University Entrepreneurship & Regional Economic Development - - PowerPoint PPT Presentation
University Entrepreneurship & Regional Economic Development David B. Audretsch The Traditional University The Humboldt Model (Wilhelm von Humboldt, 1767-1835) Freedom & independence of research & teaching knowledge
David B. Audretsch
(Wilhelm von Humboldt, 1767-1835)
teaching
capital
values
capital of knowledge
“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
university research limited to measures of what the TTO does
by TTO may lead to systematic underestimation
from university research (Thursby & Thursby, 2005; Shane, 2004)
fields and programs (i.e. biochemistry, informatics)
its own sake”
technology transfer offices, incubators, science parks, sponsored research
X X X X
University Patents as a Share of All Patents with Domestic Assignees
0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 1948 1950 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996
University Patent Issue Year (Mowery 2005)
Share %
500 1 000 1 500 2 000 2 500 3 000 3 500 4 000 4 500 5 000 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
Number of patents issued from 1998 to 2008
Number of patents
U.S. Universities
$368 million of R&D
university research limited to measures of what the TTO does
by TTO may lead to systematic underestimation
from university research (Thursby & Thursby, 2002, “Who Is Selling the Ivory Tower?” Management Science; Shane, 2004, “Technological Opportunities and New Firm Creation,” Management Science)
Technology Transfer Office Mission Statements
Primary objectives of the UTTO Percentage of times appeared in mission statement (%) Licensing for royalties 78.72 IP protection/management 75.18 Facilitate disclosure process 71.63 Sponsored research and assisting inventors 56.74 Public good (disseminate information/technology 54.61 Industry relationships 42.55 Economic development (region, state) 26.95 Entrepreneurship and new venture creation 20.57 N = 128 TTOs.
Source: G. Markman, P. Phan, D. Balkin & P. Gianiodis, “Entrepreneurship and University-Based Technology Transfer, “ Journal of Business Venturing, 2005
Institute (NCI) grant, 1998-2002 (top 20%)
2004
Aldridge & Audretsch, “The Bayh-Dole Act and Scientist Entrepreneurship”, Research Policy, 2011.
AUTM & university TTO’s may underestimate extent of scientist entrepreneurship
$368 million of R&D
implies one startup generated per $12 million of R&D
– “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?”
entrepreneurship hold across different scientific fields & heterogeneous types of scientists?
“Scientist Entrepreneurship: Does the Scientific Field Make a Difference?” Taylor Aldridge, David B. Audretsch &Venkata Nadella
Does to Commercialize Research
Characteristics in Explaining Propensity for Scientist to Engage in Entrepreneurship
Explaining Scientist Commercialization
Entrepreneurs?
9361 scientists that received NSF funding between 2005 and 2012-Q2.
email addresses of 172 scientists were returned since they were incorrect/incomplete.
population
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)
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
entrepreneurship (Minniti & Nardone (2007) “Being in Someone Else’s Shoes: The Role of Gender in Nascent Entrepreneurship,” Small Business Economics)
for gender for cancer scientists
capital and entrepreneurship for general population (Davidsson & Honig (2003) “The role
Entrepreneurs,” Journal of Business Venturing)
to have no impact on scientist entrepreneurship for cancer researchers
entrepreneurship for general population (Aldrich & Martinez (2010), “Entrepreneurship as Social Construction,” in Handbook of Entrepreneurship)
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
Vohora (2005) “Spinning Out New Ventures: A Typology of Incubation Strategies from European Research Institutions,” Journal of Business Venturing
Universities Generate More TLO Start-Ups than Others?”, Research Policy
resources found to have positive impact on entrepreneurship (Gompers &Lerner (2010), “Equity Financing,” in Handbook of Entrepreneurship Research)
influences entrepreneurship for high-tech & knowledge industries (Kerr & Nanda (2009) “Financing Constraints and Entrepreneurship,” National Bureau of Economic Research Working Paper
2005 and 2012-Q2.
population of 9361 scientists in the first round of survey administration
inactive, and email addresses of 172 scientists were returned since they were incorrect/incomplete.
population
12,8% 20,1% 4,6% 23,8% 9,2% 6,2% 8,2% 0% 5% 10% 15% 20% 25% 30% All Fields of Research Civil, Mechanical, and Manufacturing Innovation Environmental Biology Computer and Network Systems Physical Oceanography Particle and Nuclear Astrophysics Biological Infrastructure
Percent Scientist Startups
Scientist Startups by Field of Research
43,8 43,0 45,1 42,5 46,0 47,3 44,4 40 41 42 43 44 45 46 47 48 49 50 All Fields of Research Civil, Mechanical, and Manufacturing Innovation Environmental Biology Computer and Network Systems Physical Oceanography Particle and Nuclear Astrophysics Biological Infrastructure
Age of Scientists who Started Up
Scientist Age and Startup Commercialization
13% 19% 5% 25% 8% 7% 9% 5% 9% 0% 7% 4% 10% 6% All Fields of Research Civil, Mechanical, and Manufacturing Innovation Environmental Biology Computer and Network Systems Physical Oceanography Particle and Nuclear Astrophysics Biological Infrastructure 0% 5% 10% 15% 20% 25% 30%
Percent Startups by Gender
Scientist Startups and Gender
Male Scientists Female Scientists
Scientist Characteristics, Years in Tenured Status Total Sample Started Up Non- Tenured Scientists 156 17 10.9% Tenure Scientists 0-5 Years 67 6 9.0% 6-10 Years 200 31 15.5% 11-15 Years 184 20 10.9% 16-20 Years 170 33 19.4% 21-25 Years 101 13 12.9% 26-30 Years 59 6 10.2% 31-35 42 7 16.7% More than 35 Years 32 2 6.3% Total 1011 135
64% 62% 59% 71% 58% 75% 59% 31% 20% 39% 26% 38% 25% 32% All Fields of Research Civil, Mechanical, and Manufacturing Innovation Environmental Biology Computer and Network Systems Physical Oceanography Particle and Nuclear Astrophysics Biological Infrastructure 0% 10% 20% 30% 40% 50% 60% 70% 80%
Percent Scientists on a Board
Scientists on Board of Directors of other firms
Started Up Did Not Startup
28,9% 9,2% 8,4% 27,6% 11,3% 23,8% 4,6% 19,7% 5,0% 4,6% 0% 5% 10% 15% 20% 25% 30% 35% Percent Scientist Startups by Region
Share of Scientist Startups by Region
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. 0.01 0.011 0.011 0.011 (1.85)* (2.07)** (2.04)** (2.13)** Other Funding (>750K) - Fin Res. 0.343 0.282 0.297 0.316 (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 0.702 0.66 0.636 0.662 (5.30)*** (5.26)*** (5.06)*** (5.19)***
(-4.14)*** (-4.07)*** (-4.24)*** (-4.47)***
0.525 0.512 0.521 0.523 (4.02)*** (4.04)*** (4.04)*** (3.97)***
0.048 (1.15) Male 0.445 0.469 0.458 0.466 (2.33)** (2.51)** (2.43)** (2.46)** Age of Scientist 0.015 (1.2) Asia - Country of Origin
(-0.59) (-0.54) Midwest Region
(-1.03) (-0.19) (-0.20) (-0.14) South Region 0.048 0.054 0.05 0.057 (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 758 786 777 758 Wald Chi-sq. 76.32 76.1 74.86 78.2
Notes: Absolute z values in parenthesis * Denotes significant at the 10% level; ** significant at the 5% level; *** significant at the 1% level
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
+
+
+ + + + + Board Membership + + + + + Institutional Factors + + +
+ +
+ Scientist Demographics Male + + Asia - Country of Origin
+ + South Region + West Region
Astrophysics; and DBI is Biological Infrastructure
robust than had been previously measured
across scientific fields
not mirror determinants for more general population
considerably across scientific fields