Technology transfer and entrepreneurship: cross ... - Springer Link

J Technol Transf (2016) 41:1247–1259 DOI 10.1007/s10961-015-9441-8

Technology transfer and entrepreneurship: cross-national analysis David Audretsch1 • Rosa Caiazza2

Published online: 12 October 2015 Ó Springer Science+Business Media New York 2015

Abstract The purpose of this article is to improve our understanding of the links between technology transfer, entrepreneurship and the institutional setting in explaining both the competitiveness of firms and the economic performance of places, albeit a city, region, state or country. We accomplish this objective by presenting a framework for the crossnational analysis of different regional contexts. Finally, we introduce the papers included in this special issue in the International journal of Technology Transfer on ‘Technology Transfer and Entrepreneurship: Cross-National Analysis’. Keywords

Technology transfer Innovation Entrepreneurship Cross-national analysis

JEL Classification C4 O10 L26 M13

1 Introduction Advances in the state of knowledge have been responsible for much of the economic development historically. New firms’ competitiveness and regional development (Caiazza et al. 2015; Acs et al. 2002; Porter 1996). As a public good, knowledge is non-exhaustive and non-excludable (Arrow 1962). This implies that the stock of existing knowledge and the newly created knowledge can be intentionally or un-intentionally transferred (i.e. spillover) to all economic agents. However, it is neither automatic nor a priori unknown if new knowledge can be transferred successfully into a viable innovation. This implies that an entrepreneur has to develop a vision on a possible economic use of knowledge, evaluate that the its potential returns are superior to risks and engage into starting up a new venture to realize his vision. This process of exploitation of new knowledge that otherwise would

& Rosa Caiazza [email protected] 1

Indiana University, 1315 E. 10th Street, Suite 201, Bloomington, IN 47405, USA

2

Parthenope University, 13, Generale Parisi Street, Suite 415, 80132 Naples, Italy

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D. Audretsch, R. Caiazza

remain unexplored has been characterized as the knowledge spillover theory of entrepreneurship (KBST) (Ghio et al. 2015; Acs et al. 2013; Audretsch and Keilbach 2007; Audretsch and Lehmann 2006). The process of new knowledge creation, transfer and exploitation through the start of new business depend on both actions of different organizations and relations among them (Agarwal et al. 2007; Acs et al. 2002). The way actors are linked and interact tends to depend on nation-specific formal and informal institutions. Consequently, the influence of institutional factors on knowledge creation, technology transfer and entrepreneurship has always attracted the interest of managers and policy-makers. Leading researchers to investigate cross-national differences across different local and regional contexts. The purpose of this paper is to provide an introduction to the special issue in the International journal of Technology Transfer on Technology Transfer and Entrepreneurship: Cross-National Analysis. In particular, the paper introduces a new framework for analyzing the interface of technology transfer with entrepreneurship and the institutional context in explaining the economic performance for both individual firms as well as places, ranging from cities to regions, states and entire countries. This framework provides a lens facilitating the introduction and contribution of each of the individual papers included in this special issue. The remainder of this paper is organized as follows. Section 2 introduces the topic of knowledge creation and technology transfer. Section 3 introduces the role of knowledge in entrepreneurship. Section 4 provides the framework linking the cross-country institutional context to economic performance. In Sect. 5, we present and explain the contribution of each of the papers included in our special issue.

2 Technology transfer Scholars have historically evidenced the importance of knowledge as constituting the driving force underlying the competitive advantage of firms and the economic performance of places, ranging from cities to regions, states and entire countries (Grant 1996; Liebeskind 1996; Barney 1991). Indeed, firms with more knowledge systematically outperform those with less and regions that develop and manage effectively their knowledge assets perform better. The most important source of new knowledge is considered to be research and development (R&D). The scholarly literature provides systematic and compelling evidence confirming a positive relation between knowledge inputs and innovative outputs. This link is stronger as the unit of observation becomes increasingly aggregated. For example, at the unit of observation of countries, the relationship between R&D and patents is very strong. By contrast, the link between knowledge inputs and innovative output becomes weakly positive in studies that uses firms as unit of observation. This is explained from the fact that formal R&D is concentrated among the largest corporations (Acs and Audretsch 1988), while small firms account for a disproportional share of innovations given their low R&D expenditures. Firms with little or no R&D get the knowledge inputs from other firms or public research institutions. Not all knowledge created by public research institutions and private organizations investing in basic and applied research activity for scientific and technological intents is fully appropriated within the organizational boundaries (Moran and Ghoshal 1999). Organizations often falter in transforming their scientific or industrial knowledge into economic or commercialized knowledge (Arrow 1962) and suffer from an

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abundance of underexploited knowledge (Agarwal et al. 2007). Thus, part of this knowledge is intentionally or not-intentionally transferred from organizations conducting research to other ones (Harris 2001). Szulanski (1996, 2003) defines as intentional knowledge transfers the process of dyadic exchanges of knowledge between the creator and the receiver. Thus, incumbent organizations that are limited in their ability to produce new knowledge through internal R&D investments (Hagedoorn 1993) can receive and absorb external knowledge through technology transfer structure (technology transfer offices, science and technology parks and incubators) and formal arrangements (alliances, joint ventures, mergers and acquisitions, and corporate venture capital investments) (Schildt et al. 2005). The effectiveness of an intentional knowledge transfer process depends on disposition and the ability of the creator and incumbent, on the strength of the tie between them, and on the characteristics what is actually being created (Szulanski 2003). Knowledge may not be transferred easily from one actor to another, but instead requires a certain absorptive capacity on the part of the incumbent in order to absorb and use it for commercialization and ultimately innovative activity. This implies that there are some barriers to knowledge transfer through patents, licenses and research joint venture that technology transfers offices, science and technology parks and incubators try to overcome (Link and Siegel 2005). However, given its public good characteristic of being non-rival and non-excludable (Arrow 1962), knowledge has a high propensity to spill over for commercialization by third-party firms which do not pay for the full cost of accessing and implementing those ideas (Gatti et al. 2015; Griliches 1992; Caiazza et al. 2014a, b). Knowledge can, thus, spill over the source that produces it to new organizations without any intentional activity through scientific publication in scholarly journals, human capital embodied in peoples, employee mobility and interpersonal contacts (Acs et al. 2009; Audretsch and Keilbach 2008; Almeida and Kogut 1999; Arrow 1996). In this case, incumbent can absorb knowledge spillover from other organizations and combine it with their internal one for realizing an economic use of knowledge aimed to introduce innovations on the market (Coe and Helpman 1995; Jaffe 1986; Spence 1984; Scherer 1982). Thus, both intentionally and not intentionally, knowledge transfer affects incumbent’s commitment to introduce on the market and commercialize both technological and non-technological innovations (Lumpkin and Dess 1996; Covin and Slevin 1991) (Fig. 1). This intricate relationship between investments in research, technology transfers and innovations commercialization can influence the locational choice of firms (Caiazza 2015; Sorenson and Audia 2000; Vagnani 2012; Sorenson and Baum 2003). Many studies have indicated that companies are attracted to the close proximity of external sources of

Transfer • Knowledge Creation

• Technolgy

• Innovation Commercialization

Fig. 1 Technology transfer

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knowledge inputs (i.e. universities or public research institutions) for several reasons (Audretsch et al. 2005; Audretsch and Stephan 1996). First, firms run their business more efficiently and, second, they can use knowledge spillover as factor for enhancing their innovative activities. Both effects tend to increase firms’ productivity (Acs et al. 1994; Caiazza et al. 2014a). This implies that production and transfer of new knowledge has a predominant tendency to cluster spatially (Audretsch 2005; Canie¨ls 2000). Strong empirical evidence suggesting that knowledge flows (i.e. measured by patent citations) are bounded within a relatively narrow geographical range has been provided for the US (Varga 2000; Anselin et al. 2000; Almeida and Kogut 1999; Acs et al. 1991; Jaffe 1989; Caiazza and Audretsch 2013), Italy (Caiazza 2013; Capello 2001; Audretsch and Vivarelli 1996), Germany (Fritsch 2001), Europe (Caiazza 2013; Maurseth and Verspagen 1998). Consequently, economic growth of some regions of US (i.e. Silicon Valley), Europe (i.e. Cambridge) and Asia (i.e. Bangalore) is directly related to localized inter-industry knowledge flows (Caiazza and Volpe 2014; Dorfman 1983).

3 Entrepreneurship New knowledge leads to opportunities that agents exploit commercially. Such opportunities are a function of the distribution of knowledge within and between societies. However, the ability to transform new knowledge into economic knowledge (Arrow 1962) requires a set of skills, aptitudes, insights and circumstances that is neither uniformly nor widely distributed in a society. Consequently, entry and entrepreneurship are important links between knowledge creation and the commercialization of such knowledge (Audretsch et al. 2008). Entrepreneurship is a process of extracting profits from new, unique and valuable combinations of knowledge in an uncertain and ambiguous environment through creation of new enterprises (Amit et al. 1993; Low and MacMillan 1988). Thus, according to Audretsch (1995) as entrepreneurship is a process of change, entrepreneurs are agents of change. Specifically, new knowledge, created and transferred intentionally or un-intentionally, plays a relevant role in direction of entrepreneurial new venture formation for several agents of change. It creates an abundance of entrepreneurial opportunities for both existing organization that invest in research activity (i.e. public research institutions’ spinoffs) (Caiazza and Audretsch 2013; Lockett et al. 2005; O’Shea et al. 2005; Audretsch and

Entreprenership

Fig. 2 Entrepreneurship

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Knowledge trasferred

Incumbent

Knowledge spillover

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Stephan 1996; Louis et al. 2001) and incumbents that absorb knowledge through intentionally transfer mechanisms (i.e. license or patent) for expanding their set of potential opportunities to create a start-ups (i.e. private firms’ spin-outs) (Klepper 2007; Klepper and Sleeper 2005; Burton et al. 2002; Shane and Stuart 2002). However, new knowledge does not affect only creators and incumbents’ entrepreneurial activity. It also affects activity of new entrants who perceiving unexploited opportunities created by other organizations’ knowledge choose to start-up a new business. Thus, knowledge not completely commercialized by creators and incumbents offers potential entrepreneurial opportunities for entrants that aim to start new business in order to exploit knowledge that otherwise would not be commercialized (Gartner 1988; Caiazza 2014b). If entrants guess that the potential benefits of converting knowledge in economic activities overcome possible risks, they will engage into an entrepreneurial activity aimed to start-up a new venture (Fig. 2). The act of founding a new venture to commercialize knowledge generated in other organizations serves as a conduit for the spillover of knowledge (Audretsch and Keilbach 2007). This entrepreneurial activity involves the exploration and exploitation of new opportunities created but not appropriated by other firms (Schumpeter 1934), and the absorption of knowledge spillovers and creation of new organizations (Thompson and FoxKean 2005; Acs et al. 2004; Shane 2001; Gartner 1988). This complex set of activities of entrants based on knowledge generated by other organizations has been defined as knowledge spillover strategic entrepreneurship (Agarwal et al. 2007). Entrepreneurship is, thus, an endogenous response to opportunities generated by investments in new knowledge made by other organizations that are unable to completely and exhaustively commercialize that knowledge. The process through which an entrepreneur develops a vision identifying opportunities that are based on the available knowledge has been denoted as KBST (Acs et al. 2013; Audretsch and Keilbach 2007; Audretsch and Lehmann 2006). According to this theory, knowledge investments by existing organizations (i.e. firm or university research laboratory) create an abundance of entrepreneurial opportunities not fully developed by creators and incumbents as a result of the uncertainty inherent in knowledge (Acs and Armington 2006; Acs et al. 2004). These opportunities lead to a process of creative construction where entrants benefit from their entrepreneurial activities accryubg from knowledge spillovers created by other organizations that in turn benefit from the reverse flows from those entrants. This process, called the Cycle of Creative Construction connects technology transfer, new venture origin and regional growth (Agarwal et al. 2007). Several studies have provided systematic evidence suggesting that the process of knowledge creation offers a greater number of entrepreneurial opportunities that increase the rate of entrepreneurship that, in turn, positively affects economic growth. Researchers have provided empirical evidence suggesting that OECD countries exhibiting higher increases in entrepreneurship also have experienced greater rates of growth (Thurik 1999; Carree and Thurik 1999). Increased entrepreneurial activity has resulted in an environment of sustainable economic growth in North America, Europe and Japan (Caiazza 2014a, b, c; Callejoń and Segarra 1999). It plays a relevant role even in developed countries. For instance, Bangalore has become ‘‘India’s Silicon Valley’’ by promoting high-tech entrepreneurship and achieving one of the highest growth rates of per-capita income in India. Cities like Hyderabad and Gurgaon have adopted strategies to encourage entrepreneurship and are experiencing high growth rates (Audretsch 2007; Caiazza 2014c).

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4 Institutional setting Since knowledge creators, incumbents and entrants are all embedded in regional contexts, the institutional setting affects both actors and their interactions (Acs et al. 2004). Specifically, institutions define the alternative courses of action that are open to firms, dictate the potential pay-offs from different activities, legitimate organizational forms and technologies and assign rights to use resources and capture residual profits from economic activities (Van de Ven 1993; North 1990). Consequently, the way in which different actors create, transfer and commercialize knowledge tends to be affected from region-specific formal and informal institutions (Acs et al. 2004). On one hand, formal institutions (such as regulatory frameworks, industrial structure, the presence of venture capital, business angels and incubators) are elements that have all been put forward as essential ingredients for creating, transferring and enhancing knowledge in start-ups (Acs and Audretsch 1989; Blanchflower 2000; Thornton 1999; Blanchflower and Oswald 1998; Storey and Jones 1987). On the other hand, informal institutions (such as rules, conventions, norms, religious, moral and culture factors) nurture public and private capabilities, promote entrepreneurial orientation of people engender, homogenize and reinforce individual action creating and disseminating new knowledge and channeling it to entrepreneurial uses (Acs et al. 2014). Thus, according to KBST, institutions can support the context with more knowledge that in turn can generate more entrepreneurial opportunities that lead to more start-ups (Audretsch and Lehmann 2005). Institutional contexts rich in knowledge should generate more entrepreneurship, reflecting more extensive entrepreneurial opportunities. Thus, supported from institutional factors, entrepreneurship becomes a channel able to transform knowledge created, transferred and spilled over sources in economic growth. As a result, economic growth at both the level of the firm as well as the place (ranging from city to region and country) is influenced by the institutional setting able to support high technology transfer and entrepreneurship. Institutional support has influenced both the production and commercialization of new knowledge in many US, European and Asian regions, such as the Cambridge area in the UK, Montpellier area in France, Bangalore area in India, Beijing in China, San Francisco Bay Area and Silicon Valley in California (Caiazza and Audretsch 2015; Audretsch and Lehmann 2006; Gilbert et al. 2008). However, what contributes to the success in some reasons may not apply in a different regional and institutional context. Institutional factors can help to explain cross-national differences in regional economic performance (Lehrer and Asakawa 2004) (Fig. 3). Combining the formal and informal institutional aspects, it is possible to distinguish between low and high-growth regions. Low-growth regions offer low levels of institutional

Technology transfer High

Institutional support High Low

Low Entrepreneurship Low Fig. 3 Institutional setting

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support to knowledge transfer and commercialization. Because of high knowledge filters, in these regions investments in research are less successful in being transformed into commercialization (i.e. patents) and entrepreneurship (i.e. spin-off) (Acs et al. 2003; Caiazza and Volpe 2015b). The greater is the knowledge filter, the more pronounced is the gap between new knowledge and economic knowledge or commercialized knowledge. High-growth regions offer effective levels of formal institutions (such as technology licensing offices, business angels, venture capital, incubator firms) and informal supports (such as risk oriented culture, social norms, lows for property protection, regulation of entry) that positively influence knowledge creation, technology transfer and entrepreneurship (Caiazza and Volpe 2015a, b; Levie and Autio 2011; Djankov et al. 2002; Stephan and Uhlaner 2010). Because of the low filter, knowledge can be easily transferred intentionally or not intentionally and transformed into entrepreneurial activity. Consequently, institutions in high-growth regions explicitly influence actors’ ability to discover and exploit technological opportunities and their capability to create new firms. As a result, growth at more macro levels can be understood only by relating it to the more micro-level activity (Caiazza et al. 2014a). Economic growth is attributable to deliberate institutional support to incumbent organizations in creating and transferring knowledge and to entrepreneurs in using knowledge for creating new firms (Caiazza and Volpe 2014). However, entrepreneurship creates not just growth for new ventures that are launched, but also for the entire region. Institutional support of region in which actors operate is crucial for the entrepreneurial activity of firms that in turn influence the region growth. Thus, policy-makers have to implement a multilevel set of policies aimed to create e favorable institutional setting, facilitate knowledge creation, technology transfer and entrepreneurship through start-ups. This eclectic perspective links in a virtuous circle both the economic growth of a region to firm competitiveness but also to institutional support, technology transfer and entrepreneurship (Agarwal et al. 2007). Consequently, the fact that different regions may grow at different rates depends both on their different levels of investment in knowledge and on their different institutional support to knowledge transfer and exploitation in entrepreneurial activity (Fig. 4).

5 Papers in the special issue Starting from the extant literature, this special issue has the goal to provide new insights and understanding about technology transfer, entrepreneurship and the institutional setting within a cross-national context. It particular, taken together, the set of papers included in

Fig. 4 Regions and firms virtuous circle

Regions' economic growth

Firms' competiveness

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this special issue enhances our understanding of the theoretical, managerial and policy implications involved in technology transfer and entrepreneurship on competitiveness of firms and economic performance of regions. The papers included in this special issue are heterogeneous but generally build on the extant literature. The paper by Lafuente, Szerb and Acs on ‘‘Country level efficiency and National Systems of Entrepreneurship: A Data Envelopment Analysis approach’’ provides an explicit empirical test of the KBST. Using a comprehensive database for 63 countries the study tests how countries capitalize on their available entrepreneurial resources. The study finds that innovation-driven economies make a more efficient use of their resources, and that the accumulation of market potential by existing incumbent businesses explains country-level inefficiency. It also suggests that public policies promoting economic growth should consider national systems of entrepreneurship as a critical priority, so that entrepreneurs can effectively allocate resources in the economic. The paper by Lehmann and Menter on ‘‘University–Industry Collaboration and Regional Wealth’’ builds on previous studies by analyzing why and how universities shape regional wealth and competitiveness to examine differences in the causal relationship between university-induced knowledge spillovers and regional wealth. The study builds upon the knowledge spillover theory (KBST) to examine the causality and direction of knowledge spillover flows. It empirically tests that university directly shapes regional wealth, that universities as the source of knowledge spillovers are shaped by regional wealth and that both, regional wealth and university spillovers follow and co-evolutionary path and are reciprocal. Its findings have implications for policy makers in that education policy and regional cluster policy are rather complementary than substitutes. The paper by Braunerhjelm, Ding and Thulin on ‘‘Labour as a knowledge carrier—How increased mobility influences entrepreneurship,’’ is based on the spillover theory of entrepreneurship (KBST) and provides compelling empirical evidence suggesting that entrepreneurship is positively associated with the knowledge endowment level. The study’s dependent variable is an individual who has remained in a region throughout the time period considered. Controlling for a number of other variables, inter-regional labour inflows and intra-regional mobility levels are shown to exert a strong positive effect on entrepreneurship. This contrasts with inter-regional outflows, which are shown to negatively affect entrepreneurial entry. In the same vein, the paper by Blume-Kohout on ‘‘Why are some immigrants more entrepreneurial than others?’’ compares the contribution to innovation and high-growth new firm creation in the United States from US and foreign-born scientists. The study identifies factors that contribute to the entrepreneurship rates of foreign-born workers exceeding that of native US citizens. The paper provides compelling empirical evidence suggesting that although rates of business ownership are highest among immigrants who came to the US as adults having earned their highest degrees abroad and among temporary residents from E-2 Treaty countries, STEM business ownership is most common among immigrants who came to the US to pursue higher education. Belitski and Desai, in ‘‘Creativity spillover of entrepreneurship: Evidence from European cities,’’ examine the black box of creativity, entrepreneurship and economic development by asking about the mechanisms through which creativity can influence economic development in cities. The study proposes that, like the knowledge-spillover theory of entrepreneurship (KBST), creativity spillovers occur and can be slowed by a creativity filter. It examines how creativity and entrepreneurship interact to influence urban economic development. Using a dataset of 187 cities in 15 European countries, it identifies that

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interaction effects with entrepreneurship are important when considering the role of creativity in economic development. The paper by Munari Rasmussen Toschi and Villani on ‘‘Determinants of the university technology transfer policy-mix: a cross-national analysis of gap-funding instruments’’ offers a novel cross-national investigation of the policy mix emphasizing the level of centralization and decentralization of policy instruments. The paper maps and analyzes two specific types of public instruments aimed at addressing the so-called funding gap in TT; proof of concept programs (POCs) and university-oriented seed funds (USFs). Based on a survey across 21 European countries it finds that such instruments are widely used, but are organized differently depending on the level of implementation of TT practices in the country and the specific type of instrument considered. More precisely, it finds a U-shaped relationship between the use of centralized gap funding instruments and the country’s implementation of TT practices. The paper by Caiazza on ‘‘A cross-national analysis of policies affecting innovation diffusion’’ aims to identify barriers that affect innovation diffusions and clarify the role of public policy in promoting it. The study explores a topic which has been largely neglected in the literature. On the one hand, it provides a conceptual framework to analyze public policies; on the other hand, it proposes an overview of policies that can be implemented by policy-makers to overcome the most stringent barriers impeding the diffusion of a new technology. Lawton Smith, Bagchi-Sen, and Edmunds, in ‘‘Innovation capacity in the healthcare sector and historical anchors: examples from the UK, Switzerland and the US,’’ focus on innovation from the biotech—pharma perspective to see whether or not this leads to a sustainable future for the regions where there are clusters of firms in this sector. The paper examines data from an important European Union study of innovation in the Healthcare sector for the UK and Switzerland. The analytical framework comprises three elements: innovation systems and national and regional economic development theories are the first two, followed by approaches which consider organisational or institutional activity. The paper by Mendonça and Grimpe on ‘‘Skills and regional entrepreneurship capital formation: A comparison between Germany and Portugal,’’ focuses on the skill base of a region in terms of its endowment with human capital and the composition. The paper analyzes the context in which entrepreneurship capital formation takes place by focusing on differences in the institutional infrastructures for entrepreneurship in two European countries, Germany and Portugal. Based on harmonized datasets, the results of the paper suggest that there are important differences between the countries. Specifically, they suggest that both the specialization and diversity theories hold, and that the effects are thus contingent on regional specific factors. Davey, Rossano, van der Sijde, in their paper on ‘‘Does context matter in academic entrepreneurship? The role of barriers and drivers in the regional and national context,’’ focus on two environmental settings, European regions and countries, seeking to understand if it is the hurdle (barrier) or (and/or) tail-wind (drivers) that most impacts academic entrepreneurship and how does the regional or national context influence this. The results show that there is a significant difference in the university–business cooperation barriers and drivers that effect academic entrepreneurship in the European regions. Furthermore, different barriers and drivers were found to significantly affect the four lead countries with barriers and drivers being able to provide a good explanation of the extent of academic entrepreneurship in the UK and Germany, and a limited explanation of entrepreneurial activity by Spanish and Polish academics. Overall the article contributes to the literature on

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resource-based theory and also the understanding of factors influencing European academic entrepreneurship. The paper by Karlsson and Tavassoli on ‘‘Firms’ Innovation Strategies Explained and Analyzed analyzes various innovation strategies of firms,’’ traces the innovative behavior of Sweden firms over a 10-year period. The paper distinguishes between 16 innovation strategies, which correspond to four types of innovations plus various combinations of these four types. First, the paper finds that firms are not homogenous in choosing innovation strategies, instead, they have a wide range of preferences when it comes to innovation strategy and some of the innovation strategies are ‘‘commonly’’ used among firms. Second, the paper founds that firms also persist to have such a diverse innovation strategy preferences. Finally, it explains the determinant of each and every innovation strategies. Slavtchev and Go¨ktepe-Hulteń, in their paper on ‘‘Support for Public Research Spinoffs by the Parent Organizations and the Speed of Commercialization,’’ analyze whether support by the parent organization in the early stage speeds up the process of commercialization and facilitates spin-offs from public research organizations. The main findings of the paper suggest that support in the early stage by the parent organization can speed up commercialization. Moreover, the paper identifies two distinct channels through which support by the parent organization can enable spin-offs to generate first revenues sooner.

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