University Entrepreneurship & Regional Economic Development. David B. Audretsch

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1 University Entrepreneurship & Regional Economic Development David B. Audretsch

2 The Traditional University The Humboldt Model (Wilhelm von Humboldt, ) Freedom & independence of research & teaching knowledge for its own sake Little valuation for engagement & societal impact

3 Role of University in the Solow Economy Limited contribution for investment in physical capital Limited link to (exogenous) knowledge Contribution in terms of social and political values Limited contribution to economic development

4 Role of University in the Romer Economy Competitiveness Crisis of 1970s Comparative advantages shifts from physical capital of knowledge University is source of knowledge University financial shortfall Demand oriented

5 The Knowledge Filter 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

6 The Bayh-Dole Act of 1980 Penetrate the Knowledge Filter Creation of the Technology Transfer Office (TTO) Most studies analyzing commercialization of university research limited to measures of what the TTO does Intellectual property disclosed to and registered by TTO may lead to systematic underestimation of commercialization and innovation emantating from university research (Thursby & Thursby, 2005; Shane, 2004)

7 Emergence of Entrepreneurial University Facilitate knowledge spillovers from university University as solution provider user oriented fields and programs (i.e. biochemistry, informatics) Demand orientation rather than knowledge for its own sake Provision of conduits for knowledge spillovers technology transfer offices, incubators, science parks, sponsored research

8 En trepren eu ria l Un ivers ity X X X X

9 Share % University Patents as a Share of All Patents with Domestic Assignees University Patent Issue Year (Mowery 2005)

10 University of California University of Texas University of Wisconsin Cornell University Harvard University State University of New York Michigan State University Duke University University of Maryland System University of Southern California University of Utah Iowa State University Yale University University of Massachusetts University of Kentucky Emory University University of Arkansas University of Nebraska Thomas Jefferson University University of Connecticut University of Tennessee University of Missouri Brown University University of Oklahoma Rensselaer Polytechnic Institute University of Medicine and Dentistry University of Cincinnati Auburn University Washington State University University of Hawaii Colorado State University University of Houston New Jersey Institute of Technology Tulane University Distribution of University Patents Number of patents issued from 1998 to 2008 Number of patents

11 Disappointing Assessment of Technology Transfer

12 Paucity of University Entrepreneurship? AUTM reports annual mean of 426 startups from U.S. Universities MIT TTO reported 29 startups Stanford TTO reported 6 startups Based on AUTM data, one startup generated per $368 million of R&D

13 Has University Entrepreneurship been Underestimated? Most studies analyzing commercialization of university research limited to measures of what the TTO does Intellectual property disclosed to and registered by TTO may lead to systematic underestimation of commercialization and innovation emantating from university research (Thursby & Thursby, 2002, Who Is Selling the Ivory Tower? Management Science; Shane, 2004, Technological Opportunities and New Firm Creation, Management Science)

14 Technology Transfer Office Mission Statements Primary objectives of the UTTO Percentage of times appeared in mission statement (%) Licensing for royalties IP protection/management Facilitate disclosure process Sponsored research and assisting inventors Public good (disseminate information/technology Industry relationships Economic development (region, state) Entrepreneurship and new venture creation N = 128 TTOs. Source: G. Markman, P. Phan, D. Balkin & P. Gianiodis, Entrepreneurship and University-Based Technology Transfer, Journal of Business Venturing, 2005

15 Making the switch from science to business Nature

16 Asking What Scientists Do Not What the University Does 16,693 scientists awarded National Cancer Institute (NCI) grant, (top 20%) $5,350 million NCI grant awards NCI awards matched to patents 398 distinct patentees, (1,204 patents), in 4 scientists started new business Aldridge & Audretsch, The Bayh-Dole Act and Scientist Entrepreneurship, Research Policy, 2011.

17 Scientist Entrepreneurship Measurement of scientist entrepreneurship by AUTM & university TTO s may underestimate extent of scientist entrepreneurship Based on AUTM data, one startup generated per $368 million of R&D Aldridge & Audretsch (Research Policy, 2011) implies one startup generated per $12 million of R&D

18 Limitations of Previous Research on Scientist Entrepreneurship Limited to a single field of science cancer research Limited to the highest performing scientists Unanswered questions To what extent is the high rate of entrepreneurial activity exhibited by the high performing cancer research scientists prevalent across different types of scientific fields for different types of scientists? -- To what extent do the main determinants of scientist entrepreneurship hold across different scientific fields & heterogeneous types of scientists?

19 Scientist Entrepreneurship: Does the Scientific Field Make a Difference? Taylor Aldridge, David B. Audretsch &Venkata Nadella Ask What Scientists Do & Not What the TTO Does to Commercialize Research Move Beyond Traditional Individual-Specific Characteristics in Explaining Propensity for Scientist to Engage in Entrepreneurship Move Beyond University Characteristics in Explaining Scientist Commercialization Why & How Do Scientists Become Entrepreneurs?

20 Creating a Scientist Entrepreneurship Database Web of knowledge database contained addresses of 9361 scientists that received NSF funding between 2005 and 2012-Q2. Online survey questionnaire directed to the entire population of 9361 scientists in the first round of survey administration 30 scientists were on sabbatical, 9 scientists were inactive, and addresses of 172 scientists were returned since they were incorrect/incomplete. Survey sample of 9150 scientists (97.75 percent of the population

21 Creating a Scientist Entrepreneurship Database Scientists spanned 6 different fields of research, 1899 scientist responses (response rate of 20.75%) from three rounds of administering questionnaire

22 Hypothesis 1: Age is positively related to the propensity for scientists to become an entrepreneur For general entrepreneurship literature, age has negative impact on entrepreneurship (Parker, 2010, The Economics of Entrepreneurship, Oxford University Press; Reynolds, Carter, Gartner & Greene (2004) The Prevalence of Nascent Entrepreneurs in the United States: Evidence from the Panel Study of Entrepreneurial Dynamics, Small Business Economics) Levin and Stephan, (1991), Research Productivity Over the Life Cycle; Evidence for Academic Scientists, American Economic Review; Stephan, Paula., & Levin, Sharon (1992), Striking the Mother Lode in Science: the Importance of Age, Place, and Time, Oxford University Press

23 Hypothesis 2: Female scientists less likely to be an entrepreneur Studies from general population find likelihood of female entrepreneurship lower than male entrepreneurship (Minniti & Nardone (2007) Being in Someone Else s Shoes: The Role of Gender in Nascent Entrepreneurship, Small Business Economics) Aldridge & Audretsch (2011) find no difference for gender for cancer scientists

24 Hypothesis 3: The propensity for a scientist to become an entrepreneur is positively related to human capital Positive relationship found between human capital and entrepreneurship for general population (Davidsson & Honig (2003) The role of Social and Human Capital among Nascent Entrepreneurs, Journal of Business Venturing) Aldridge & Audretsch (2011) find human capital to have no impact on scientist entrepreneurship for cancer researchers

25 Hypothesis 4: Social capital is positively related to the propensity for a scientist to become an entrepreneur Positive relationship found between social capital and entrepreneurship for general population (Aldrich & Martinez (2010), Entrepreneurship as Social Construction, in Handbook of Entrepreneurship) Mosey & Wright, Michael (2007) From Human Capital to Social Capital: A Longitudinal Study of Technology Based Academic Entrepreneurs, Entrepreneurship Theory and Practice and Aldridge & Audretsch (2011) find social capital to be most important determinant of scientist entrepreneurship for cancer researchers

26 Hypothesis 5: Scientist entrepreneurship is positively related to the resources available to the technology transfer office Clarysse, Wright, Lockett, Van de Velde, & Vohora (2005) Spinning Out New Ventures: A Typology of Incubation Strategies from European Research Institutions, Journal of Business Venturing Di Gregorio & Shane (2003), Why Some Universities Generate More TLO Start-Ups than Others?, Research Policy

27 Hypothesis 6 Access to financial resources is positively related to scientist entrepreneurship For general population, access to financial resources found to have positive impact on entrepreneurship (Gompers &Lerner (2010), Equity Financing, in Handbook of Entrepreneurship Research) Access to financial resources positively influences entrepreneurship for high-tech & knowledge industries (Kerr & Nanda (2009) Financing Constraints and Entrepreneurship, National Bureau of Economic Research Working Paper

28 Creating a Scientist Entrepreneurship Database Web of knowledge database contained addresses of 9361 scientists that received NSF funding between 2005 and 2012-Q2. Online survey questionnaire directed to the entire population of 9361 scientists in the first round of survey administration 30 scientists were on sabbatical, 9 scientists were inactive, and addresses of 172 scientists were returned since they were incorrect/incomplete. Survey sample of 9150 scientists (97.75 percent of the population

29 Creating a Scientist Entrepreneurship Database Scientists spanned 6 different fields of research, 1899 scientist responses (response rate of 20.75%) from three rounds of administering questionnaire

30 Percent Scientist Startups 30% Scientist Startups by Field of Research 25% 23,8% 20% 20,1% 15% 12,8% 10% 9,2% 8,2% 6,2% 5% 4,6% 0% All Fields of Research Civil, Mechanical, and Manufacturing Innovation Environmental Biology Computer and Network Systems Physical Oceanography Particle and Nuclear Astrophysics Biological Infrastructure

31 Age of Scientists who Started Up 50 Scientist Age and Startup Commercialization , , ,1 44, , ,0 42, All Fields of Research Civil, Mechanical, and Manufacturing Innovation Environmental Biology Computer and Network Systems Physical Oceanography Particle and Nuclear Astrophysics Biological Infrastructure

32 Percent Startups by Gender 30% Scientist Startups and Gender 25% 25% 20% 19% 15% 13% 10% 5% 5% 9% 5% 7% 8% 4% 7% 10% 9% 6% 0% All Fields of Research Civil, Mechanical, and Manufacturing Innovation 0% Environmental Biology Computer and Network Systems Physical Oceanography Particle and Nuclear Astrophysics Biological Infrastructure Male Scientists Female Scientists

33 Scientist Characteristics, Years in Tenured Status Total Sample Started Up Non- Tenured Scientists % Tenure Scientists 0-5 Years % 6-10 Years % Years % Years % Years % Years % % More than 35 Years % Total

34 Percent Scientists on a Board 80% Scientists on Board of Directors of other firms 75% 70% 71% 60% 64% 62% 59% 58% 59% 50% 40% 39% 38% 30% 31% 26% 25% 32% 20% 20% 10% 0% All Fields of Research Civil, Mechanical, and Manufacturing Innovation Environmental Biology Computer and Network Systems Physical Oceanography Particle and Nuclear Astrophysics Biological Infrastructure Started Up Did Not Startup

35 Percent Scientist Startups by Region 35% Share of Scientist Startups by Region 30% 28,9% 27,6% 25% 23,8% 20% 19,7% 15% 11,3% 10% 9,2% 8,4% 5% 4,6% 5,0% 4,6% 0%

36 Table 8: Probit regression results estimating likelihood of scientist startups, all fields of research Independent variables (1) (2) (3) (4) Grant Amount (in millions) - Fin Res (1.85)* (2.07)** (2.04)** (2.13)** Other Funding (>750K) - Fin Res (2.69)*** (2.27)** (2.36)** (2.46)** # of Students - Human Res (-1.95)* (-1.88)* (-1.89)* (-2.03)** Years in Tenure - Human Capital (-1.46) (-1.45) (-1.32) (-1.27) Full Professor - Human Capital (-1.33) (-1.23) (-1.26) Board Membership - Social Capital (5.30)*** (5.26)*** (5.06)*** (5.19)*** Dept. Encourages Commercialization (-4.14)*** (-4.07)*** (-4.24)*** (-4.47)*** Dept. Head Entrepreneurial Orientation (4.02)*** (4.04)*** (4.04)*** (3.97)*** Univ. TTO Success (1.15) Male (2.33)** (2.51)** (2.43)** (2.46)** Age of Scientist (1.2) Asia - Country of Origin (-0.59) (-0.54) Midwest Region (-1.03) (-0.19) (-0.20) (-0.14) South Region (0.28) (0.32) (0.3) (0.33) West Region (-0.37) (-0.11) (-0.25) (-0.16) Constant (-2.38)** (-1.66)* (-1.53) (-1.84)* Number of Observations Wald Chi-sq Notes: Absolute z values in parenthesis * Denotes significant at the 10% level; ** significant at the 5% level; *** significant at the 1% level

37 Table 15: Summary of Key Determinants of Scientist Entrepreneurship by Field of Research All Fields CMMI DEB CNS OCE PHY DBI Financial Resources Grant Amount Other Funding (>750K) Human Resources # of Students Human Capital + - Years in Tenure + - Full Professor - Social Capital Board Membership Institutional Factors Dept. Encourages Commercialization Dept. Head Entrepreneurial Orientation + + Univ. TTO Success + Scientist Demographics Male + + Asia - Country of Origin - Midwest Region + + South Region + West Region - Notes: CMMI is Civil, Mechanical, and Manufacturing Innovation; DEB is Environmental Biology; CNS is Computer and Network Systems; OCE is Physical Oceanography; PHY is Particle and Nuclear Astrophysics; and DBI is Biological Infrastructure

38 Conclusions Scientist entrepreneurship is more prevalent and robust than had been previously measured Scientist entrepreneurship varies considerably across scientific fields Determinants of scientific entrepreneurship do not mirror determinants for more general population Determinants of scientific entrepreneurship vary considerably across scientific fields