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Personal, institutional and spatial determinants of academic entrepreneurship in the UK. Maria Abreu (University of Groningen) Vadim Grinevich (University of Cambridge). Background. Growing policy interest in the role of universities for regional economic development.
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Personal, institutional and spatial determinants of academic entrepreneurship in the UK Maria Abreu (University of Groningen) VadimGrinevich (University of Cambridge)
Background • Growing policy interest in the role of universities for regional economic development. • Universities are important contributors to economic growth, as sources of knowledge and human capital. • They are key components of the innovation system (Lundvall, 1992; Nelson, 1993; Cooke et al., 1997). • The “entrepreneurial university” (Etzkowitz et al., 2000; Etzkowitz, 2003). • Universities have moved beyond their traditional missions of research and education. • In the UK: third stream funding.
Background • The literature has focused on a “narrow” view of the academic entrepreneur: • Patenting, licensing and spin-outs. • Relatively easy to measure and analyse. • The vast majority of studies focus on engineering, science and medicine. • Entrepreneurial activities in the arts, humanities and social sciences not well understood. • A focus on institutional rather than individual factors, although this is changing with micro-data availability.
Aims • Our unit of analysis is the individual academic entrepreneur who is: • Engaged through a variety of formal and informal channels. • Not only engaged with industry, but also with wider society. • From a variety of disciplines, including the arts, humanities and social sciences. • We argue that the “academic entrepreneur” is someone who generates value for his/her research outside academia. • He/she capitalises on it either professionally or commercially.
Aims • Our aim is to understand what determines academic entrepreneurship: • Individual characteristics: age, gender and type of research. • Institutional characteristics: culture, norms and facilities provided. • Spatial factors: location and access to networks. • We use a new data set that covers all higher education institutions and all disciplines (in the UK). • Previous work has focused on a small number of institutions, and/or a small number of disciplines. • We include a wide range of activities including informal advice and community-based work.
Individual characteristics • Academic entrepreneurship increases with age: • Younger academics need to publish to establish their reputation; older academics can cash-in and commercialise. • However, cohort effect whereby younger generations are more familiar with these activities, and are more receptive to them. • Empirical evidence is mixed, with positive, negative, non-linear and insignificant results. • Female academics are less likely to commercialise: • Less likely to have industry and business contacts. • More ambivalent about ethics and benefits of third mission (Murray and Graham, 2007). • Difficulties in raising finance from venture capitalists.
Individual characteristics • Extent of academic entrepreneurship varies by subject: • In some cases (e.g., the life sciences) applications follow directly from research, not so in others (e.g., theoretical physics). • In some subjects (e.g., computer sciences, arts, humanities) outputs are less likely to be patented or licensed. • Basic, user-inspired and applied research (Stokes, 1997). • Previous business experience encourages future entrepreneurial behaviour. • Research and/or teaching roles have a mixed effect: • Research-only positions lead to more outputs that can be commercialised. • But there may be a greater pressure to publish, so less time.
Institutional characteristics • Institutional factors occur at the department and university level. • The literature has mostly focused on the role of the TTO. • Incentives such as higher royalties raise the rate of patenting and licensing: • Non-pecuniary incentives such as credits towards promotion and tenure are also important (Link et al., 2007). • If incentives are low, academics may use informal channels in exchange for equipment, student placements etc. • Support facilities have a positive effect , but only if they are flexible and not bureaucratic.
Spatial characteristics • Personal relationships are key to developing collaborative partnerships. • Close geographical location facilitates knowledge exchange and the development of new ideas (Jaffe, 1989; Feldman, 1994 etc.). • Relevance of the quality of the institution for the geography of collaborations is mixed: • Businesses may look for the ideal academic partner, irrespective of location (unless the research is confidential or urgent). • Top universities attract greater interest from local businesses. • Academics working in remote locations may struggle to maintain business and industry contacts.
Data • The analysis is based on a UK-wide survey of academics conducted as part of a wider ESRC project (Abreu et al., 2009). • The sampling frame included all academics working in teaching and/or research at all higher education institutions in the UK. • All disciplines and job categories were included. • The total sample is 22,556 individuals. • We complement this using institutional data from the “Higher Education – Business and Community Interaction Survey 2007-08”. • Available from the Higher Education Funding Council for England (HEFCE). • Includes questions on third stream activities, funding and facilities provided by the institution.
Methods • We run regressions to analyse the factors that affect: • Formal activities (patenting, licensing, spin-outs), collaborative research activities, and community-based activities. • Activities with the private, public and third sectors. • These models were estimated using probit regressions. • We also investigate the determinants of the variety and distance of interactions: • The number of activities an individual is involved in (following D’Este and Patel, 2007). • The greatest geography at which interactions take place (out of 1=local, 2=regional, 3=national and 4=overseas). • These models were estimated using ordered probit regressions.
Conclusions • Our results are generally in line with the findings of the literature, but some are surprising. • Contrary to conventional wisdom, we find that academics in the arts and social sciences are very much involved with external organisations. • The level for the humanities is significantly below the average for all subjects, except for community-based activities. • Individual characteristics are more important than institutional characteristics. • Access to commercialisation facilities is beneficial, but inflexible bureaucracy is not.
