1. THE EFFECTIVENESS OF UNIVERSITY KNOWLEDGE SPILL-OVERS: PERFORMANCE DIFFERENCES BETWEEN UNIVERSITY SPIN-OFFS AND CORPORATE SPIN-OFFS Karl Wennberg Stockholm School of Economics & Ratio Johan Wiklund Syracuse University Mike Wright CMBOR & EMLyon

2. Context

3. The Bayh-Dole Act of 1980 “ A wealth of scientific talent at American colleges and universities – talent responsible for the development of numerous innovative scientific breakthroughs each year – is going to waste as a result of bureaucratic red tape and illogical government regulations…What sense does it make to spend billions of dollars each year on government-supported research and then prevent new developments from benefiting the American people because of dumb bureaucratic red tape?” U.S. Senator Birch Bayh, 1980

4. Unversities own the Intellectual Property (IP) generated through university research

5. Bayh-Dole implications Creation of Technology Transfer Offices (TTO) Explosion of university patent activity

6. University Patents as a Share of All Patents with Domestic Assignees

7. How does knowledge spill over from universities?

8. Knowledge spill-over through entrepreneurship? AUTM reports annual mean of 426 startups from U.S. Universities, 1998-2004 MIT TTO reported 29 startups (2001) Stanford TTO reported 6 startups (2001) Based on AUTM data, one startup generated per $368 million of R&D

9. Broader perspective needed

10. Our paper How does knowledge spill over from universities through entrepreneurship?

11. Steve graduates from Stanford, works at Stanford, spins off a company

12. Lisa graduates from Stanford, works at Fairchild, spins off a company

13. To date we have focused on the Steves of the world but not the Lisas

14. Unfortunate

15. Much entrepreneurship is probably carried out by the Lisas

16. Even if we are mainly interested in the Steves, the Lisas provide a relevant baseline for comparison

17. We suggest both Steve and Lisa represent university knowledge spill-over through entrepreneurship They differ in terms of their experience

18. Both Steve and Lisa hold unique knowledge that can be valuable for knowledge-intensive entrepreneurship

19. Ranked #1 worldwide for publications in academic entrepreneurship Which path to entrepreneurship is more productive?

20. Ranked #1 worldwide for publications in academic entrepreneurship How does experience inside/outside university influence subsequent spin-off performance?

21. Ranked #1 worldwide for publications in academic entrepreneurship University spinoffs (USOs) Corporate spinoffs (CSOs)

22. Individuals with University Degree Company Entrepreneur Performance University

23. Gap Academic entrepreneurship literature emphasizes venture creation – Not subsequent performance Little attention to indirect spillover from university to entrepreneurship – CSOs provide alternative mechanism to USOs Policies to stimulate USOs has not used suitable baseline Comparison of USOs to CSOs relevant

24. Performance differences Potential for successful entrepreneurship depends on technological and market knowledge Prior experience of customer relationships essential to generate market knowledge – More likely in commercial environment than university CSOs have greater exposure to commercial interaction and thus greater market knowledge H1: Firms started by university graduates as commercial spin-offs perform better than firms started by university graduates as university spin- offs.

25. Knowledge Sources Schooling: Increases general human capital Prior industry experience: provides relevant product related knowledge Previous entrepreneurial experience: Specific knowledge of running a business CSO founders complement university knowledge with market knowledge unlike USO founders Prior industry experience, schooling and entrepreneurial experience can compensate for lack of market knowledge This compensation more valuable to USOs than to CSOs H2: Firms started by university graduates as university spin-offs benefit more from the knowledge sources [a] years of education, [b] years of industry experience in the same sector, [c] years of entrepreneurial experience, than firms started by university graduates as commercial spin-offs.

26. Parent organizational context We build on the spawning literature Examines entrepreneurship depending on parent organization characteristics spin-offs usually inherit both general technological and market-related knowledge from their parents We suggest there are important differences between university context and corporate context that influences spin- off performance

27. Parent organizational context University technological knowledge broad but far from market Corporate technological knowledge narrow and closer to market  CSOs more affected by parent knowledge Universities generally bureaucratic  USOs less affected by parent organization Large corporations especially those with many divisions have spawnable activities that are peripheral and difficult to control and incentivize yet which may have good underlying performance prospects H3: Firms started by university graduates as commercial spin-offs benefit more from the spawning environments of the parent organization (size and breadth of technological knowledge) than firms started by university graduates as university spin-offs

28. Research design Symmetric data on USOs and CSOs Follow firms from inception and onwards Performance data that are robust across industries Data from Sweden – Complete data – IP remains with inventor for USOs

29. Data I Official data maintained by Statistics Sweden Annual observations, great detail All private incorporated companies started in Sweden 1994-2001 in knowledge-intensive sectors – Excluded other sectors and legal forms – Ensures relevance Match with individual data on founders Individuals completing university degree lasting at least 3 years in any field Worked for university or a private company at least some time in 1993-2000 Leave employer at T and start firm at T+1 – USO if employer = university – CSO if employer = private firm

30. Data II Must hold majority stake in first year and work there full time. Team spinoffs require that 50% or more work at same employer at T Identified 528 USOs (6%), 8,663 CSOs (94%)

31. Dependent variable Three different indicators of performance – Employment growth – Sales growth – Survival [discontinued, excluding M&A]

32. Independent Variables Design allows detailed assessment of human capital – Entrepreneurial experience (team mean) – Same industry experience (team mean) – Education length (team mean) Parent organization – Revenues – Employment – # establishments – Share of employees with engineering degree – Share of employees with PhD

33. Control Variables Team size Capital invested Social capital (prior years in location where business was started; Industry affiliation (ISIC 3-digit level)

34. Industry of spinoffsAcademic SpinoffsCorporate Spinoffs Chemicals and fibre manufacturing0.30%0.19% Electrical and optical equipment2.37%3.42% Transport equipment0.30%0.12% Networks, radio and TV2.96%2.27% Finance4.44%4.65% Real estate business0.31%12.07% Computers/software19.53%16.25% Research and Development11.54%1.18% Accounting / auditing3.25%6.16% Construction / engineering5.03%11.09% Advertising3.25%7.78% Management consulting19.53%14.30% Law firms1.18%5.03% Other consulting services3.25%6.82% Education13.30%0.02% institutions (elderly/children/care)0.30%1.64% Private Health care4.14%5.14% News and entertainment5.03%1.86%

35. Analyses Random effects generalized least squares regression for growth DVs Cox regression for survival

36. Dependent variables Survival Emp growth Sales growth H1CSOs outperform USOs Supported H2 (a) Education matters more for USOsnot supported (b) Ind Exp matters more for USOsSupported weak support (c) Ent Exp matters more for USOsSupported H3 Employment size matters more for CSOs Supported weak support Revenue size matters more for CSOsSupported # Establishments matters more for CSOs Supported # Engineers matters more for CSOsweak supportSupported # PhDs matters more for CSOsSupported not supported

37. Conclusions & Implications CSOs outnumber USOs 14 to 1 and perform better – Universities educate people who become entrepreneurs but mainly indirectly – CSOs seem to be good mechanism for knowledge-intensive entrepreneurship – Why assign policies that single out and support USOs? USOs benefit more from entrepreneurial and industry experience – Connecting USO entrepreneurs to experienced people could be important task for TTO – Do TTOs have expertise to build these teams? Parent size has positive effect on CSO performance – Large firms seems like good seed bed for spinoffs

38. Policy Implications Implications for IP policy – Broader view of university knowledge spillover Assist USOs in building viable teams with commercial experience to succeed – TTO competence needs augmentation Wider policy debate on how knowledge spills over into new organizations – Policy support to facilitate spinning out from established organizations?

39. Policy Implications Why exclusive policy focus on entrepreneurs who work at universities? – Realizing growth among knowledge-intensive firms involves general problems that apply to the whole population of spinoffs – Policy favoring the establishment of growth-oriented entrepreneurship in general, not just USOs?