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Universities in National Innovation Systems

Universities in National Innovation Systems. David C. Mowery Haas School of Business, UC Berkeley. Outline. Universities and industrial innovation in knowledge-based economies. Cross-national indicators on the structure of national higher education systems.

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Universities in National Innovation Systems

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  1. Universities in National Innovation Systems David C. Mowery Haas School of Business, UC Berkeley

  2. Outline • Universities and industrial innovation in knowledge-based economies. • Cross-national indicators on the structure of national higher education systems. • Evidence from U.S. surveys on the contributions of university research to innovation. • Case study: The Bayh-Dole Act of 1980. • Is the US system a “role model”? • “Emulation” of Bayh-Dole elsewhere in the OECD. • Managing University-Industry linkages.

  3. Universities within national innovation systems. • Universities are among the oldest institutions in most European economies. • They are also among the most nationally idiosyncratic throughout the industrial economies. • Conceptual frameworks for understanding the role of universities in industrial innovation: • “Pasteur’s Quadrant”: basic research that has direct industrial applications. • The “republic of science” and contrasting norms of disclosure and dissemination of research in industry and academia.

  4. “Pasteur’s quadrant” (PQ) and academic research • Stokes (1997) proposed that academic basic research included 2 broad classes: • Fundamental knowledge about the universe (“Bohr’s quadrant”). • Knowledge flowing from basic research with direct applications (“Pasteur’s quadrant”). • 3d quadrant, “Edison”: technological research for application. • Recent academic research, esp. in biomedical fields, frequently yield knowledge in “Pasteur’s quadrant” (as did Pasteur’s own work). • Gene-splicing a classic example. • An input to further basic research and to innovation.

  5. Different rewards & incentives in industrial and academic research => potential conflict in PQ • Academia: Priority and disclosure are critical to professional success. • 1st to publish reaps the majority of the “returns.” • Publication & disclosure of methods are essential. • Industry: Returns to innovation operate very differently. • Disclosure may be detrimental to innovative success. • Priority in invention may not be essential to commercial success. • Additional investment, innovation often required for commercial success.

  6. The rise of the modern research university • European universities originally (11th century) were established as institutions for training clerics. • Although affiliated with the church, universities were autonomous entities. • Through the early 19th century, universities continued to focus on teaching of future clerics in Europe, US. • A new model emerges in mid-19th German states: the state-funded research university. • Emulated rapidly in US, elsewhere in continental Europe.

  7. How do universities influence innovation? • Multiple roles: • Source of trained S&Es. • Combination of research & training => an important mechanism for knowledge & technology transfer through flow of graduates to industry. • Source of peer-reviewed knowledge placed in the global public domain. • Magnet for S&E immigrants from diaspora & elsewhere. • In some cases, universities support regional high-technology agglomerations. • Multiplicity of roles => varied channels through which universities affect industrial innovation.

  8. Universities and high-tech clusters • We observe numerous clusters with universities, but numerous universities without clusters. • MIT & Stanford appear important to regional clusters, but “causal” evidence is sketchy. • Klepper argues that early Silicon Valley resembles Detroit & auto industry rather than relying on academic institutions. • Fairchild, IBM in Silicon Valley were very important sources of spinoffs that (may have) benefited from academic links. Compare with Stanford role? • Carnegie-Mellon (Pittsburgh), CWRU (Cleveland), Johns Hopkins (Baltimore) have spawned less powerful clusters. • Universities’ role in sustaining clusters may differ from role in catalyzing their creation. • Regional firms’ role also may differ over time.

  9. Comparing higher ed. systems • Most systems combine education & training in varying degrees and occupy positions of varying prominence in these functions within different national economies. • How do national systems of higher education differ in the following dimensions? • Scale • Contributions to training of scientists & engineers. • Performance of R&D within the national economy. • Mix of public, industrial funds in university research support. • Centralized vs. decentralized national structure of administration.

  10. Indicators of university-industry linkages within the OECD • Few internationally comparable measures of collaboration, technology transfer: • Patent counts do not adjust for quality of patents, incentives of university administrators to seek patents. • No internationally comparable university licensing data. • US widely cited as a model of close collaboration, but (funding-based) indicators do not rank US at the top of the OECD: • University share of national R&D performance. • Industry-funded share of university R&D performance (Germany 1st, Canada 2nd), which in US is lower in 2008 than in 1953. • Crespi et al. (2006): majority of faculty patents in UK, France, Italy, Germany, Netherlands, Spain are not assigned to universities. • Context and structure supporting linkages are more complex than indicators can convey. • OECD report (2002): qualitative evidence => labor mobility between US higher education and industry is greater than in other national higher ed. systems. • At least some important influences on U-I links are outside of university boundaries. • Labor markets for scientists and engineers. • Venture capital. • University structure creates (or fails to create) incentives for collaboration between university and industry researchers.

  11. Channels of interaction between academic research and industrial innovation • Multiple channels of interaction (training; publishing; faculty consulting; new-firm formation; patents & licenses). • The interaction is bidirectional: industrial research/innovation affects academic research, as well as the reverse. • Schockley Semiconductor and Stanford. • Importance of different channels varies among fields of research. • Outside of pharmaceuticals, US industrial R&D managers in large firms indicate that patents are relatively unimportant channels of influence.

  12. Little work on relationship among channels of interaction • How important are different channels to different university missions? • Little work on role of licensing in “spinoff” formation, survival. • Most work on patenting & publishing concludes that patenters also are publishers. • Gender and patenting: Senior female faculty publish comparably, patent far less than male faculty of similar rank and productivity in US universities. • Ding and Choi (2009): Younger US faculty in biomedical research are more likely to pursue new-firm entrepreneurship at an early point in their career. • We know little about relative importance of these, other channels of interaction in different national university, innovation systems.

  13. Case Study: The u.s. Bayh-dole act of 1980 and policy emulation

  14. Policy “emulation” and university-industry links in OECD economies • “Systems of innovation” literature rarely considers interaction among different national systems. • “evolutionary”: cross-border flows of capital, technology => some requirement for adaptation, reflecting competitive pressure. • “purposive”: policymakers “learn” from one another’s policies. • “Purposive” interaction => conscious “emulation.” • OECD members’ evolving policies toward university-industry interaction an example of “purposive” interaction, emulation.

  15. International “emulation” in technology policy • Examples: • R&D collaboration (EU, US emulated Japanese collaboration in the 1980s; Japan now emulates SEMATECH in ASET, SELETE). • Deregulation. • Intellectual property rights. • Venture capital. • Characteristics: • Learning is selective. Implementation of the imitative/emulative response further muddles the fidelity of the “reflection.” • International emulation of Bayh-Dole shares these characteristics.

  16. The Bayh-Dole Act of 1980 • Act sought to encourage commercial development of federally funded inventions in university and government labs. • Rationalized and simplified federal policy toward assignment of patent rights, licensing. • Political statement as important as statutory provisions. • Bayh-Dole did not legalize anything previously prohibited. It replaced a complex web of Institutional Patent Agreements (IPAs) between individual federal agencies and universities. • Act delegated management to research performers and reduced agency oversight of licensing of federally funded research results.

  17. Other developments during the 1970s and 1980s influenced US universities. • Diamond v. Chakrabarty: Life forms are deemed patentable by the US Supreme Court in 1980. • Creation of the Court of Appeals for the Federal Circuit in 1982. The Court becomes a strong “pro-patentholder” judicial body. • Other federal actions strengthen intellectual property protection in domestic, international economy during the 1980s. • “War on Cancer” spurs research in molecular biology.

  18. International “emulation” of the Bayh-Dole Act. • Discussions or policy changes affecting “technology transfer” activities of national universities in Japan; Italy; Germany; Denmark; France; Canada, and other nations. • Bayh-Dole widely cited as a model. • Many policy initiatives focus on patenting of university inventions. • Transfer ownership of patent rights from faculty to university (Denmark; Germany). • Transfer ownership of patent rights from university to individual faculty (Italy). • Some initiatives (Sweden, Japan) include authority or public financial support for creation of “technology transfer offices.” • Others (France) liberalize leave-of-absence policies for gov’t and university researchers to start new firms.

  19. But several issues have not been addressed • How important has the Bayh-Dole Act been in supporting university-industry collaboration and technology transfer in the United States? • Would growth in these activities have occurred without the Bayh-Dole Act? • Will emulation of the Bayh-Dole Act accelerate collaboration and technology transfer in other nations’ university systems? • What side effects for academic research?

  20. Structural characteristics of US higher education created incentives for technology transfer before 1980 • Large scale of national “system.” • No centralized (e.g.,federal) control of administrative policies. • Heterogeneous institutional structure (public; private; secular; religious; large; small) and quality. • Dependence by many institutions on “local” sources of financial & political support. • This dependence motivated research with “local” benefits, search for links with “local” industry. • Inter-institutional competition for resources, prestige, faculty. • Aghion et al. (2009), Katz & Goldin (2008): Institutional autonomy => higher performance among US universities.

  21. US university patenting before Bayh-Dole • Many U.S. universities avoided a direct role in management of patenting, licensing. • UCB inventor Cottrell founded the Research Corporation in 1912 as a specialized patent-licensing manager. • Federal research funding agencies developed accommodative policies in the form of Institutional Patent Agreements (IPAs) in the late 1960s. • Significant change in the 1970s: • Biomedical technologies’ share of US university patents increased from 17% in 1971 to more than 30% in 1980. • Private universities’ share of US university patenting more than tripled during 1960-80, growing from 14% in 1960 to 45% in 1980. • Universities became more active managers of patenting & licensing during the 1970s, using IPAs.

  22. Tensions between universities active in patenting and federal agencies led to passage of Bayh-Dole in 1980 • HEW (parent of NIH) considered limitations on use of exclusive licensing agreements for NIH-funded inventions under IPAs. • In response, universities (led by Purdue, Stanford, MIT, Harvard, Columbia) lobbied for flexibility and consistency (and tolerance for exclusive licensing agreements) in federal policy. • University efforts were influential in a period of concern over (apparently) declining U.S. competitiveness. • Bayh-Dole thus is an effect of growth in US university patenting during the 70s, as well as one of several causes of increased academic patenting during the 80s.

  23. Post-Bayh-Dole trends • University share of all US patents grew from 0.5% in 1980 to >4% by 2008. • US universities account for as much as 11% of “biotechnology” patents by 2000. • Entry into patenting by universities with limited pre-1980 experience. • Academic institutions receiving 10 or fewer patents during 1970-1980 increased their share of total patenting from 15% during this period to 36% by 1992. • Entrant universities received “lower-quality” patents initially, closed “quality gap” with experienced institutional patenters by early 1990s. • Underscores complexity, difficulty of “learning to patent” in university OTTs. • Simple patent counts are poor performance measures. • Although “university spinoffs” are widely cited, new firms account for less than 20% of US university licensees. • Industry-funded share of total university research in U.S. grew from roughly 3.9% in 1980 to 6.9% in 1995, 7.4% in 1999, drops to 5.1% in 2008.

  24. Summary: The effects of Bayh-Dole in the United States • Much of the growth in patenting & licensing would have occurred without Bayh-Dole: • Growth in biomedical research funding and discoveries. • Broader strengthening of federal intellectual property rights. • Growth in other forms of research collaboration is less apparent. • Other forms of university-industry research collaboration have a long history in the United States and rely on other characteristics of the system. • Growth in patenting and licensing has been heavily concentrated in biomedical technologies.

  25. Managing University-Industry Linkages

  26. US university management of IP • For many US universities, net licensing revenues are modest (or negative). • U of California systemwide gross revenues averaged US$99M/year for FY 2001 – 2006; net licensing revenue averaged US$28M/year. • Industry-funded research exceeded $200M during FY 2006. • Licensing revenues dominated by small # of patents, typically in biomedical field. • Other (non-revenue) motives for university patenting: • Faculty pressure. • Economic development/technology transfer. • Funding of research by industrial collaborators/licensees. • “Research freedom,” especially in the absence of “experimental use” infringement defense. • Different goals => different policies, performance measures. • University administrators often are not clear about priorities, unrealistic about potential licensing revenues. • Fixed costs, operating expenses of TTOs are high. • Does every university need an independent TTO? Considerable scope for multi-institutional collaboration.

  27. Does university patenting affect research content and exploitation? • Does greater emphasis on one channel of university-industry interaction have a chilling effect on others? • Little evidence that faculty patenters publish less. • Is increased academic patenting (for many reasons beyond Bayh-Dole) impeding science? Evidence is inconclusive. • Cohen et al. (2006): Academics are not constrained by patents. • Murray & Stern (2009): Patented discoveries experience relative decline in citations. • Sampat et al. (2003): Slowdown in citations to university patents since 1980; slowdown is greatest for industry citations to university patents (Fabrizio, 2007). • Are Material Transfer Agreements (MTAs) linked to patenting (yes); do they impede sharing of results (possibly)? • Cohen et al. (2007): Denial of access to materials impedes academic research, and MTAs often cover research tools. • Delays are common in negotiation, approval of MTAs.

  28. How do firms link to university research? • Funding • Consulting • Hiring • Collaboration (including sending employees to academic labs). • Licensing • Virtually all of these (including licensing) require intrafirm absorptive capacity. • Very little research on determinants of firms’ ability to “tap into” university research. • What does “tapping into” mean? Recognition of opportunity? Refining research agenda?

  29. Gov’t., industry criticism of US universities • Universities’ emphasis on patenting => frictions with some non-biomedical firms. • Hewlett-Packard cited “less restrictive” IPR regime in non-U.S. universities in expanding foreign research collaboration. • National Institutes of Health efforts to standardize, simplify MTAs have encountered resistance from universities. • “…universities take inconsistent positions on fair terms of access to research tools depending on whether they are importing tools or exporting them.” (Working Group on Research Tools, 1998). • Late-2010 National Academy of Sciences report: • “Patenting and licensing practices should not be predicated on the goal of raising significant revenue for the institution. The likelihood of success is small, the probability of disappointed expectations high, and the risk of distorting and narrowing dissemination efforts is great.”

  30. Some US universities have developed less “patent-centric” policies • Gradual shift to recognize that: • Licensing revenues may not be either large or worth the expense and conflict with industry. • Much academic research does not resemble the biomedical field. • Patents are less valuable, lucrative sources of licensing revenues. • Both Stanford, UCB now emulate MIT in combining management of IP with industrial liaison activities supporting industry-sponsored research. • New policies have reduced universities’ emphasis on ownership of tangible IP from IT industry collaborations. • December 2005 “Open Collaboration Principles” agreement between 7 research universities and 4 IT firms.

  31. Conclusion • Bayh-Dole extended, rather than creating a “new era” in US university patenting, licensing, industry collaboration. • Long history of such collaboration reflects structural characteristics of US higher education “system.” • Growth of patenting in the 1980s was rooted in developments during the 1970s. • In important respects, Bayh-Dole was a response to increased university patenting, rather than an “exogenous” causal factor. • Other developments in US IPR policy, growth in biomedical research funding and scientific advances, contributed to the growth of patenting during the 1980s. • The “endogeneity” of Bayh-Dole may limit the effects of its emulation by other governments.

  32. Conclusion (2) • More than a “Bayh-Dole policy” is needed to stimulate closer interaction between universities and industry. • Structure of public research funding. • Structure of university system. • Importance of institutions external to the university (labor mobility; venture capital). • Multiplicity of channels through which universities and industry interact => the importance of patents for university-industry technology & knowledge transfer varies across and within industries. • Neither necessary nor sufficient in some research fields. • Necessary but not sufficient in others. • What role for different types of firms (established, small, startup)?

  33. Research issues (partial list) • effects of “BD emulation” outside of US. • How do firms exploit university research and how does this affect their performance? • Interactions among different classes of U-I links • Role of established firms in mediating U-I regional spillovers and cluster formation. • Effects of patenting on academic research agenda? • Research tools and IP.

  34. Further Reading • D. Mowery, "Learning from one another? International policy “emulation” and university-industry technology transfer," Industrial and Corporate Change, 2012. • D. Mowery, “University-Industry Research Collaboration and Technology Transfer in the United States since 1980,” in S. Yusuf and K. Nabeshima, How Universities Promote Economic Growth (World Bank, 2007). • Ivory Tower and Industrial Innovation: U.S. University-Industry Technology Transfer Before and After the Bayh-Dole Act (with R.R. Nelson, B.N. Sampat, and A.A. Ziedonis), Stanford University Press, 2004.

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