faculteit technologie management the different channels of university-industry knowledge transfer:...
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The different channels of university-industry knowledge transfer:
Empirical evidence from Biomedical Engineering
Reg BrennenraedtsDialogic Innovatie & Interactie
Bart VerspagenTechnische Universiteit Eindhoven
Rudi BekkersTechnische Universiteit Eindhoven
DIME, Workshop on Technology transfer from universities: A critical appraisal of patents, spin-offs and human mobility
September 29-30/2006, Lausanne
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Talk outline
• Research questions• Theoretical framework• Methodology• Analysis of the data• Conclusions• Discussion
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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?
Research questions
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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
Theoretical framework
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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
Theoretical framework
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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)
Theoretical framework
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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
Theoretical framework
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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
Methodology
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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)
Methodology
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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
Methodology
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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
Analysis of the data
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Perceived importance and frequency of ISRs (top-5)1. Conferences and workshops2. Refereed scientific journals or books3. Joint R&D projects with the industry4. Networks based on friendship5. Presentation of research at the industry
Analysis of the dataAverage scores of academic researchers regarding knowledge transfer
1,0 1,5 2,0 2,5 3,0 3,5 4,0 4,5 5,0 5,5
Emitting licenses on university patents
Participation in fairs
Own double appointment
Temporarily exchange of personnel with industry
Teaching employees of the industry
University patents
Spin-offs
Contract advisement
Participation in boards of organizations
Participation in professional organizations
Contract research
Sharing facilities with industry
Not refereed publications
Supervision of a Ph.D. student
Graduates who get job in industry
Colleagues who get (or have) job in industry
Presentation of research at the industry
Networks based on friendship
Joint R&D projects with industry
Refereed scientific journals or books
Conferences, congresses and workshops
Importance
Frequency
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General patterns in ISRs (using Factor Analysis)
Analysis of the data
1 2 3 4 5
Emitting licenses on university patents 0.79
Spin-offs 0.76
University patents 0.74
Contract advisement 0.72
Contract research 0.52
Temporarily exchange of personnel with industry 0.77
Colleagues who get (or have) a job in industry 0.62
Graduates who get a job in industry 0.61
Sharing facilities with industry 0.59
Teaching employees of the industry 0.55 0.58
Joint R&D projects with industry 0.53 0.57
Supervision of a Ph.D. student 0.51 0.51
Your own double appointment 0.79
Participation in fairs 0.68
Participation in professional organizations 0.68
Participation in boards of organizations 0.63
Publications in (refereed) scientific journals or books 0.84
Participation in conferences, congresses and workshops 0.72
Networks based on friendship 0.73
Other (not refereed) publications 0.70
Presentation of research at the industry 0.63
Rotated factor loadings
Factors1. Entrepreneur2. Dense
cooperation3. Formal network4. Science5. Informal
network
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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
Analysis of the data
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Towards a taxonomy (ii)(using multinomial logit regression)
• Cluster II (opposed to Cluster I) is typified by researchers who usually:– Do not have another appointment;– Do not have worked in a firm;– Do not 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)
Analysis of the data
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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.
Conclusions
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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
Conclusions
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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.
Conclusions
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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?
Conclusions
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N=24
Average scores of industrial researchers regarding knowledge transfer
1,00 1,50 2,00 2,50 3,00 3,50 4,00 4,50 5,00 5,50
Emitting licenses on university patents
Colleagues who get (or have) job in industry
Contract advisement
University patents
Participation in professional organizations
Participation in fairs
Temporarily exchange of personnel with industry
Spin-offs
Participation in boards of organizations
Own double appointment
Teaching employees of the industry
Not refereed publications
Presentation of research at the industry
Contract research
Supervision of a Ph.D. student
Sharing facilities with industry
Graduates who get job in industry
Conferences, congresses and workshops
Joint R&D projects with industry
Refereed scientific journals or books
Networks based on friendship
Importance
Frequency
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N=24
Average scores of academic researchers regarding knowledge transfer
1,0 1,5 2,0 2,5 3,0 3,5 4,0 4,5 5,0 5,5
Emitting licenses on university patents
Participation in fairs
Own double appointment
Temporarily exchange of personnel with industry
Teaching employees of the industry
University patents
Spin-offs
Contract advisement
Participation in boards of organizations
Participation in professional organizations
Contract research
Sharing facilities with industry
Not refereed publications
Supervision of a Ph.D. student
Graduates who get job in industry
Colleagues who get (or have) job in industry
Presentation of research at the industry
Networks based on friendship
Joint R&D projects with industry
Refereed scientific journals or books
Conferences, congresses and workshops
Importance
Frequency