (1992) Executive leadership of the high-technology fi rm: What’s so special about it? In Advances in Glob-al High-Technology Management, Gomez-Mejia, L. R. and Lawless, M. W. (eds). Greenwich, CT: JAI Press, Vol. 2: 3-18.

Hansen, G. S. and Hill, C. W. L. (1991) Are institu-tional investors myopic? A time series study of four technology-driven industries, Strategic Management Journal, 12: 1-16.

Harada, N. (2004) Productivity and Entrepreneurial Characteristics in New Japanese Firms, Small Busi-ness Economics, 23 (4): 299-310.

Henderson, R., Jaffe, A. B. and Trajtenberg, M. (1995) Universities as a source of commercial technology: A detailed analysis of university patenting 1965-1988, NBER Working Paper, No. 5068 (Cambridge, MA: National Bureau of Economic Research).

Highfi eld, R. and Smiley, R. (1987) New business starts and economic activity: An empirical investigation, International Journal of Industrial Organization, 5 (1): 51-66.

Hills, G. E. and Shrader, R. C. (1998) Successful en-trepreneur’s insights into opportunity recognition. In Frontiers of Entrepreneurship Research, Reynolds, P. D., Bygrave, W. D., Carter, N. M., Manigart, S., Mason, C. M., Meyer, G. D. and Shaver, K. G. (eds). Wellesley, MA: Babson College, 30-43.

Hills, G. E., Shrader, R. C. and Lumpkin, G. T. (1999) Opportunity recognition as a creative process. In Frontiers of Entrepreneurship Research, Reynolds, P. D., Bygrave, W. D., Maingart, S., Mason, C., Meyer, G. D., Sapienza, H. and Shaver, K. G. (eds). Welles-ley, MA: Babson College.

Himmelberg, C. P. and Petersen, B. C. (1994) R&D and internal fi nance: A panel study of small fi rms in high-tech industries, Review of Economics and Statistics, 76 (1): 38-51.

Hitt, M. A. and Tyler, B. B. (1991) Strategic decision models: Integrating different perspectives, Strategic Management Journal, 12 (5): 327-351.

Honjo, Y. (2004) Growth of new start-up fi rms: Evi-dence form the Japanese manufacturing industry, Ap-

― 33 ―


plied Economics, 36 (4): 343-356.Horwitz, B. and Kolodny, R. (1981a) The impact of rule

making on R&D investments of small high-technol-ogy fi rms, Journal of Accounting, Auditing and Fi-nance, 4 (2): 102-113.

Horwitz, B. and Kolodny, R. (1981b) The FASB, the SEC and R&D, Bell Journal of Economics, 12 (1): 249-262.

Hoskisson, R. E. and Hitt, M. A. (1988) Strategic con-trol systems and relative R&D investment in large multiproduct fi rms, Strategic Management Journal, 9: 605-621.

Imai, Y. and Kawagoe, M. (2000) Business start-ups in Japan: Problems and policies, Oxford Review of Eco-nomic Policy, 16 (2): 114-123.

Jaffe, A. B. (1989) Real effects of academic research, American Economic Review, 79 (5): 957-970.

Jaffe, A. B., Trajtenberg, M. and Henderson, R. (1993) Geographic localization of knowledge spillovers as evidenced by patent citations, Quarterly Journal of Economics, 108 (3): 577-598.

Japan Small Business Research Institute (JSBRI) (2003) White Paper on Small and Medium Enterprises in Japan (Tokyo: Japan Small Business Research Insti-tute).

Jo, H. and Lee, J. (1996) The relationship between an entrepreneur’s background and performance in a new venture, Technovation, 16 (4): 161-171.

Kim, P., Aldrich, H. and Keister, L. (2006) Access (not denied): the impact of fi nancial, human and cultural capital on entrepreneurship entry in the United States, Small Business Economics, 27, 5-22.

Kimberly, J. R. and Evanisko, M. J. (1981) Organiza-tional innovation: The infl uence of individual, orga-nizational and contextual factors on hospital adoption of technical and administrative innovations, Academy of Management Journal, 24 (4): 689-713.

Kirzner, I. M. (1973) Competition and Entrepreneurship (Chicago: University of Chicago Press).

Klandt, H. and Szyperski, N. (1988) Similarities and differences between business founders and NTBF founders. In New Technology Based Firms in Britain and Germany, London: Anglo German Foundation, 33-47.

Kortum, S. and Lerner, J. (2000) Assessing the contribu-tion of venture capital to innovation, RAND Journal

of Economics, 31 (4): 674-692.Krugman, P. (1991) Geography and Trade (Cambridge,

MA: MIT Press).Kubo, T. and Harada, S. (eds.) (2001) The Knowledge

Economy and Science Parks: Entrepreneurial Urban Strategies in the Age of Globalisation (Chishiki kizai to science park) [in Japanese] (Tokyo: Nihon Hy-oronsha).

Kuemmerle, W. (2001) Comparing catalysts of change: Evolution and institutional differences in the venture capital industries in the U.S., Japan and Germany. In Comparative Studies of Technological Evolution, Burgelman, R. A. and Chesbrough, H. (eds). Amster-dam and Oxford: Elsevier Science, pp. 227-261.

Lach, S. (2000) Do R&D subsidies stimulate or displace private R&D? Evidence from Israel, NBER Working Paper, No. 7943 (Cambridge, MA: National Bureau of Economic Research).

Lado, A. A., Boyd, N. G. and Wright, P. (1992) A com-petency-based model of sustainable competitive ad-vantage: toward a conceptual integration, Journal of Management, 18 (1): 77-91.

Lee, C., Lee, K. and Pennings, J. M. (2001) Internal capabilities, external networks, and performance: a study on technology-based ventures, Strategic Man-agement Journal, 22 (6-7): 615-640.

Lichtenberg, F. R. and Siegel, D. (1991) The impact of R&D investment on productivity – New evidence us-ing linked R&D-LRD data, Economic Inquiry, 29 (2): 203-229.

Lynskey, M. J. (1999) The Transfer of Resources and Competencies for Developing Technological Capa-bilities - The Case of Fujitsu-ICL, Technology Analy-sis & Strategic Management, 11 (3): 317-336.

Lynskey, M. J. (2001) Technological Distance, Spatial Distance and Sources of Knowledge: Japanese ‘New Entrants’ in ‘New’ Biotechnology, in R. A. Burgel-man and H. Chesbrough eds., Comparative Studies of Technological Evolution (Amsterdam and Oxford: Elsevier Science), pp. 127-205.

Lynskey, M. J. (2002) Introduction in M. J. Lynskey and S. Yonekura eds., Entrepreneurship and Organiza-tion: The Role of the Entrepreneur in Organizational Innovation (Oxford: Oxford University Press), pp. 1-57.

Lynskey, M. J. and Yonekura, S. (2001) Softbank: An


― 34 ―

Internet Keiretsu and its Leveraging of Information Asymmetries, European Management Journal, 19 (1): 1-15.

Lynskey, M. J. (2004) Knowledge, Finance and Human Capital: The Role of Social Institutional Variables on Entrepreneurship in Japan, Industry and Innovation, 11 (4): 373-405.

Lynskey, M. J. (2006) Transformative Technology and Institutional Transformation: Co-evolution of Biotechnology Venture Firms and the Institutional Framework in Japan, Research Policy, 35 (9): 1389-1422.

Lynskey, M. J. (2009) Knowledge Spillovers from Pub-lic Research Institutions to the Private Sector: Evi-dence from Japanese New Technology-Based Firms, International Journal of Technology Transfer and Commercialisation, 8 (2/3): 159-184.

Lynskey, M. J. (2010) Capitalizing on Knowledge from Public Research Institutions: Indications from New Technology-Based Firms in Japan, Industry and Higher Education, 24 (1): 29-45.

MacCrimmon, K. R. and Wehrung, D. A. (1986) Taking Risks: The Management of Uncertainty (New York: Free Press).

Mansfi eld, E. (1968) Industrial Research and Techno-logical Innovation (New York: Norton).

Mansfi eld, E. (1995) Academic research underlying in-dustrial innovations: Sources, characteristics, and fi -nancing, Review of Economics and Statistics, 77 (1): 55-65.

Mansfi eld, E. and Lee, J.-Y. (1996) The modern univer-sity: Contributor to industrial innovation and recipi-ent of industrial R&D support, Research Policy, 25 (7): 1047-58.

March, J. and Simon, H. (1958) Organizations (New York: Wiley).

Marshall, A. (1949) Elements of Economics of Industry (London: Macmillan).

Masser, I. (1990) Technology and regional develop-ment policy: A review of Japan’s technolopolis pro-gramme, Regional Studies, 21 (1): 41-53.

Matherne, B. P. (2004) If you fail to plan, do you plan to fail?, Academy of Management Executive, 18 (4): 156-157.

Mayer, C., Schoors, K. and Yafeh, Y. (2003) Sources of funds and investment activities of venture capital

funds: Evidence from Germany, Israel, Japan and the UK, NBER Working Paper No. 9645. Cambridge, MA: National Bureau of Economic Research.

Miller, D. (1991) Stale in the saddle: CEO tenure and the match between organization and environment, Management Science, 37 (1): 34-52.

Motohashi, K. (2004) Economic Analysis of University-Industry Collaborations: The Role of New Technol-ogy Based Firms in Japanese National Innovation Reform, RIETI Discussion Paper, 04E001 (Tokyo: Research Institute of Economy, Trade and Industry).

Mulkay, B., Hall, B. and Mairesse, J. (2000) Investment and R&D in France and the United States, NBER Working Paper, No. 8038, Cambridge, MA: National Bureau of Economic Research.

Nakayama, Y., Hosono, M., Saito, Y., Fukugawa, N. and Kobayashi, S. (2003) ‘University-Industry Research Cooperation: A Status Report 1983-2001’, NISTEP Research Material No. 96 (Tokyo: National Institute of Science and Technology Policy).

Nooteboom, B. (1999) Innovation, learning and indus-trial organization, Cambridge Journal of Economics, 23 (2): 127-150.

Pavitt, K., Robson, M. and Townsend, J. (1987) The size distribution of innovating fi rms in the UK: 1945-1983, Journal of Industrial Economics, 35 (3): 297-316.

Penrose, E. T. (1959) The Theory of the Growth of the Firm (Oxford: Basil Blackwell).

Perry, S. C. (2001) The relationship between written business plans and the failure of small businesses in the U.S., Journal of Small Business Management, 39 (3): 201-208.

Phillips, B. D. and Kirchhoff, B. A. (1989) Formation, growth, and survival: Small fi rm dynamics in the U.S. economy, Small Business Economics, 1 (1): 65-74.

Pittaway, L., Robertson, M., Munir, K., Denyer, D. and Neely, A. (2004) Networking and innovation: A sys-tematic review of the evidence, International Journal of Management Reviews, 5/6 (3/4): 137-168.

Polanyi, M. (1958) Personal Knowledge: Towards a Post-Critical Philosophy (Chicago: University of Chicago Press).

Porter, M. E. (1990) The Competitive Advantage of Na-tions (New York: Free Press).

Pouder, R. and St. John, C. H. (1996) Hot spots and

― 35 ―


blind spots: Geographic clusters of fi rms and innova-tion, Academy of Management Journal, 21 (4): 1192-1225.

Rajagopolan, N. and Datta, D. K. (1996) CEO charac-teristics: Does industry matter?, Academy of Manage-ment Journal, 39 (1): 197-215.

Reynolds, P. D. (1997a) New and small fi rms in expand-ing markets, Small Business Economics, 9 (1): 79-84.

Reynolds, P. D. (1997b) Who starts new fi rms? Prelimi-nary explorations of fi rms-in-gestation, Small Busi-ness Economics, 9 (5): 449-462.

Roberts, E. B. (1991) Entrepreneurs in High Technol-ogy: Lessons from MIT and Beyond (New York: Ox-ford University Press).

Robinson, P. B. and Sexton, E. A. (1994) The effect of education and experience on self-employment suc-cess, Journal of Business Venturing, 9 (2): 141-156.

Ronstadt, R. (1988) The corridor principle, Journal of Business Venturing, 3 (1): 31-40.

Rue, L. W. and Ibrahim, N. A. (1998) The relationship between planning sophistication and performance in small businesses, Journal of Small Business Manage-ment, 36 (4): 24-32.

Sakakibara, M. (1997) Heterogeneity of fi rm capabili-ties and cooperative research and development: An empirical examination of motives, Strategic Manage-ment Journal, 18 (S1): 143-164.

Sakakibara, K., Koga, T., Honjo, Y. and Kondo, K. (2000) Nihon ni okeru gijutsukei benchaa kigyo no keiei jittai to sougyou-sha ni kan suru chousa kenkyu (Survey research on technology-based start-ups and their entrepreneurs in Japan) [in Japanese]. Tokyo: National Institute of Science and Technology Policy (NISTEP).

Santoro, M. D. and Chakrabatri, A. K. (2002) Firm size and technology centrality in industry-university inter-actions, Research Policy, 31 (7): 1163-1180.

Saxenian, A. (1990) Regional networks and the resur-gence of Silicon Valley, California Management Re-view, 33 (1): 89-112.

Saxenian, A. (1991) The origins and dynamics of pro-duction networks in Silicon Valley, Research Policy, 20 (5): 423-437.

Saxenian, A. (1994) Regional advantage: Culture and competition in Silicon Valley and Route 128. (Cam-bridge, MA: Harvard University Press).

Schaede, U. (2008) Choose and Focus: Japanese Busi-ness Strategy for the 21st Century (New York: Cor-nell University Press).

Scherer, F. M. (1965) Firm size, market structure, op-portunity, and the output of patented inventions, American Economic Review, 55 (5): 1097-1125.

Scherer, F. M. and Huh, K. (1992) Top managers’ educa-tion and R&D investment, Research Policy, 21 (6): 507-511.

Schoenecker, T. S. and Swanson, L. J. (2002) Indicators of fi rm technological capability: validity and perfor-mance implications, IEEE Transactions on Engineer-ing Management, February: 36-44.

Schumpeter, J. A. (1942) Capitalism, Socialism and De-mocracy (New York: Harper & Row).

Shane, S. (2000) Prior knowledge and the discovery of entrepreneurial opportunities, Organizational Sci-ence, 11 (4): 448-469.

Shefer, D. and Frenkel, A. (2005) ‘R&D, Firm Size and Innovation: An Empirical Analysis’, Technovation, 25 (1): 25-32.

Shepherd, D. A. and De Tienne, D. R. (2001) Discov-ery of opportunities: Anomalies, accumulation and alertness. In Frontiers of Entrepreneurship Research: Proceedings of the Twenty-First Annual Entrepre-neurship Research Conference, Bygrave, W. D., Autio, E., Brush, C. G., Davidsson, P., Green, P. G., Reynolds, P. D. and Sapienza, H. J. (eds) (Wellesley, MA: Babson College).

Small and Medium Enterprise Agency (SMEA) (2000) White Paper on Small and Medium Enterprises in Ja-pan (2000). Tokyo: Small and Medium Enterprise Agency, Ministry of Economy, Trade and Industry (METI).

Stephan, P. (1996) The economics of science, Journal of Economic Literature, 34 (3): 1199-1235.

Stinchcombe, A. L. (1965) Social structures and orga-nizations. In Handbook of Organizations, March JG. (ed) (Chicago: Rand McNally), 142-193.

Storey, D. J. (1994) Understanding the Small Business Sector (London: Routledge).

Stuart, R. W. and Abetti, P. A. (1990) Impact of en-trepreneurial and management experience on early performance, Journal of Business Venturing, 5 (3): 151-162.

Suzuki, S. (2001) Research on High-tech Development


― 36 ―

Policies (high-tech gata kaihatsu seisaku no kenkyu) [in Japanese] (Tokyo: Minerva).

Szakonyi, R. (1990) Coordinating R&D and business planning, Technology Analysis & Strategic Manage-ment, 2 (4): 391-411.

Tether, B. and Storey, D. (1998) Smaller fi rms and Eu-rope’s high technology sectors, Research Policy, 26 (9): 947-971.

Tyler, B. B. and Steensma, H. K. (1998) The effects of executives’ experiences and perceptions on their as-sessment of potential technical alliances, Strategic Management Journal, 19 (10): 939-965.

Van de Ven, A. H., Hudson, R. and Schroeder, D. M. (1984) Designing new business startups: Entrepre-neurial, organizational and ecological considerations, Journal of Management, 10 (1): 87-107.

Venkataraman, S. (1997) The distinctive domain of en-trepreneurship research: An editor’s perspective. In Advances in entrepreneurship, fi rm emergence and growth, Katz J, Brockhaus R (eds) (Greenwich, CT: JAI Press), 119-138.

VEC (Venture Enterprise Center, Ministry of Economy Trade and Industry) (2002) 2001 Survey of Japanese Venture Capital Investments [and] Venture Capital Fund Benchmark Survey (Tokyo: VEC).

von Burg, U. and Kenney, M. (2002) Venture Capital and the Local Area Networking Industry. In Entrepre-neurship and Organization: The Role of the Entrepre-neur in Organizational Innovation, Lynskey, MJ and Yonekura S. (eds) (Oxford: Oxford University Press), 209-237.

Wally, S. and Baum, J. (1994) Personal and structural determinants of the pace of strategic decision mak-ing, Academy of Management Journal, 37 (4): 932-956.

Westhead, P. and Storey, D. J. (1994) An Assessment of Firms Located on and off Science Parks in the United Kingdom (London: HMSO).

Wilbon, A. D. (2000) Executive technology education and fi rm performance, Technology Management: Strategies and Applications, 5 (1): 103-109.

Witt, P. (2004) Entrepreneurs’ networks and the success of start-ups, Entrepreneurship & Regional Develop-ment, 16 (5): 391-412.

Zahra, S. A. (1999a) The changing rules of global com-petitiveness in the 21st century, Academy of Manage-

ment Executive, 13 (1): 36-42.Zahra, S. A. (1999b) Technology strategy and fi nancial

performance: Examining the moderating role of the fi rm’s competitive environment, Journal of Business Venturing, 11 (3): 189-219.

Zahra, S. A. and Pearce, J. A. (1989) Board of directors and corporate fi nancial performance: A review and integrative model, Journal of Management, 15 (2): 291-334.

Zantout, Z. Z. and Tsetsekos, G. P. (1994) The wealth ef-fects of announcements of R&D expenditure increas-es, Journal of Financial Research, 17 (2): 205-216.

Zucker, L. G. and Darby, M. R. (1998) Capturing tech-nological opportunity via Japan’s star scientists: Evi-dence from Japanese fi rms’ biotech patents and prod-ucts, NBER Working Paper, No. 6360. Cambridge, MA: National Bureau of Economic Research.

Zucker, L. G. and Darby, M. R. (1999) Star-scientist linkages to fi rms in APEC and European countries: Indicators of regional institutional differences affect-ing competitive advantage, International Journal of Biotechnology, 1 (1): 119-131.

determinants of r&d investment: strategic and

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