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Explore individual, institutional, and spatial factors influencing academic entrepreneurship in the UK across all disciplines. Investigate age, gender, research type, institutional culture, and location effects.
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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.
