گرایش کارآفرینی، انتقال فن آوری و عملکرد اسپین آف دانشگاه های آمریکا

This paper adopts a resource-based perspective to understand why some universities are more successful than others at generating technology-based spinoff companies. In this respect, we derive eight hypotheses that link attributes of resources and capabilities, institutional, financial, commercial and human capital, to university spinoff outcomes. Using panel data from 1980 to 2001, our econometric estimators reveal evidence of history dependence for successful technology transfer to occur although faculty quality, size and orientation of science and engineering funding and commercial capability were also found to be predictors of university spinoff activity. We conclude by drawing implications for policy makers and university heads.

Given the difficulties of established firms in bringing new technologies to the market (Utterback, 1994), U.S. universities are increasingly viewed as a source for the creation of high tech firms (Roberts, 1991). As a result, there is a growing need for universities to develop more ‘rapid’ linkages between science, technology and utilization (Allen and Cohen, 1969 and Allen et al., 1979) and serve a ‘third-mission’ of contributing to local economic development (Etzkowitz, 2002). These developments are posing challenges to the traditional role of the university and its support practices towards entrepreneurial activities (Van Dierdonck and Debackere, 1988 and Lerner, 2004). The importance of the traditional university is well documented in the literature (Geiger, 1993 and Bok, 2003). Their primary mission is to engage in research and disseminate knowledge across both academic and student communities. They also contribute indirectly to technology transfer activities by providing highly educated and qualified personnel to industry (Carayannis et al., 1998). According to Segal (1986), these universities not only provide a source of technical expertise for faculty members, but their students also acquire a wealth of codified and tacit knowledge through learning and living at the university. However, across national economies there is a need for more emphasis to be placed on transferring and commercializing knowledge generated within universities (Cohen et al., 1998). More specifically, there is a growing need for universities to disseminate the knowledge generated beyond the narrow confines of the academic community itself (Mansfield and Lee, 1996, Branscomb et al., 1999 and Hague and Oakley, 2000). As a result, many universities are now playing a third role in society through actively converting new scientific discoveries into spinoff opportunities (Kinsella and McBrierty, 1997 and Leitch and Harrison, 2005). In essence, these ‘entrepreneurial’ oriented universities, as coined by Etzkowitz (1998), are proving key for regional economic development, going beyond the provision of graduates and research. Although some authors refer to the spinoff strategies of different European public research-based institutions (Klofsten and Jones-Evans, 2000, Davenport et al., 2002 and Clarysse et al., 2005), the case of Massachusetts Institute of Technology (MIT) is the reference example (Roberts and Malone, 1996 and Lüthje and Franke, 2003). By encouraging faculty members to pursue private ventures outside the research lab, Bank Boston Economics Department, 1997 has calculated that MIT start-up companies generate 232 billion dollars worth of sales per year to the U.S. economy. University spinoffs are an important subset of start-up firms because they are an economically powerful group of high technology companies (Shane and Stuart, 2002 and Heirman and Clarysse, 2004). According to the Association of University Technology Managers (AUTM), spinoffs from American academic institutions between 1980 and 1999 have contributed 280,000 jobs to the U.S. economy. The recent plethora of studies on university spinoffs can be divided into three main categories. The earliest research regarding the topic assesses the personal characteristics of academics that appear to impact entrepreneurship. For example, Roberts (1991) found the average MIT technical entrepreneur typically exhibited a high desire for independence, a moderate need for achievement and a low need for affiliation. In a more recent exploratory study at MIT, Shane (2004a) uncovered motivational characteristics, such as (1) a desire to bring technology into practice; (2) a desire for wealth and (3) a desire for independence, as key ‘pull’ and ‘push’ factors impacting academic spinoff behavior. Furthermore, Zucker et al. (1998) found scientific ‘stars’ collaborating with firms had substantially higher citation rates than pure academic stars. The second strand of spinoff literature assesses the influence of universities’ policies, procedures and practices on commercialization. Some studies found that the perceived responsiveness of university policy may affect whether academics attempt to exploit intellectual property (IP) within or outside the perimeters of the university (Feldman et al., 2002 and Degroof and Roberts, 2004). Beyond this, Clarke (1998) in a cross-national study of five highly successful European universities identified entrepreneurial culture as a key element for successful University Industry Technology Transfer (UITT, as coined by Siegel et al. (2003)). In addition, Siegel et al. (2004) propose that in order to foster a climate of entrepreneurship within U.S. academic institutions, university administrators should focus on five organizational and managerial factors. These are reward systems for UITT, staffing practices in the technology transfer office (TTO), designing flexible university policies to facilitate university technology transfer, devoting additional resources to UITT and working to eliminate cultural and informational barriers that impede the UITT process. Debackere and Veugelers (2005) also supports this view and postulates that universities should employ (1) incentive structures to reward academic entrepreneurial endeavors; (2) decentralized operating structures to provide greater autonomy to research teams and (3) a centralized staff of experienced technology transfer personnel to manage the ‘contract’ and ‘training’ issues associated with the technology transfer process. A third strand of the spinoff literature explores environmental factors impacting academic innovations (Mowery et al., 2001). According to Shane (2004b), a significant impetus in the generation of spinouts in the U.S. was the enactment of the Bayh–Dole Act, whereby inventions were assigned to academic institutions rather than individual inventors. Beyond this, Florida and Kenney (1988) highlight the central role venture capital plays in encouraging the formation of high technology companies. Knowledge infrastructure of a region is also cited as a key factor. For example, Saxenian (1994) found that spinoff activity is more likely to occur in high technology clusters because access to critical expertise, networks and knowledge is readily available. While these studies have advanced our understanding of spinoff behavior, a number of scholars have pointed out deficiencies in the literature. First, most studies have explored the effects of individual, institutional or environmental factors on university spinoff behavior (Nicolaou and Birley, 2003). As a result, a distinct void exists with respect to the organizational factors accounting for variability in university spinoff activity. Second, the literature has been primarily atheoretical and non-cumulative in that most writers have developed conceptual models that are not empirically tested or make conclusions based on case studies (Djokovic and Souitaris, 2004). Third, while a number of studies have investigated knowledge flow effects from universities to industry (Agrawal and Henderson, 2002, Siegel et al., 2003a and Siegel et al., 2003b) and university technology transfer performance (Henderson et al., 1998, Thursby and Kemp, 2002, Siegel et al., 2003a, Siegel et al., 2003b and Chapple et al., 2005), few studies have systematically attempted to explain why some universities are more successful than others at generating technology-based spinoff companies (Shane, 2004a, Wright et al., 2004a and Lockett and Wright, 2004). This study aims to address these limitations by investigating the impact of internal characteristics on university spinoff activity. The contribution of this article is our focus on university resources and capabilities explaining variation in spinoff behavior.

Recent research underscores the importance of universities in contributing to local economic development, leading edge research, high value jobs and innovation (Etzkowitz, 2002). Unfortunately, for many institutions, efforts to make universities more entrepreneurial have not had sufficient impact. In fact, recent findings in Europe (Jones-Evans et al., 1999 and Wright et al., 2003) suggest that many universities are not experiencing a significant increase in spinoff behavior. As a consequence, many universities today are looking to improve their strategies for dealing with the vestiges of academic entrepreneurship. From an academic standpoint, the reasons why rates of spinoff activity differ among universities have motivated economists and management scientists to study this important topic of recent. However, little is still known about the relative influence of university resource endowments in spinoff behavior. Therefore, using panel data from 1980 to 2001, we address this gap by developing a theoretical and econometric model to understand why some U.S. universities are more successful than others at generating spinoff companies. This longitudal approach allowed us to resolve the endogeneity issue that otherwise plagues cross-sectional technology transfer analyses. A central finding of our research confirms the notion that each university, as a function of its history and past success, has different resource stocks available and these resource combinations are shown to be a relevant factor in explaining inter-university variation in spinoff activity. These findings support a path dependency argument that current choices of technologies, products and operation are heavily influenced, probably even constrained, by the cumulative effect of previous development (Arthur, 1989). Thus, public policy and university heads would be advised to intensify their activities to implement educational, research and resource programs to enable a culture of academic entrepreneurship to emerge within universities (Lüthje and Franke, 2003). Furthermore, the image of academic entrepreneurship as a career path for academics to pursue should be enhanced through developing incentives for academics to participate in entrepreneurial process. Our second finding relates to the impact of science and engineering faculty quality on university spinoff activity. The presence of star scientists and engineers affect university spinoff activity as they have leading-edge knowledge with critical expertise and ability to create radical innovations (Schumpeter, 1950) conducive for commercial exploitation. Consistent with the work of Powers and McDougall (2005) and DiGregorio and Shane (2003), this result highlights the critical importance of investing, recruiting and retaining top ranked science and engineering faculty. However, it is worth noting, the number of faculty and postdoctoral staff aligned to an institution is incidental to spinoff production. These findings reinforce empirical work from Van Looy et al. (2004) that highlight the mutual reinforcing nature of faculty quality and entrepreneurial activity of universities. A third finding of our study shows that the size and nature of financial resources allocated to universities influence academic entrepreneurship. First, we examined the ratio of industrial support to total research support in an attempt to capture the applied nature of research of universities and found a significant positive effect with this variable. Therefore, our result suggests that a greater proportion of industry-level funding is associated with higher levels of technology transfer. From a policy perspective, this suggests pursuing greater industry–university collaborations generate beneficial effects for technology transfer. Furthermore, our results also reveal that the size of federal science and engineering funding with a particular orientation on life science, computer science and chemistry disciplines show positive and statistically significant results. This finding supports the view those opportunities for technology commercialization and the propensity of faculty members to engage in technology transfer vary substantially across fields (Shane, 2004a and Siegel and Phan, 2005). This finding holds implications for policy makers seeking a return on investment from R&D expenditure inputs. A fourth finding of our study also provides convincing evidence that the magnitude of resources invested in TTO personnel increases spinoff activity. In each regression specification model, our findings show results significantly different from zero. Given the complex and time-intensive job of identifying, sourcing and exploiting university technologies for commercial exploitation, this finding highlights the greater the size of the TTO offices, the greater the likelihood of the university to produce spinoffs. These results are interesting because they clearly confirm the relevant role of tangible and intangible resources in accounting for university spinoff activity. In summary, these findings provide evidence that the organizational characteristics of universities play a significant role in the entrepreneurial behavior of academics. These findings suggest that in order for policy makers to encourage academic entrepreneurship a comprehensive systems approach to the identification, protection and commercialization of university intellectual property needs to be undertaken (Arrow, 1962). In particular, we argue (1) the need for the development of a commercially supportive culture to emerge within universities to enable academic entrepreneurship to flourish; (2) the need for active partnership and financial support with industry and government funding agencies; (3) the recruitment and development of science and engineering academic stars and (4) the development of a commercial infrastructure to enable the valorization of academic research to occur. However, it also worth noting that while our research has found that spinoff activity is positively related to knowledge accumulation dynamics and learning effects, a limitation of our study is that it does not identify the university levels at which learning dynamic effects operate. Therefore, studies that can augment our current research findings with more fine-grained methods (Birley and Gartner, 2002) in the form of qualitative research may provide insights into where learning effects occur and the nature and processes they go through to influence start-up activity.