The different channels of university-industry knowledge transfer: Empirical evidence from Biomedical Engineering

1. The different channels of university-industry knowledge transfer: Empirical evidence from Biomedical Engineering Reg Brennenraedts Dialogic Innovatie & InteractieBrennenraedts@dialogic.nl Bart Verspagen Technische Universiteit EindhovenB.Verspagen@tm.tue.nl Rudi BekkersTechnische Universiteit EindhovenR.N.A.Bekkers@tm.tue.nl DIME, Workshop on Technology transfer from universities: A critical appraisal of patents, spin-offs and human mobilitySeptember 29-30/2006, Lausanne

2. Talk outline • Research questions • Theoretical framework • Methodology • Analysis of the data • Conclusions • Discussion

3. Research questions Research questions How do industry-science relations take place at the faculty of Biomedical Engineering at the Eindhoven University? • What is the relative frequency of the different forms of ISRs? • What is the perceived importance of the different forms of ISRs? • Which factors influence the pattern of ISRs?

4. Theoretical framework Context • Science increasingly more important for economic growth • European paradox: • Europe excels in scientific research… However: • Commercial/technological performance in high tech sectors is decreasing • Large differences in ISRs occur between countries and universities • Purpose of ISRs  Knowledge transfer

5. Theoretical framework Forms of ISRs • Publications • Participation in conferences, professional networks and boards • Mobility of people • Other informal contacts • Cooperation in R&D • Sharing of facilities • Cooperation in education • Contract research and advisement • Intellectual property rights • Spin-offs and entrepreneurship

6. Theoretical framework What causes different footprints of ISRs? • Between sector variation: • Knowledge base (in casu BME) • Nelson and Winter (entrepreneurial / routinized) • Schumpeter (Mark I: widening / Mark II deepening) • Pavitt (supplier dominated, production intensive, science) • Within sector variation: • Reputation of a researcher • Exact type of research one conducts: • Applied vs. not-applied • Multidisciplinary vs. monodisciplinary • Social network of an individual • Weak ties (acquaintances) • Strong ties (friends) • National or Regional System of Innovation • Policy of faculty or university (regarding ISRs)

7. Theoretical framework Faculty of Biomedical Engineering (BME) • 200 employees, 400 students • Founded in 1997 • Cooperation between: • Eindhoven University (TU/e) • Maastricht University (UM) • Teaching hospital Maastricht (azM) • Focus on: • BMTE (BioMechanics and Tissue Engineering) • MBEMI (Molecular BioEngineering & Molecular Imaging) • BIOMIM (BIOMedical Imaging and Modeling) • Knowledge base in: Physics, Chemistry, Mathematics, Electronics, Medicine & Biology

8. Methodology Back to our research question… • Relative frequency / perceived importance of the different forms of ISRs? • Which factors influence the pattern of ISRs? • Dependent variables: frequency/perceived importance of ISRs • Independent variables: Properties of researchers

9. Methodology Obtaining data (i) Focus on knowledge producers, not R&D managers • Publication and citation scores • Web of Science database • Questionnaire: • Population are all the researchers employed at BME (n=138) • Response >62% (n=85)

10. Methodology Obtaining data (ii) • Questionnaire contains questions regarding: • Background of the researcher • Position at university? • Other position? • In the past employed in industry? • Monodisciplinary or multidisciplinary research? • Applied or fundamental or experimental research? • Patents? • Frequency/perceived importance of forms of ISRs • 21 different forms of ISRs

11. Methodology

12. Analysis of the data Relative frequency and perceived importance of ISRs • Highly correlated • Correlation coefficient = 0.95 • Rank correlation = 0.92 • People do what they find important • No possibility (or need) to distinguish between these variables • Further analysis is conducted using the sum of these scores

13. Analysis of the data Perceived importance and frequency of ISRs (top-5) 1. Conferences and workshops 2. Refereed scientific journals or books 3. Joint R&D projects with the industry 4. Networks based on friendship 5. Presentation of research at the industry

14. Analysis of the data General patterns in ISRs (using Factor Analysis) Factors 1. Entrepreneur 2. Dense cooperation 3. Formal network 4. Science 5. Informal network

15. Analysis of the data Towards a taxonomy (i)(using cluster analysis) • Clustering the respondents by their factor scores… • Cluster I (n=24)high factor scores on informal networking • Cluster II (n=18)high factor scores on science • Cluster III (n=14)high factor scores on science, formal network, informal network • Note: Factors entrepreneur and dense cooperation are not preffered by a specific group

16. Analysis of the data Towards a taxonomy (ii)(using multinomial logit regression) • Cluster II (opposed to Cluster I) is typified by researchers who usually: • Donot have another appointment; • Donot have worked in a firm; • Donot have any patents; • Do have conducted mainly fundamental; • Do have many publications. • Cluster III (opposed to Cluster I) is typified by researchers who usually: • Do have another appointment (relative risk ration >60)

17. Conclusions The taxonomy (i) • Some ISRs are appreciated by a broad set of respondents: • Spin-offs, patents, contract research, et cetera (factor: Entrepreneur) • Exchange of personnel, sharing facilities, joint R&D, et cetera (factor: Dense cooperation) • Some ISRs are preferred by a specific type of respondent.

18. Conclusions The taxonomy (ii) • Cluster I: • prefers: friendships, presentation at the industry, et cetera (factor: informal networking) • Cluster II: • prefers: refereed publications, conferences, supervision of a Ph.D. student (factor: science) • contains: Traditional academics • Cluster III • prefers: many different channels (factors: informal networking, formal networking, science) • contains: academics with more then 1 appointment

19. Conclusions Policy implications: • Much variation found in transferring knowledge • Policy should be aimed at a multitude of channels and a wide range of channels. • Academics with a strong reputation prefer to use the traditional (rather passive) channels • Although an interesting match for the industry, could possibly be hard to motivate to use the more active channels of knowledge transfer.

20. Conclusions Suggestions for further research • Research at another sector (faculty)  verify within sector variations • Research at broad scope of faculties  find between sector variations • Research at the industry  do they have the same opinion?

21. Discussion Discussion…

22. N=24

23. N=24