Entrepreneurial Universities An Overview & Reflection Prof. Bart Van Looy 27.05.15 Managerial Economics, Strategy and Innovation (Chair) Faculty of Business

Entrepreneurial Universities

An Overview & Reflection

Prof. Bart Van Looy

27.05.15

Managerial Economics, Strategy and Innovation (Chair)Faculty of Business & Economics

KU Leuven, Belgium

Research Division INCENTIM Expertise Centre O&O Monitoring (ECOOM) – Co-Promotor Technometrics

Office: HOG – Naamsestraat 69, 03.143.

[email protected]

mailto:[email protected]

2

Robert Solow (1957)

Production function approach:

– Y=F(L,C) (e.g. Cobb-Douglas Y = LK) (L= Labor, C=Capital)

– Y=F(L,C).A(T) with A(T) a technological progress parameter (e.g. evolution in R&D expenditures or evolution in patent output)

– R2: 20% ==> 80%

3

Income Levels California (2000 Census data)

Rank National Rank

County Per Capita Income

Median House- hold Income

1 1 Marin County $44,962 $71,306

2 14 San Mateo County $36,045 $70,819

3 19 San Francisco County $34,556 $55,221

4 25 Santa Clara County $32,795 $74,335

5 45 Contra Costa County $30,615 $63,675

6 49 Ventura County $29,634 $75,157

7 77 Placer County $27,963 $57,535

8 96 Alameda County $26,860 $55,946

9 106 Santa Cruz County $26,396 $53,998

10 107 Napa County $26,395 $51,738

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EPO – Patent Applications by universities

• Period: 2000 – 2012

• Who do you expect in the Top 10?

• How many European universities in the top 20?

• How many European universities in the top 100?

INCENTIM/KU Leuven Share of triadic Patents

(DG Research – 2000-2010)

EU-27 North America Asia1.Health 34,38% 44,18% 14,00%

2a. Food, Agriculture & Fisheries 36,33% 31,04% 24,85%

2b. Biotechnology 33.40% 41.04% 21.21%

3. ICT 27,43% 27,57% 42,02%

4a. Nanotechnology 28,12% 31,76% 36,90%

4b. Materials 36,87% 28,96% 29,77%

4c. New Production Technologies 34,24% 27,42% 31,60%

4d. Construction 49,68% 19,70% 25,48%

5. Energy 34.85% 23.96% 37.22%

5 -6 Green Energy 32.94% 30.24% 31.47%

6. Environment 34.27% 28.52% 34.00%

7a. Aeronautics 45,62% 39,74% 12,07%

7b. Automobiles 37,16% 11,37% 50,28%

7c. Other Transport 30,16% 8,47% 55,16%

9. Space 28,33% 44,33% 24,67%

10. Security 29,11% 33,61% 31,66%

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Seven fields in which Europe has the largest share of Triadic Patents:

Food, Agriculture & Fisheries: Materials; New Production Technologies; Construction; Green Energy; Environment; Aeronautics.

Four fields in which North America (USA & Canada) have the largest share of triadic patents: Health; Biotechnology; Space; Security

Five fields in which Asia has the largest share of triadic patents: ICT; Nanotechnology; Energy; Automobiles; Other transport technologies.

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Science-Technology-Industry links and the ‘European’ paradox: Some notes on the dynamics of the scientific and technological research in Europe (Dosi et al. 2005)

Entrepreneurial Universities - the role of science (when innovating/inventing) : A recurrent theme (in my research portfolio)

• Van Looy, B., K. Debackere and P. Andries (2003), “Policies to stimulate regional innovation capabilities via university-industry collaboration, R&D Management, 33, 209-229.

• Van Looy, B., J. Callaert, A. Verbeek, and K. Debackere (2003), “Patent Related Indicators for Assessing Knowledge Generating Institutions: Towards a contextualised Approach”, Journal of Technology Transfer, 28, 53-61.

• Van Looy, B., E. Zimmermann, R. Veugelers, J. Mello, A. Verbeek, and K. Debackere (2003), “Do science-technology interactions pay off when developing technology? An exploratory investigation of 10 science-intensive technology domains”, Scientometrics, 57, 355-367.

• Van Looy, B., Ranga M., Callaert, J. , Debackere K. & Zimmermann E. (2004): Combining Entrepreneurial and Scientific Performance in Academia: Towards a compound Matthew Effect encompassing both activity realms? Research Policy, 33, 425-441.

• Van Looy, B., Debackere K., Callaert J., Tijssen, R. & Van Leeuwen T. (2006). Scientific capabilities and technological performance of National Innovation Systems: An exploration of emerging industrial relevant research domains. Scientometrics, 66, 2, 295-310.

• Van Looy, B., Callaert J. & Debackere K. (2006) Publication and Patent Behaviour of academic researchers: conflicting, reinforcing or merely co-existing. Research Policy. 35, 4, 596-608

• Van Looy B., Magerman T. & Debackere K. (2007) Developing technology in the vicinity of science: An examination of the relationship between science intensity (of patents) and technological productivity within the field of biotechnology. Scientometrics, 70, 2, 441-458

• Van Looy B. (2009) , The role of universities within innovation systems: an overview and assessment. Review of Business and Economics, 2009, LIV, 1. 62-81

Entrepreneurial Universities - the role of science (when innovating/inventing) : A recurrent theme (in my research portfolio)

• Lecocq, C., Van Looy, B., Zimmermann, E. (2009), Developing the support infrastructure of technology transfer offices to accommodate the needs of global spinoff companies. International Journal of Globalisation and Small Business, 2009, 3(2), 201-219.

• Van Looy, B., Landoni P., Callaert J., van Pottelsberghe B., Sapsalis E. & Debackere K. (2011) Entrepreneurial effectiveness of European universities: An empirical assessment of antecedents and trade-offs. Research Policy, 40(4), 553-564.

• Callaert J. , Grouwels J. & Van Looy B. (2012) Delineating the scientific footprint in technology: Identifying scientific publications within non-patent references. Scientometrics. 91,2, 383-398.

• Leten B., Landoni P. & Van Looy B. (2014) Science or Graduates: How do Firms Benefit from the Proximity of Universities? Research Policy.

• Lecocq C. & Van Looy B. (2013/2014) What Differentiates Top Regions in the Field of Biotechnology? An empirical Study of the Texture Characteristics of 101 Biotech Regions in North-America, Europe and Asia-Pacific. Industry and Corporate Change, second round.

• Callaert J. , Landoni P. & Van Looy B. (2013/2014) Academics collaborating with industry: what drives scientific leverage? Research Policy.

• Faems D., Van Looy B. & Debackere K. (2005) Inter-organizational collaboration and Innovation: towards a portfolio approach. Journal of Product Innovation Management, 22, 238-250.

• Cassiman, B., Glenisson, P., Van Looy, B. (2007). Measuring industry-science links through inventor-author relations: A profiling methodology. Scientometrics, 70(2), 379-391.

• Belderbos R., Cassiman B., Faems D., Leten B. & Van Looy B. (2014) Co-Ownership of Intellectual Property: Exploring the Value Creation and Appropriation Implications of Co-Patenting. Research Policy.

Entrepreneurial Universities

• Complex: A lot of constituents/antecedents– Innovation Systems– Entrepreneurial universities & regional development

• At the same time, one could also argue that the core ‘constituents’ are straightforward (and hence simple)

Firms’ capabilities

and networks

Other research bodies

Science system

Supporting institutions

Global innovation networks

National innovation system

Knowledge generation, diffusion and use

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National Innovation Capacity

COUNTRY PERFORMANCE Growth, job creation, competitiveness

Education and training system

Product market conditions

Factor market conditions

Communication infrastructure

Macroeconomic and regulatory context

National Innovation System Framework, (OECD, 1998)

Co-operation with and (co-)development of existing economic texture

Nature of the existing economic texture (both in terms of critical mass and in terms of ‘requisite’ variety).

Proximity of Financial Markets (venture capital, business angels, private investors, capital markets)

Availability of Business Services - Proximity of (Product) Markets

Availability of Qualified Labour Communication, Transport, Infrastructure (airports,

highways, science parks,….) Science Park Infrastructure

Real estate development Maintenance, development and exploitation of

infrastructure Development of basic & specialised services

Presence/inflow of knowledge intensive foreign direct investment

Presence and Active Involvement of Knowledge Generating Institutions

Scientific Capabilities: Scope/Size/Quality of Research Disciplines Longevity of Institute & Research Infrastructure

Entrepreneurial Orientation : Strategic Intent (amount/nature of entrepreneurial direction setting) Presence and nature of Technology Transfer Mechanisms and

specialised supporting services (e.g. with respect to contract research, spin off activities, patents/licensing) Design of motivating incentive systems in relation to

entrepreneurial activities of Academic/Research staff Proactive development of technology transfer oriented

collaboration agreements both with local and international partners

Orientation towards local and global networking initiatives Presence of capabilities in the field of Business Administration

Direct Economical Impact ( KGI’s as Originator/Owner)

# Spin offs (turn-over; employment) - Amount of Contract research - # Patents (license revenues)

Indirect Economical Impact (KGI’s as Contributor/Participant)

Contribution to the development of technological and innovative

capabilities of firms within the region ( Degree of new product development - GERD / BERD /HERD …)

Spill overs - Number of patents per capita

Development of a motivating institutional framework and Support

Infrastructure Establishment of a Legal Framework that addresses Property

Right Issues in an ‘entrepreneurial’ friendly way. Design – Dynamics of the National Innovation System

o Task and role allocation including public funding policies with respect to science, technology and innovation

o Presence of supporting R&D Policies and Priorities

o Alignment with Regional Development Policies Establishing links with internationally operating Promotion

Agencies (FDI – International Business Development) Stimulation of cooperation by designing incentive schemes

(e.g. with respect to supporting NPD) Encouraging the development of a regional entrepreneurial

culture & improving + Quality of life

True or False

Entrepreneurial activities hamper science.

TTO’s are crucial to arrive at scale/scope of technology transfer activities (TTO’s are the ‘engine’ behind the third mission).

Entrepreneurial activities generate a substantial share of funding for universities (allowing to decrease over time more traditional types of university funding).

A more entrepreneurial orientation of universities will be beneficial for all kind of industries and all kind of R&D/Innovation challenges.

‘Bayh Dole’ type of legislations are not relevant (or even harmful).

Entrepreneurial activities hamper science?

Combining Entrepreneurial and Scientific Performance in Academia: Towards a compound Matthew Effect

encompassing both activity realms?

Research Policy, 33, 425-441.Van Looy, B., Ranga M., Callaert, J. , Debackere K. & Zimmermann E. (2004):

Publication and Patent Behaviour of academic researchers: conflicting, reinforcing or merely co-existing.

Research Policy. 35, 4, 596-608 Van Looy, B., Callaert J. & Debackere K. (2006)

BackgroundBackground• Central importance of knowledge in

national innovation systems

• Public governance and funding rules – an increasing emphasis on:– socio-economic relevance of research– encourage university-industry relations

• Entrepreneurial Universities adding patenting activities, contract research, spin off activities to traditional missions of teaching and

research

BackgroundBackground• Concerns relating to this ‘second academic revolution’

– Secrecy problem (Florida & Cohen, 1999)

alleged restrictions on free disclosure of research - especially pronounced when IPR practices enter the stage

– Skewing problem (Florida & Cohen, 1999) ~ Corporate Manipulation Thesis (Noble, 1977)

alleged modification of academic research agenda by industry

• Previous research focused on the feasibility of reconciling contract research (with industrial partners) with scientific activities (Van Looy et al., 2004)

– Positive relation between involvement in CR and scientific output (amount of publications)

– Involvement in CR did not ‘skew’ the research agenda (nature of publications)

– Time effect: development of a CR division allowed faculty to ‘widen’ an aready existing gap in publication output (leveraging resources)

Involvement in contract research & publication ‘differentials’ (Van Looy et al. RP, 2004)

Faculty/Discipline Division

number

yearly average number of publications

(division members – faculty members)

Applied Sciences 1 0.45

2 0.56

3 1.72

4 0.91

5 4.22

6 0.58

7 6.10

8 2.25

Medicine 1 1.33

2 0.22

Agricultural Sciences 1 6.97

2 4.49

Pharmaceutical Sciences 1 5.21

Sciences 1 3.67

Mean difference (division – faculty) = 2.76

Median difference (division – faculty) = 1.98

Paired samples t-test: p =0.001

Leveraging Resources

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Research QuestionsResearch Questions• Building upon our previous results, we currently focus

on combining scientific and patent activity

• Research Questions1. Do faculty members who are engaged in patenting activity

(inventors) publish less than their colleague non-inventors?

2. Do inventors differ from colleague non-inventors in terms of the nature of their publications (basic/applied)?

3. To what extent does involvement in contract research with industry influence the co-existence of patent and scientific activities?

Situating the data: KU LeuvenSituating the data: KU Leuven• Founded in 1425; 14 faculties, including Engineering and Medicine,

Social Sciences, Arts and Humanities; +/-30.000 students; +/- 15.000 academic staff, of which +/- 1000 professors

• From the ’70’s and ’80’s onwards: active strategic stance towards knowledge transfer and participation in regional and (inter)national economic development

• Supportive context: K.U.Leuven Research & Development (LRD), founded in 1972. LRD provides advice, coordination, administration and legal support with regard to: patenting and licensing, development of spin off activities, contract research

MethodologyMethodology• Sample: KUL faculty members (N=32) ...

1) …appearing in the inventor name fields of granted EPO patents during the time period 1995 – 2001; and

2) …employed as professor at K.U.Leuven at the time of the invention

• Per individual: comparison group of faculty members (non-inventors) in same discipline and with comparable career profile (research discipline, age, date of first KUL appointment)

• For all individual faculty members: – Number of publications, extracted from WoS database (1998-2000)– Membership of contract research division (Y / N)

Discipline Number of Inventors Medicine & Pharmaceuticals 20 Applied Engineering 5 Science 3 Agriculture 4 Total 32

Results – RQ 1Results – RQ 1RQ 1 - Do faculty members who are engaged in patenting activity (inventors) publish less than their colleague non-inventors?

Paired sample t-test for number of SCI publications (1998 – 2000) Inventors/Non-Inventors

Mean Difference

Std. Deviation

Std. Error Mean

95% Confidence

Interval of the Difference

t df Sig. (2-tailed)

Complete Sample

Lower Upper

24,1482 50,12 8,860 6,07 42,21 2,726 31 ,010

Sample Without Outliers

Lower Upper

10,7210 18,25 3,389 3,77 17,66 3,163 28 ,004

Inventors Non-inventors Complete sample 35,8 11,7 Sample without outliers (# pubs < 90) 22,8 12,1

Average number of SCI publications (1998-2000)

>>

Results – RQ1 (longitudinal)Results – RQ1 (longitudinal)

Mean Std. Deviation N Significance

Before Invention 2.33 4.80 85 0.000 After Invention

4.58

8.04

114

0.000

Total

3.62

6.92

199

0.000

Source Type III Sum of Squares df Mean Square F Sig.

Corrected Model 4,994.264(a) 25 199.771 7.686 0.000 Intercept 1,874.024 1 1,874.024 72.100 0.000 Before/After (0/1) 384.875 1 384.875 14.807 0.000 Inventor 3,104.285 12 258.690 9.953 0.000 Before/After * Inventor 1,228.103 12 102.342 3.937 0.000 Error 4,496.643 173 25.992 Total 12,098.103 199 Corrected Total 9,490.907 198

Time effect: Additional longitudinal comparison data for a sample of inventors (n=16)

Mean difference in publication output (per year) between inventors and comparison persons

ANOVA (DV= difference in yearly publication output between inventors and non-inventors)

R Squared = 0.526 (Adjusted R Squared = 0.458)

Results – RQ1 (longitudinal)Results – RQ1 (longitudinal)

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Results – RQ2Results – RQ2RQ 2 - Do inventors differ from colleague non-inventors in terms of the nature of their publications (basic/applied)?

Nature of Publications Technology

- oriented Applied

Technology- oriented

Basic

Science- oriented Applied

Science- oriented

Basic

Total

Observed Inventors 23 119 257 188 587 Non-Inventors 79 221 186 181 667 Total 102 340 443 369 1,254 Expected Inventors 47.75 159.15 207.37 172.73 587 Non-Inventors 54.25 180.85 235.63 196.27 667 Total 102 340 443 369 1,254 Significance p<0.0001

Chi Square: Relation between nature of publications and involvement in inventions

• Inventors publish less than expected in technology-oriented journals

• Inventors publish more than expected in science-oriented journals

Results – RQ3Results – RQ3RQ 3 - To what extent does involvement in contract research with industry influence the co-existence of patent and scientific activities?

R Squared = 0.567 (Adjusted R Squared = 0.461)

Non-inventor Inventor Total Non-division 10,72 20,21 15,47 Division 13,72 58,62 36,17 Total 12,22 39,42

Average number of SCI publications (1998-2000)

ANCOVA (DV= total SCI publications between 1998 and 2000)Source Type III Sum of Squares Df Mean Square F Sig. Corrected Model 8,084.403a 16 505.275 5.325 0.000 Intercept 229.633 1 229.633 2.420 0.125 Age (covariate) 57.804 1 57.804 0.609 0.438 Division Membership (DIV) 2,930.278 1 2,930.278 30.881 0.000 Discipline (DIS) 2,482.647 3 827.549 8.721 0.000 Inventor (INV) 1,731.204 1 1,731.204 18.244 0.000 DIV * DISC 1,616.784 3 538.928 5.680 0.002 DIV * INV 1,070.976 1 1,070.976 11.287 0.001 DISC * INV 458.711 3 152.904 1.611 0.195 DIV * DISC * INV 511.256 3 170.419 1.796 0.157 Error 6,167.821 65 94.890 Total 34,806.213 82 Corrected Total 14,252.224 81

ConclusionsConclusions

• Inventors publish significantly more than their colleagues who work in similar fields and who have similar career characteristics.

• Over time, involvement in patenting activities appears to increase the publication difference in favor of inventors.

• The alleged skewing problem is not confirmed: no shift of publication output towards the more applied end of the publication spectrum at the expense of more scientific or basic-oriented publications.

• Involvement in contract research further adds to the differential publication outputs.

SOURCE RESEARCH SETTING FINDINGS

Calderini & Franzoni (Working Paper, 2004)

Quantitative analysis of patent and publication behavior of Italian scientists over time (Engineering Chemistry and Nanotechnology for New Materials; N=1323)

Scientific advantage (quantity and impact) of inventorsPublications positively related to patents in the same period and in preceding years

Van Looy et al. (Research Policy, 2004)

Quantitative analysis of entrepreneurial (contract research) and scientific activities of professors at K.U. Leuven, Belgium (N=167)

Scientific advantage of entrepreneurial professorsNo skewing of publications towards the more applied spectrum

Breschi et al. (Revue d’Economie Industrielle, 2005)

Quantitative analysis of Italian inventors’ patent and publication activity over time (N=300)

Scientific advantage of inventors; already somehow existing before patenting event, but increasing in the years immediately after the patent

Gulbrandsen & Smeby (Research Policy, 2005)

Survey among tenured Norwegian professors (N=1967)

Publication productivity positively related to industry funding; but not to entrepreneurial outputs

Czarnitzki et al. (Research Evaluation, 2006)

Quantitative analysis of publication and patent activity of over 3500 German researchers

Positive relation between patenting and publication quantity as well as quality

Meyer (Research Policy, 2006)

Quantitative analysis of publication and patent activity of nano-scientists in UK (13235 authors), Germany (22242 authors) and Belgium (2652 authors)

Overall: Scientific advantage (quantity and impact) of inventorsFor star scientist sample: scientific advantage does not hold

Van Looy et al. (Research Policy, 2006)

Quantitative analysis of patent and publication behavior of professors at K.U. Leuven, Belgium (N=317)

Scientific advantage of inventors; larger in the period after first patent has been invented

Azoulay et al. (Journal of Economic Behavior andOrganization, 2007)

Quantitative analysis of publication and patent activity of 3862 life-scientists in US

Increase in researcher’s publications significantly adds to the odds of this researcher entering the patenting regime in the following year

SOURCE RESEARCH SETTING FINDINGS

Calderini, Franzoni & Vezzulli (Research Policy, 2007)

Quantitative analysis of patent and publication behavior of Italian scientists over time (Material Sciences; N=1276)

Probability to patent is a curvilinear function of scientific productivity, basicness and impact: increasing for low-to-moderate-high values of the variables, and decreasing for high values

Carayol(Economics of Innovation and New Technologies, 2007)

Quantitative analysis of patent and publication behavior of faculty at Université Louis Pasteur, Strasbourg, France (N=941)

Positive relation between publishing and patentingBut perhaps incompatibility at lab level: research organizations that support patenting differ from those that promote publishing activities

Crespo & Dridi (Higher Education, 2007)

Qualitative study of how UI relations impact academic research (in-depth interviews with 5 TT officers and 28 university researchers in Sciences, Engineering and Social Sciences (< 6 Québec HE institutions, Canada)

Scientific benefits to be yielded from involvement in projects with industryBenefits stem from adopting strategies in the negotiations with industrial partners and from networking with other researchers in the same area

Elfenbein (Journal of Economic Behavior and Organization, 2007)

Quantitative analysis of the relation between academic prestige and licensing outcome (1703 reports of patentable inventions by Harvard University faculty (N=451)

Inventors' prior scientific output positively correlated with the likelihood that their new technologies will be licensed, but uncorrelated with the receipts generated by the licensed technology

Stephan et al. (Economics of Innovation and New Technology, 2007)

Quantitative analysis on patenting and publication behaviour of a cross-section of over 10.000 US doctorate recipients

Positive and significant relation between patents and number of publications

Fabrizio & DiMinin (Research Policy, 2008)

Survey + quantitative analysis of patent and publication activity over time of US researchers (N=400) in science and engineering disciplines

Scientific advantage of inventorsYearly number of inventors’ publications increases following a patent

Bart Van Looy* Eleftherios Sapsalis**

Paolo Landoni ***Julie Callaert *

Bruno van Pottelsberghe** Koenraad Debackere*

*Research Division INCENTIM, Faculty of Economics & Applied Economics, K.U.Leuven, Belgium

** Université Libre de Bruxelles - Solvay Business School – Centre Emile Bernheim, ULB, Belgium

*** Politecnico di Milano, Italy

Entrepreneurial performance of European Universities:

An empirical assessment of antecedents

• Over the last decades, science-industry relationships have received considerable attention, resulting from an increased recognition of the fundamental role of knowledge and innovation in fostering economic growth, technological performance and international competitiveness (e.g. Freeman, 1987, 1994; Lundvall, 1992; Nelson, 1993; Nelson and Rosenberg, 1993; Mowery and Nelson, 1999; Dosi, 2000).

• In line, the concept of ‘innovation systems’ has gained widespread acceptance and has been used as a general framework for designing innovation policies and adequate institutional arrangements in support of those policies (OECD, 1999; European Innovation Scorecard, 2002).

• Complementary important contributions can be found in the influential work of Michael Porter (1995), and the work on the 'Triple Helix', which rose to prominence in the second half of the 1990s (Leydesdorff en Etzkowitz, 1996, 1998; Etzkowitz en Leydesdorff, 1997; Leydesdorff en Etzkowitz, 1998).

• Closely associated with the Triple Helix model, the notion of ‘entrepreneurial universities’ (Branscomb, Kodama & Florida, 1999; Etzkowitz, Webster & Healy, 1998) has increasingly been used in relation to the spectrum of evolutions faced in recent years by academia: more involvement in economic and social development, more intense commercialization of research results, patent and licensing activities, the institutionalization of spin off activities and managerial and attitudinal changes among academics with respect to collaborative projects with industry

Background

Antecedents of Entrepreneurial Performance

• Previous research identified several elements beneficial for the entrepreneurial activities of universities (e.g. Henderson et al. 1998; Varga, 1009; Debackere, 2000,2005; Mowery & Ziedonis, 2002; Colyvas et al., 2002; Agrawal & Henderson, 2002; Di Gregorio & Shane, 2002; Coupé, 2003; Lach and Schankerman, 2003; Shane, 2004; O’Shea, Allen & Chevalier, 2004).

• R&D intensity of the regional economical texture (for spin offs, this includes the presence of – early stage - venture capital)

• Strategic orientation and commitment of the university towards the ‘third’ mission (top and academic staff)

• Legislative frameworks allowing and/or stimulating knowledge transfer from universities• Size/Disciplines present at the university• Scientific capabilities?

– Di Gregorio & Shane (2002); O’Shea, Allen and Chevalier (2004), Powers & McDowell (2004) observe a positive relationship between scientific ‘eminence’ and entrepreneurial performance (US).

– At the same time, the reconciliation of scientific and entrepreneurial performance is being questioned (e.g. Geuna, 1999; Hane, 1999; Vavakova, 1998, Nelson, 2004)

– ‘Fundamental’ differences in terms of reward and incentive systems (secrecy and closure versus the open dissemination of knowledge) might result in trade-offs or strategic choices favoring entrepreneurial over scientific activities (or vice versa)

Research Questions

• Large scale empirical evidence on a European level is scarce

• Research Focus:

To what extent are scientific capabilities related to – positively or negatively - entrepreneurial performance of European universities?

Stated otherwise, when controlling for size (total academic staff), presence of disciplines and the R&D intensity of the local business environment does one observe a relationship between scientific and entrepreneurial activities?

• Data gathering on a European level• Focus on larger, science/technology intensive universities • Sample: n=105, response rate, 62%

Germany – Austria Belgium France Scandivia Spain University of Leoben Graz University of technology research Agro University Vienna University of Vienna University of Salzburg University of Tuebingen Technische Universität Dresden (TUD) University of Karlsruhe Johannes Gutenberg-Universität Mainz Ruhr-Universität Bochum ZFT Universität Freiburg University of Stuttgart RWTH Aachen Universität Heidelberg

LUC Diepenbeek University of Antwerp Vrije Universiteit Brussel Gent University Catholic university of Leuven University of Mons Hainaut University of Namur Faculté Polytechnique de Mons Université Libre de Bruxelles University of Liège Université Catholique de Louvain

Ezus Lyon 1 - Subsidiary of Univ Claude Bernard Lyon-1 University of Nantes Ecole Polytechnique University Pierre et Marie Curie Télécom de Paris (Ecole nationale supérieure de Télécommunications) University of Paris 11 University of Rouen Aix Marseille II University of Rennes 1 ENSAM University of Franche-Comté-Besançon University Victor Segalen Bordeaux 2 University Avignon Inst. Nat. Polytechnique de Toulouse Université des Sciences et Technologies de Lille (USTL) University Louis Pasteur (Strasbourg 1) Université de Reims Champagne-Ardenne Paris 7 Université de Bretagne Occidentale

University of Aarhus Technical University of Denmark University of Southern Denmark Upssala University Holding Company Chalmers University of Technology Karolinska intitute Tampere University of Technology University of Turku Lappeeranta University of Technology University of Jyväskylä Helsinki University of Technology University of Kuopio University of Oulu University of Helsinki

Univ. Polytechnica Catalunya University Carlos III de Madrid University Politecnica de Valencia University Politecnica de Madrid University of Salamanca Universidad Autonoma de Barcelona University Santiago de Compostela University of Cordoba University Complutense de Madrid University of Sevilla University of Barcelona University of Granada Universidad Miguel Hernández de Elche

Netherlands Italy Greece - Portugal United Kingdom - Ireland

University of Amsterdam Delft University of Technology University of Nijmegen Technische Universiteit Eindhoven University of Utrecht University of Leiden Maastricht University Tilburg University University of Twente

University of Genoa University of Turin Universita' degli studi di Bologna Università degli studi di Milano Scuola Superiore Sant'Anna Politecnico di Milano Università di Siena Università di Pavia Università degli studi della Calabria Università di Roma "La Sapienza" Politecnico di Torino

National Technical University of Athens University of Ioannina Aristotle University of Thessaloniki University of Porto University of Lisbon Instituto Superior Técnico, Lisboa

National University of Ireland, Galway University College Dublin University of Nottingham Queen's University Belfast University of Surrey University of Glasgow University of Oxford University of Warwick

Constructs, Indicators & Data Sources

Construct Indicator Source Size of the University Number of Academic Staff Survey Range of Disciplines present at University

Presence (0/1) of Arts & Humanities, Engineering, Science, Life Sciences (Medicine/Pharmaceutical)

Survey

Scientific Orientation Number of Scientific Publications normalized by Number of Academic Staff.

Web of Science EC Report on S&T Indicators

Regional R&D intensity Business Expenditures on R&D (BERD), Nuts level 3 Eurostat Entrepreneurial Orientation

Size of TTO Staff Survey

Amount of contract research 2002 Survey

Number of Spin offs Established Survey

Entrepreneurial Performance:

Number of Patent Applications 2002 Number of EPO patent Applications 1999/2000 –

Survey EPO Database

Analysis

Three Independent Variables:

• Amount of Contract Research• Amount of Spin Off activity• Amount of Patenting Activity

Three Models:

• (1) Size, TTO Size, BERD & Scientific Orientation • (2) Size, TTO Size, BERD & Scientific Orientation + Presence of

Disciplines (0/1)• (3) Size, TTO Size, BERD & Scientific Orientation + Presence of

Disciplines (0/1) + Country (0/1)

Antecedents of Entrepreneurial Performance: Contract Research

CONTRACT RESEARCH

B Std. Error Beta t Sig B Std. Error Beta t Sig B Std. Error Beta t Sig

Constant 6,7245 0,1146 58,7025 0,0000 6,7661 0,2223 30,4390 0,0000 6,9675 0,2796 24,9183 0,0000

#Academic Staff 0,0001 0,0000 0,2327 2,2351 0,0283 0,0001 0,0000 0,2941 2,4114 0,0184 0,0001 0,0000 0,2581 2,4550 0,0167

BERD (Nuts 3) 0,0359 0,0520 0,0731 0,6905 0,4919 0,0230 0,0600 0,0467 0,3831 0,7028 -0,0003 0,0602 -0,0006 -0,0050 0,9960

Size TTO 0,0041 0,0044 0,0978 0,9336 0,3534 0,0023 0,0046 0,0549 0,4987 0,6195 0,0027 0,0043 0,0638 0,6198 0,5375

Scientific Orientation 0,0471 0,0145 0,3409 3,2527 0,0017 0,0564 0,0162 0,4080 3,4855 0,0008 0,0291 0,0140 0,2106 2,0743 0,0420

Arts & Humanities 0,0753 0,1423 0,0730 0,5292 0,5983 -0,1475 0,1148 -0,1429 -1,2855 0,2031

Medicine -0,0930 0,1383 -0,0913 -0,6721 0,5036 -0,0338 0,1142 -0,0332 -0,2962 0,7680

Engineering 0,1098 0,1286 0,0950 0,8539 0,3959 0,2066 0,1028 0,1788 2,0103 0,0485

Science -0,1955 0,1703 -0,1509 -1,1482 0,2546 0,0676 0,1448 0,0522 0,4671 0,6420

Germany – Austria 0,1678 0,2137 0,1145 0,7851 0,4352

France -0,6282 0,1925 -0,5682 -3,2625 0,0018

Italy -0,3228 0,2120 -0,2091 -1,5225 0,1327

Spain -0,4434 0,2000 -0,3423 -2,2168 0,0301

Belgium 0,0396 0,1906 0,0295 0,2078 0,8360

Scandinavia -0,0439 0,2083 -0,0326 -0,2105 0,8339

Portugal - Greece -0,1217 0,2392 -0,0572 -0,5088 0,6126

Netherlands 0,3141 0,2369 0,1477 1,3261 0,1894

R 0,4674 0,5001 0,7774

R Square 0,2184 0,2501 0,6044

Adjusted R Square 0,1784 0,1690 0,5085

Std. Error of the Estimate 0,4155 0,4179 0,3214

Regression Sum of Squares 3,7641 4,3095 10,4144

Residual 13,4668 12,9214 6,8165

Total 17,2309 17,2309 17,2309

Mean Square Regression 0,9410 0,5387 0,6509

Mean Square Residuals 0,1727 0,1746 0,1033

F 5,4504 3,0850 6,3023

Significance 0,0006 0,0047 0,0000

Degrees of freedom model 4 8 16

Total Observations 82 82 82

Antecedents of Entrepreneurial Performance: Patent Activity

(EPO Applications, 1999-2000)

EPO APPLICATIONS ’99 – ‘00

Negative Binomial QML

Variable Coefficient Std, Error Prob, Coefficient Std, Error Prob, Coefficient Std, Error Prob,

Constant 0,222 0,291 0,447 -1,432 0,603 0,018 0,464 1,074 0,666

#Academic Staff 0,000489 0,0001 0,0000 0,0004 0,0001 0,0007 0,0005 0,0001 0,0000

BERD (NUTS 3) -0,157 0,141 0,267 0,098 0,161 0,545 -0,054 0,222 0,808

Size TTO 0,012 0,012 0,314 0,006 0,013 0,616 0,010 0,014 0,497

Scientific Orientation 0,150 0,036 0,000 0,140 0,037 0,000 0,145 0,047 0,002

Arts & Humanities -0,201 0,379 0,596 -0,510 0,430 0,236

Medicine 0,664 0,348 0,056 0,295 0,381 0,440

Engineering 1,051 0,340 0,002 0,576 0,384 0,133

Science 0,494 0,455 0,278 -0,321 0,565 0,570

Belgium 0,483 0,592 0,414

Netherlands -0,439 0,705 0,533

France -0,037 0,600 0,951

Germany – Austria -0,731 0,670 0,276

Scandinavia -2,497 0,752 0,001

Italy -1,356 0,679 0,046

Portugal – Greece -2,009 0,921 0,029

Spain -1,040 0,679 0,126

R-squared 0,407 R-squared 0,534 R-squared 0,737

Adjusted R-squared 0,381 Adjusted R-squared 0,491 Adjusted R-squared 0,683

Log likelihood -276,209 Log likelihood -270,059 Log likelihood -250,975

LR index (Pseudo-R2) 0,100 LR index (Pseudo-R2) 0,120 LR index (Pseudo-R2) 0,182

Observations 95 95 95

Antecedents of Entrepreneurial Performance: Spin Off Activity

NUMBER OF SPIN OFFS B Std. Error Beta t Sig. B Std. Error Beta t Sig B Std. Error Beta t Sig

Constant 0,5179 0,1230 4,2116 0,0001 0,1307 0,2310 0,5656 0,5734 0,7428 0,3398 2,1859 0,0324

#Academic Staff 0,0000 0,0000 0,0284 0,2577 0,7974 0,0000 0,0000 -0,0769 -0,5931 0,5549 0,0000 0,0000 -0,0294 -0,2207 0,8260

BERD (Nuts 3) 0,1148 0,0574 0,2109 1,9987 0,0492 0,1689 0,0640 0,3104 2,6377 0,0102 0,1112 0,0817 0,2043 1,3607 0,1783

Size TTO 0,0174 0,0057 0,3457 3,0638 0,0030 0,0186 0,0059 0,3678 3,1411 0,0024 0,0167 0,0062 0,3304 2,6902 0,0091

Scientific Orientation 0,0341 0,0142 0,2559 2,4055 0,0186 0,0393 0,0157 0,2948 2,5090 0,0143 0,0214 0,0162 0,1606 1,3222 0,1907

Arts & Humanities 0,1136 0,1331 0,1133 0,8532 0,3963 -0,0043 0,1311 -0,0043 -0,0330 0,9738

Medicine 0,0662 0,1412 0,0651 0,4691 0,6404 0,1101 0,1394 0,1083 0,7900 0,4324

Engineering 0,2640 0,1265 0,2427 2,0866 0,0404 0,2333 0,1245 0,2145 1,8735 0,0655

Science 0,0233 0,1555 0,0183 0,1501 0,8811 0,0685 0,1598 0,0537 0,4285 0,6697

Germany – Austria -0,2587 0,2432 -0,1958 -1,0636 0,2915

France -0,6593 0,2293 -0,6060 -2,8754 0,0054

Italy -0,6145 0,2446 -0,4465 -2,5118 0,0145

Spain -0,5648 0,2530 -0,4433 -2,2321 0,0291

Belgium -0,3607 0,2324 -0,2730 -1,5518 0,1256

Scandinavia -0,2064 0,2508 -0,1500 -0,8227 0,4137

Portugal – Greece -0,4237 0,3181 -0,1766 -1,3323 0,1874

Netherlands -0,1830 0,3047 -0,0763 -0,6006 0,5502

R 0,4587 0,5129 0,6531

R Square 0,2104 0,2631 0,4265

Adjusted R Square 0,1694 0,1823 0,2853

Std. Error of the Estimate 0,4130 0,4097 0,3831

Regression Sum of Squares 3,4994 4,3755 7,0931

Residual 13,1318 12,2557 9,5381

Total 16,6311 16,6311 16,6311

Mean Square Regression 0,8748 0,5469 0,4433

Mean Square Residuals 0,1705 0,1679 0,1467

F 5,1297 3,2578 3,0211

Significance 0,0010 0,0032 0,0008

Degrees of freedom model 4 8 16

Total Observations 81 81 81

PATENT ACTIVITY

Neg. Bin.CONTRACT RESEARCH

OLSSPIN OFF ACTIVITY

OLS

B Stand. Err.

WaldChi-Square

Sig.B Stand. Err. t

Sig.B Stand. Err. t

Sig.

Intercept -,766 ,4681 2,674 ,102 6,568*** ,146 45,027 ,000 ,550*** ,143 3,857 ,000

Arts &

humanities = 0

-,139 ,4549 ,094 ,759 -,036 ,144 -,250 ,803 -,098 ,141 -,694 ,490

Medicine = 0 -,031 ,4711 ,004 ,947 ,130 ,147 ,885 ,380 -,035 ,144 -,243 ,809

Engineering = 0 -1,113** ,4670 5,678 ,017 -,216 ,132 -1,634 ,107 -,095 ,129 -,733,466

Science = 0 ,017 ,5146 ,001 ,974 ,078 ,164 ,473 ,638 -,035 ,160 -,216 ,829

TTO size ,013 ,0192 ,484 ,487 ,005 ,006 ,826 ,412 ,018*** ,006 2,984 ,004

Scientific

productivity

,187*** ,0559 11,228 ,001 ,066*** ,018 3,578 ,001 ,033* ,018 1,827 ,072

BERD ,039 ,2232 ,030 ,861 ,046 ,069 ,670 ,506 ,163** ,067 2,421 ,018

Academic staff ,000*** ,0001 11,126 ,001 8,927E-5* 4,802E-5 1,859 ,068 9,852E-6 4,693E-5 ,210 ,834

Spin-offs

(residual)

,378 ,4451 ,722 ,395 ,388*** ,117 3,304 ,002-- -- -- --

Patents

(residual)

-- ----

-- ,010 ,010 1,072 ,288 ,014 ,009 1,498 ,139

Contract

Research

(residual)

,429 ,3988 1,155 ,283 -- -- -- -- ,371*** ,112 3,304 ,002

R-square 0,378 0,381

Adj R-square 0,282 0,286

Likelihood Ratio Chi-square

85,437***

Total obs76 76 76

Major Findings & Intermediate Conclusions

• Overall, our findings reveal that scientific strength (measured by average number of publications of academic staff), is positively related to entrepreneurial performance.

• This effect remains present after introducing moderating variables like size, discipline and the R&D intensity of the regional environment.

• Size and BERD are positively associated with entrepreneurial effectiveness albeit differently for the different entrepreneurial outcomes considered (contract research, patenting and spin off activity).

• Discipline effects are present for spin off activities (engineering) and patent activity (engineering, medicine)

• Finally, our analysis points out considerable country effects, signaling not only the importance of ‘national innovation system’ framework conditions; they also suggest opportunities for growth of science related economical activity within the European Research Arena.

Scientific yield from collaboration with industry:

The relevance of researchers’ Action Strategies

Julie Callaert

Bart Van Looy

Department of Managerial Economics, Strategy and Innovation

Katholieke Universiteit Leuven (Belgium)

[email protected]

Paolo Landoni

Roberto Verganti

Department of Management, Economics and Industrial Engineering

Politecnico di Milano (Italy)

[email protected]



Scientific yield from collaboration with industry: The relevance of researchers’ action strategies

• H1: The scientific yield from collaborative projects is higher for professors that engage in industry collaboration on topics close to their current focus/research agenda.

• H2: The scientific yield from collaborative projects is higher for professors that adopt a pro-active approach.

• H3: The scientific yield from collaborative projects is higher for professors that declare to have a higher level of “selectiveness” in their choice of projects and partners.

Description Source PeriodUniversity KU Leuven (BE) or Politecnico di

Milano (IT)Sample Time of survey

Age Age in 2009 Survey Field Subfields:

- Aerospace- Bioengineering- Chemistry - Civil & Environmental Engineering- Electrical- Energy- Mechanical Engineering- Physics, Astronomy & Computer science

Survey Time of survey

Teamsize Number of researchers (including self, PhD students, postdocs, researcher assistants,…)

Survey Yearly average of period 2003-2007

Scientific productivity Number of published articles ISI Web of Science Yearly average of period 1990-2008

Project publications (scientific yield) Self-reported number of publications resulting from collaborative projects from the past five years

Survey Time of survey

Collaborative strategy: Proactiveness

% of research collaborations with firms that were proposed (initial idea / contact) by the respondent professor or his research team (versus proposed by the firm partner)

Survey 2003-2007

Collaborative strategy: Novelty % of collaborative projects that involve new topics (as opposed to topics from the ongoing or previous research agenda)

Survey 2003-2007

Collaborative strategy: Selectiveness

Frequency of refusals of requests for collaborative projects with industry (on a scale from 1 – never to 5 – frequently)

Survey Period preceding the survey

Budget from collaboration Sum of the budget acquired from research projects directly funded by industrial partners and the budget from research projects with firms funded by competitive programs

Survey 2003-2007

Tests of Between-Subjects Effects Dependent Variable: Scientific Yield from collaborative projects

Source Type III Sum of Squares

df Mean Square F Sig. Param. Estim. (B)

Corrected Model 45,340a 14 3,239 3,061 ,001 Intercept ,052 1 ,052 ,049 ,825 ,129Field 4,613 7 ,659 ,623 ,735 Sci Prod ,243 1 ,243 ,229 ,634 -,135Budget from collaboration 7,437 1 7,437 7,030 ,010 ,278Selectiveness 1,440 1 1,440 1,362 ,248 ,189Novelty 1,464 1 1,464 1,384 ,244 -,007Proactiveness ,280 1 ,280 ,265 ,608 ,003Teamsize 2,917 1 2,917 2,757 ,102 ,042Age ,008 1 ,008 ,007 ,932 -,001Error 67,710 64 1,058 Total 575,778 79 Corrected Total 113,049 78 a. R Squared = ,401 (Adjusted R Squared = ,270)

Tests of Between-Subjects Effects Dependent Variable: Budget from Collaboration Source Type III Sum

of Squaresdf Mean Square F Sig. Param.

Estim. (B)

Corrected Model 121,013a 13 9,309 6,075 ,000 Intercept 3,994 1 3,994 2,607 ,110 3,029Field 39,657 7 5,665 3,697 ,002 Sci Prod 5,823 1 5,823 3,800 ,055 ,557Selectiveness 10,083 1 10,083 6,580 ,012 ,426Novelty ,540 1 ,540 ,352 ,555 ,003Proactiveness 14,506 1 14,506 9,466 ,003 ,015Team size 6,324 1 6,324 4,127 ,046 ,047Age 4,673 1 4,673 3,049 ,085 ,031Error 119,529 78 1,532 Total 3417,941 92 Corrected Total 240,542 91 a. R Squared = ,503 (Adjusted R Squared = ,420)

The impact of legislative framework conditions on the entrepreneurial activities

of universities: an (empirical) assessment

Bart Van Looy&

Martin Meyer

i.c.w.Mariette Du Plessis

Koenraad Debackere

Steunpunt O&O IndicatorenResearch Division INCENTIM

Managerial Economics, Strategy and Innovation Faculty of Economics and Applied Economics

K.U.Leuven

Freeman Research Centre SPRU, University of Sussex

Legitimating Entrepreneurial Agency at the level of Universities: Why? Why not?

• It hampers (science): By legitimating universities as entrepreneurial actors, universities will become too entrepreneurial/commercial. Phenomena like secrecy (e.g. Blumenthal et al., 1996; Campbell & Slaughter, 1999), skewing (shifting from basic to the applied spectrum) and even ‘corporate manipulation efforts’ (Florida & Cohen, 1999; Noble, 1977) might in the medium and long run destroy the values and dynamics of the open science model itself. See in this respect also allegations about the genesis and development of ‘anti-commons’ effects (Heller & Eisenberg, 1998; Nelson, 2004)

• Empirical evidence about such negative dynamics is limited and sometimes contradictory. At the same time, the most recent studies clearly suggest positive effects – on the level of the scientific performance of researchers - when combining entrepreneurial and scientific activities: Van Looy et al. 2004, 2006; Breschi et al., 2005; Calderini et al., 2005; Fabrizio & DiMinin, 2005; Gulbrandsen & Smeby, 2005; Azoulay et al., 2006; Meyer, 2006.

• It doesn’t matter: Other phenomena have contributed to the growth of patent activity at (American) universities: patent law with respect to novel organisms, investment in biomedical research and the growth of research-intensive industries (Mowery et al.2001; Mowery & Sampat, 2005)

Legitimating Entrepreneurial Agency at the level of

Universities: Why? Why not? • It helps:

– Critical for the successful transfer of new scientific/technological knowledge from universities and PRO’s to industry. As such the presence of Bayh-Dole like legislation can become a catalyst (one of the) for economic growth (lack of entrepreneurial orientation of universities in Europe as part of the ‘European Paradox’ phenomenon?)

– Market failures (Arrow,1962) occur when involvement of scientists/inventors is critical for further development towards market exploitation (see Jensen & Thursby, 2003). If scientists/inventors are not acknowledged as ‘owners’, incentives to engage in further development efforts equal voluntarism.

– Hence, granting IP rights can be seen as a way of creating entrepreneurial agency.

– Situating these rights at the level of the principal of the inventors – rather than on the level of individual inventors - might contribute to remedying market failures (risk averseness/resource/capabilities issues). Moreover, such a situation allows to devise accompanying framework conditions that address the co-presence of multiple academic missions (Science, Education & Knowledge Transfer) and related, potential conflicts.

– Situating these rights at levels above the principal of the inventors would only make sense if economies of scale are important; these are however limited (and relate to IP procedures). Moreover, by de-multiplexing relationships, new conflict situations (both within and between involved organizations) can/will arise (e.g. BTG (UK) and NRC (US); see for a revealing account Mowery & Sampat, 2001).

– Notice also that granting rights to universities creates a more transparent ‘market’ situation towards industrial partners; being explicit on the level of terms and conditions not only seems fair from a funding perspective; it might also reduce transaction costs (whether it will actually do, will depend on the behavior of negotiating partners)

Countries under study– Belgium: The governance of Universities has become a regional responsibility (state reform

1991). In Flanders all IP from university researchers belongs to the university. A similar logic has been adopted in 1998 by the French Community.

– Germany: Private and public employer has the rights to patent service inventions; at the same time university professors own the patent rights to university inventions (law on employee inventions 1994). 2001 Reform of Employee Law has rendered university inventions “service inventions” which means they now belong to the university.

– Denmark: Act on Inventions at Public Research Institutions (2000) grants title to PRO but allows inventor right of first refusal. Before 2000 the rights were owned by the researcher/professor.

– Finland: Employer has right to patent, also in the case of PRO. University inventions are notably exceptions: the patent rights belong to the employee (1967). Finland is currently changing its legislation (towards granting rights to universities).

– Sweden : Professor’s privilege.

– Netherlands, France and UK: Three countries in which legislation is general, i.e. universities are considered as employers, which will own the rights on inventions made by staff.

Research Design

• Amount of patent activity undertaken by universities within different countries.

• Identification by means of EPO applications (1978 – 2004) based on the sector allocation methodology developed for Eurostat/Patstat (Van Looy, Du Plessis, Magerman (2006)).

• Allows to calculate the amount of university patent activity over time (absolute/normalized/relative).

• The presence of legislation shifts allows to assess ‘treatment’ effects (before/after).

• Time period: 1990 – 2004/5

• Method: ANCOVA, with country acting as additional variable (Fixed Effect modeling).

• Control variables: BERD, HERD, Year

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003AT 0,5% 1,1% 0,5% 0,2% 0% 0,1% 0,1% 0,2% 0,7% 0,1% 0,4% 0,3% 0,4%AU 6,4% 6,0% 7,0% 7,4% 11,1% 7,3% 7,2% 9,1% 11,5% 7,9% 6,3% 9,2% 6,6%BE 3,1% 1,7% 2,9% 2,0% 3,3% 6,2% 6,6% 8,6% 10,2% 11,1% 11,1% 10,6% 12,6%CA 4,8% 7,3% 8,5% 6,7% 7,3% 8,9% 9,3% 9,1% 8,2% 7,1% 7,0% 6,5% 6,1%CN 13,0% 16,0% 13,6% 16,1% 12,9% 6,0% 9,3% 6,3% 2,8% 4,0% 9,0% 9,0% 4,2%CZ 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 7,0% 2,3% 0%DE 0,1% 0,1% 0,1% 0,2% 0,1% 0,2% 0,2% 0,2% 0,2% 0,3% 0,3% 0,5% 0,6%DK 0% 0,3% 0,5% 0,9% 0,4% 0,4% 0,2% 0,5% 0,8% 0,7% 1,6% 2,4% 1,9%ES 0,4% 2,2% 2,6% 1,8% 2,5% 3,4% 3,6% 3,4% 2,7% 5,7% 4,4% 6,6% 4,0%FI 0% 0% 0,2% 0,3% 0,3% 0,5% 0,4% 0,3% 0,1% 0,1% 0% 0% 0%FR 0,4% 0,3% 0,6% 0,5% 0,3% 0,4% 0,4% 0,4% 0,6% 0,8% 1,0% 1,6% 1,4%GB 1,8% 1,7% 2,2% 2,5% 3,6% 3,1% 3,5% 4,1% 5,0% 5,0% 5,2% 5,8% 5,8%GR 0% 0% 0% 0% 0% 4,3% 0% 3,8% 0% 0% 3,4% 0% 0%HK 0% 0% 0% 0% 0% 0% 0% 15,4% 7,0% 3,7% 5,9% 5,0% 11,5%HU 0% 0% 0% 0% 0% 0% 0% 0% 0% 1,4% 0% 0% 3,6%IE 6,3% 2,8% 1,0% 0% 4,9% 1,6% 2,5% 4,3% 5,5% 7,5% 3,8% 3,9% 3,2%IT 0,1% 0,2% 0,3% 0,2% 0,4% 0,3% 0,4% 0,5% 0,5% 1,1% 1,0% 1,4% 1,2%JP 0,1% 0,1% 0% 0% 0,1% 0,1% 0,1% 0,1% 0,1% 0,3% 0,3% 0,4% 0,5%KR 0% 0% 0% 0% 0% 0,2% 0,2% 0,3% 0,8% 1,5% 2,1% 1,4% 0,6%LU 3,5% 0% 0% 1,8% 0% 0% 0,9% 1,6% 0% 0,0% 0% 0% 0%NL 0,6% 0,4% 1,0% 0,5% 1,1% 1,1% 1,7% 2,1% 2,1% 2,0% 1,5% 1,3% 1,8%NO 0% 0% 0% 0% 0,5% 0% 0% 0,6% 0% 0,3% 0% 0,6% 0%PL 12,5% 14,3% 0% 10,0% 0% 0% 10,5% 10,0% 4,3% 3,4% 0% 0% 3,3%PT 0% 0% 0% 5,6% 0% 0% 4,5% 0% 2,9% 2,9% 2,3% 6,9% 3,8%SE 0,4% 0,2% 0,1% 0,1% 0,1% 0,2% 0,1% 0% 0,1% 0% 0% 0,04% 0%SG 50% 10% 19% 5% 0% 8% 4% 5% 4% 7% 10% 16% 8%SI 14,3% 0% 0% 5,3% 0% 0% 0% 0% 0% 0% 6,9% 5,3% 0%US 3,2% 3,2% 3,5% 4,0% 3,6% 4,5% 4,8% 4,7% 4,7% 4,2% 4,6% 4,0% 3,0%Grand Total 1,3% 1,3% 1,5% 1,7% 1,7% 2,0% 2,1% 2,2% 2,3% 2,2% 2,3% 2,2% 1,8%

Increase in Patent Activity when changing legislation?

IP Rights Mean Std. Deviation N

Employee has right to patent invention ,6918 ,93124 24

Employer has right to patent invention 4,9846 4,66603 17

Total 2,4717 3,71375 41

Source Type III Sum of Squares df Mean Square F Sig.

Corrected Model 291,330(a) 4 72,833 10,071 ,000

Intercept 2,070 1 2,070 ,286 ,596

HERD 14,562 1 14,562 2,014 ,164

GERD 51,292 1 51,292 7,093 ,012

Year 2,433 1 2,433 ,336 ,566

IP Rights 96,635 1 96,635 13,362 ,001

Error 260,346 36 7,232

Total 802,161 41

Corrected Total 551,676 40

a R Squared = ,528 (Adjusted R Squared = ,476)

Increase in Patent Activity when changing legislation?

Source Type III Sum of

Squares df Mean Square F Sig.


Intercept 2,200 1 2,200 ,789 ,381

HERD 2,713 1 2,713 ,973 ,331

GERD 15,333 1 15,333 5,502 ,025

Year 2,287 1 2,287 ,821 ,372

IP Rights 11,107 1 11,107 3,986 ,054

Country 93,734 2 46,867 16,818 ,000

IP Rights * Country 74,305 2 37,152 13,332 ,000

Error 89,174 32 2,787

Total 802,161 41


R Squared = ,838 (Adjusted R Squared = ,798)

Intermediate Conclusion:

Changing the legislation results in more patent activity of universities.

Increase range between 250% (Germany) and 500% (Denmark) (Belgium: 300% increase)

Do we really need a university tailored legislative approach?

Extending the dataset with countries that:

a) opt for “professor’s privilege” : Sweden and Finland

b) do not provide specific - ‘tailor made’ - IP legislation for HEI but apply a broader, ‘employer’ oriented IP legislative framework: UK, France, Netherlands.

IP Rights Mean Std. Deviation N

Employee has right to patent invention

,4630 ,72297 47

Employer has right to patent invention

4,9846 4,66603 17

General Employer Oriented IP 1,7193 1,45154 45

Do we really need a university tailored legislative approach?

Source Type III Sum of Squares

df Mean Square F Sig.


Intercept 15,105 1 15,105 9,221 ,003

HERD 4,406 1 4,406 2,690 ,104

GERD ,174 1 ,174 ,106 ,745

Year 15,458 1 15,458 9,436 ,003

IP Rights 41,105 1 41,105 25,091 ,000

Country 174,400 6 29,067 17,743 ,000

IP Rights * Country 68,486 2 34,243 20,903 ,000

Error 155,630 95 1,638

Total 1030,578 109



Intermediate Conclusion: Specific HEI centered legislative frameworks seem to have an impact beyond general ‘employer’ oriented IP regulations.

Is this increase of university patenting activity resulting in effects elsewhere (patenting at the company level and/or by individuals)?

Patents held by Individuals Type III Sum of Squares



Intercept ,004 1 ,004 ,014 ,905

HERD 2,627 1 2,627 10,429 ,003

GERD 1,806 1 1,806 7,173 ,012

Year ,003 1 ,003 ,013 ,910

IP Rights ,435 1 ,435 1,726 ,198

Country 6,907 2 3,454 13,713 ,000

IP Rights * Country ,544 2 ,272 1,080 ,352

Error 8,059 32 ,252

Total 84,056 41




Patents held by Companies Type III Sum of



Intercept 1894,375 1 1894,375 1,325 ,258

HERD 8868,996 1 8868,996 6,203 ,018

GERD 6063,977 1 6063,977 4,241 ,048

Year 1876,956 1 1876,956 1,313 ,260

IP Rights 1017,819 1 1017,819 ,712 ,405

Country 1196,766 2 598,383 ,418 ,662

IP Rights * Country 275,610 2 137,805 ,096 ,908

Error 45756,014 32 1429,875

Total 578011,913 41




Patents held by Individuals Type III Sum of



Intercept 5,829 1 5,829 8,700 ,004

HERD ,407 1 ,407 ,607 ,438

GERD ,005 1 ,005 ,007 ,931

Year 5,941 1 5,941 8,868 ,004

IP Rights ,367 1 ,367 ,548 ,461

Country 213,960 6 35,660 53,227 ,000

IP Rights * Country ,715 2 ,358 ,534 ,588

Error 63,647 95 ,670

Total 715,467 109




Company held patents Type III Sum of



Intercept 14621,205 1 14621,205 8,140 ,005

HERD 23227,458 1 23227,458 12,932 ,001

GERD 62130,520 1 62130,520 34,592 ,000

Year 14485,254 1 14485,254 8,065 ,006

IP Rights 4380,411 1 4380,411 2,439 ,122

Country 157179,891 6 26196,648 14,585 ,000

IP Rights * Country 101,910 2 50,955 ,028 ,972

Error 170631,319 95 1796,119

Total 1829193,277 109



A closer look at potential ‘crowding out’ dynamics: The case of Flanders

– 1991: Flemish government defines and anchors the triple mission of universities (Decree 12 June 1991) : Education, Research and Scientific services. All three areas are considered as of equally importance.

– Decree of 22 February 1995 defines boundaries and conditions pertaining to scientific services (authorization as well as pricing principles reflecting full cost principles).

– This decree has been complemented in 1998 (14 July 1998) on the level of ownership rights pertaining to inventions resulting from academic research. Exploitation rights are granted to the university.

– The university has to ensure that inventive activities do not jeopardize research and education. In addition each university has to install procedures that result in a fair return for researchers and research groups.

Academic Patent Activity Flanders1991-2001

EPO USPTO

APY Patents assigned to Flemish universities

Patents identified as invented by university researchers

Total number of patents related to Flemish Universities

Patents assigned to Flemish universities

Patents identified as invented by university researchers

Total number of patents related to Flemish Universities

1991 7 13 20 1 15 16

1992 2 10 12 7 18 25

1993 5 9 14 3 19 22

1994 2 10 12 6 33 39

1995 3 10 13 24 57 81

1996 3 10 13 3 51 54

1997 2 4 6 10 42 52

1998 0 4 4 8 41 49

1999 0 0 0 5 39 44

2000 0 0 0 1 7 8

2001 0 0 0 0 1 1

Total 24 70 94 68 323 391

Average 2,18 6,36 8,55 6,18 29,36 35,55

ANOVA Results Before/After Decree 1996

Type III Sum of Squares



Hoofdeffecten Intercept 10748,869 1 10748,869 160,132 ,000 Periode (Voor/Na decreet 1995)

173,804 1 173,804 2,589 ,114

Applicatie/Grant 672,400 1 672,400 10,017 ,003 Universiteit Aanvrager (J/N)

543,657 1 543,657 8,099 ,006

Patent Systeem (EPO/USPTO)

2190,400 1 2190,400 32,632 ,000

Interactie-effecten Periode * Applicatie/Grant

372,100 1 372,100 5,543 ,023

Periode * Universiteit Aanvrager

324,188 1 324,188 4,830 ,033

Periode * patent_system 129,600 1 129,600 1,931 ,171 Universiteit Aanvrager * Patent Systeem

1081,600 1 1081,600 16,113 ,000

Applicatie/Grant * Universiteit Aanvrager

592,900 1 592,900 8,833 ,005

Periode * Applicatie/Grant * Universiteit Aanvrager

730,133 1 730,133 10,877 ,002

Periode * Applicatie/Grant * Universiteit Aanvrager * Patent Systeem

129,600 1 129,600 1,931 ,171

Error 3222,000 48 67,125 Total 19956,000 60 Corrected Total 10779,933 59

0

5

10

15

20

25

30

35

Before After

Legislation Change

Pat

ent

Act

ivit

y (Y

earl

y av

erag

e)

Company

University

Total

Conclusion

• Legislative framework conditions affect universities‘ patent behavior.

• If one aims to stimulate technological activities of universities, HEI-specific legislative frameworks - that legitimates entrepreneurial agency on the level of universities - seems most effective.

• Such a HEI specific legislation seems also appropriate to address potential conflicts of interest:

– Within HEI: reconcile multiple missions without jeopardizing the openess required for science and education– Within innovation systems:

• foster and develop constructive, complementary, relationships between science-industry • safeguard the prevalence of the scientific commons: e.g. Providing research or even humanitirian exemptions, define terms and conditions in terms

of pricing practices/fair use of gains (see also Nelson, 2004; Boettiger & Bennett, 2005)

• Notice that for the countries under study going through a change of legislation, we did not observe “crowding out“ effects (towards Individuals/Companies).

• Rather, our findings suggest a NET positive effect in terms of technology production.

• As one observes huge differences between EU-countries, our findings also suggest room for improvement: rather than debating whether we need Bayh-Dole like legislation in Europe, defining and implementing a HEI specific legislative approach that transcends potential unintended (negative) consequences seems the relevant priority.

Collaboration with Universities: Firm LevelFaems D., Van Looy, B. & Debackere K. (2005) - Journal of Product Innovation Management

Variable Estimate St Error Chi-Square Pr > ChiSq Label Intercept 0.214 0.052 16.739 0.00 Subsidiary -0.044 0.024 3.519 0.06 Ln(Size) -0.010 0.008 1.433 0.23 Textile, Fur, Leather 0.099 0.056 3.149 0.08 Wood & Paper 0.050 0.057 0.790 0.37 Chemicals and Pharmaceuticals

-0.020 0.042 0.239 0.63

Metals and Manufacturing -0.004 0.044 0.010 0.92 Machines 0.036 0.045 0.639 0.42 Electrical Equipment 0.053 0.045 1.421 0.23 Transport 0.073 0.053 1.892 0.17 Furniture 0.053 0.073 0.527 0.47 R&D Intensity 0.233 0.187 1.565 0.21 Appropriation Effort 0.059 0.022 6.830 0.01

σ-Collaborations 0.016 0.006 7.614 0.01 Number of Obs.: 221 Censored observations: 6 Noncensored observations: 215 LR chi2: 37.56 Prob > chi2: < 0.005 Pseudo R2: 0.148

Factor 1 Factor 2 # Customer Collaborations .209 .873 # Supplier Collaborations .343 .772 # Universities collaborations .867 .319 # Research Institute Collaborations .897 .249 Number of observations: 221 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Kaiser-Meyer-Olkin Measure of Sampling Adequacy: 0.745 Bartlett’s Test of Sphericity: Approx. Chi-Square: 321.229 Sig: < 0.000

Towards a Portfolio Approach: Impact on improving existing products versus creating

new products(Faems et al., 2005)

Variable Estimate St Error Chi-Square Pr > ChiSq Label Intercept 0.108 0.047 5.244 0.02 Subsidiary -0.043 0.020 4.399 0.04 Ln(Size) -0.002 0.007 0.075 0.79 Textile, Fur, Leather 0.060 0.048 1.555 0.21 Wood & Paper -0.010 0.050 0.038 0.85 Chemicals and Pharmaceuticals

-0.018 0.037 0.249 0.62

Metals and Manufacturing 0.021 0.039 0.291 0.59 Machines 0.048 0.039 1.507 0.22 Electrical Equipment 0.046 0.039 1.359 0.24 Transport 0.028 0.046 0.365 0.55 Furniture 0.026 0.064 0.164 0.69 R&D Intensity 0.114 0.163 0.489 0.48 Appropriation Effort 0.022 0.019 1.269 0.26

# Exploitation-oriented collaborations

0.026 0.007 12.731 0.00

# Exploration-oriented collaborations

-0.008 0.009 0.790 0.37

Number of Obs.: 221 Censored observations: 179 Non-censored observations: 42 LR chi2: 31.56 Prob > chi2: <0.025 Pseudo R2: 0.125

Variable Estimate St Error Chi-Square Pr > ChiSq Label Intercept 0.102 0.036 8.217 0.00 Subsidiary 0.004 0.016 0.077 0.78 Ln(Size) -0.017 0.006 8.665 0.00 Textile, Fur, Leather 0.054 0.037 2.134 0.14 Wood & Paper 0.058 0.038 2.357 0.12 Chemicals and Pharmaceuticals

0.005 0.028 0.037 0.85

Metals and Manufacturing -0.017 0.030 0.316 0.57 Machines -0.007 0.030 0.054 0.82 Electrical Equipment 0.018 0.030 0.352 0.55 Transport 0.068 0.035 3.720 0.05 Furniture 0.042 0.047 0.804 0.37 R&D Intensity 0.094 0.122 0.584 0.45 Appropriation Effort 0.052 0.014 12.785 0.00

# Exploitation-oriented collaborations

0.008 0.005 2.392 0.12

# Exploration-oriented collaborations

0.015 0.006 5.290 0.02

Number of Obs.: 221 Censored observations: 43 Non-censored observations: 178 LR chi2: 45.66 Prob > chi2: <0.005 Pseudo R2: 0.171

Myths versus Realities (Van Looy/Piccaluga/Debackere)

Entrepreneurial activities hamper science.

Scientific capabilities (eminence) are the engine of entrepreneurial performance.

TTO’s are crucial to arrive at scale/scope of technology transfer activities (TTO’s are the ‘engine’ behind the third mission).

Distributed entrepreneurial efforts (within the university) benefit from the presence of specialized support staff and a strategic vision/commitment at the level of the top (of universities) (our ‘internal triple helix’).

Entrepreneurial activities generate a substantial share of funding for universities (allowing to decrease over time more traditional types of university funding).

Universities will always require funding for research (market failures) and education (as long as we organize it as a ‘public good’). Entrepreneurial activities of universities could/should not be organized for monetary purposes only.

A more entrepreneurial orientation of universities will be beneficial for all kind of industries and all kind of R&D/Innovation challenges.

The specific role of universities within innovation systems is situated in the vicinity of ‘market failures’

‘Bayh Dole’ type of legislations are not relevant (or even harmful).

To the extent IP rights are essential to operate they are best situated at the level of the principal (University/Faculty/Department) while agents (academic staff) should be considered as entrepreneurial (and hence incentivized as such)

Documents

Entrepreneurial Universities An Overview & Reflection Prof. Bart Van Looy 27.05.15 Managerial Economics, Strategy and Innovation (Chair) Faculty of Business