Knowledge Spillover Entrepreneurship & Innovation: The Role of Universities David B. Audretsch
The Traditional University
• The Humboldt Model (Wilhelm von Humboldt, 1767-1835)
• Freedom & independence of research & teaching
• “knowledge for its own sake”
• Little valuation for engagement & societal impact
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
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
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
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)
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
--(Shiri M. Breznitz and Maryann P. Feldman, “The Engaged University,” Journal of Technology Transfer, 2012)
Entrepreneurial University
X
X
X
X
University Patents as a Share of All Patents with Domestic Assignees
0
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)
Sh
are
%
Distribution of University Patents
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
Un
iver
sity
of
Cal
ifo
rnia
Un
iver
sity
of
Texa
s
Un
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Wis
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Co
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ty
Har
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Un
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Stat
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Un
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Number of patents issued from 1998 to 2008
Number of patents
Disappointing Assessment of Technology Transfer
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
Has Knowledge Spillover Entrepreneurship from Universities 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)
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
“Making the switch from science to business” Nature
Measuring Knowledge Spillover Entrepreneurship from Universities
• 16,693 scientists awarded National Cancer
Institute (NCI) grant, 1998-2002 (top 20%)
• $5,350 million NCI grant awards
• NCI awards matched to patents
• 398 distinct patentees, (1,204 patents), 1998-2004
• 1 in 4 scientists started new business
Aldridge & Audretsch, “The Bayh-Dole Act and Scientist Entrepreneurship”, Research Policy, 2011.
Knowledge Spillover Entrepreneurship from Unviersities • 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
Limitations of Previous Research on University Knowledge Spillover 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?
Purpose of Paper
• 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?
Creating a Scientist Entrepreneurship Database • Web of knowledge database contained email 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 email addresses of 172 scientists were returned since they were incorrect/incomplete.
• Survey sample of 9150 scientists (97.75 percent of the population
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
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
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
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
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
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
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
Creating a Database
• Web of knowledge database contained email 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 email addresses of 172 scientists were returned since they were incorrect/incomplete.
• Survey sample of 9150 scientists (97.75 percent of the population
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
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
Per
cen
t S
cien
tist
Sta
rtu
ps
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
Sci
enti
sts
wh
o S
tart
ed U
p
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%
Per
cen
t S
tart
up
s b
y G
end
er
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%
Per
cen
t S
cien
tist
s on
a B
oa
rd
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%
Per
cen
t S
cien
tist
Sta
rtu
ps
by
Reg
ion
Share of Scientist Startups by Region
Probit Regression Results Estimating likelihood of Scientist Startups, all Fields of Research
Independent Variables Model I Model II
Grant Amount 0.01* 0.011**
Other Funding (>750K) 0.343*** 0.316**
# Student Collaborators -0.001* -0.001**
Years in Tenure -0.017 -0.009
Full Professor Dummy -0.201
Scientific Board Member 0.702*** 0.662***
Dept. Encourages Commercialization
-0.167*** -0.191***
Dept. Head Entrepreneur 0.525*** 0.523***
Univ. TTO Success 0.048
Notes: * Denotes 10%; ** Denotes 5%; and *** Denotes 1% level of significance respectively. Controls Include, Scientist Age, Country of Origin, and Region of Main Institutional Affiliation.
Summary of Key Determinants of Scientific Entrepreneurship, by Field of Research
All Fields
Civil-
Mechanical
Envi.
Biology
Computer
Networks
Oceanogr
aphy
Astrophy
sics
Biological
Infra
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 Entrepreneur + +
Univ. TTO Success +
Notes: Controls Include, Scientist Age, Country of Origin, and Region of Main Institutional Affiliation.
Conclusions
• Knowledge spillover entrepreneurship from universities more prevalent than reflected in extant literature
• Knowledge spillover entrepreneurship varies across scientific fields
• Determinants of knowledge spillover entrepreneurship from universities do not mirror determinants for more general population
• Determinants of knowledge spillover entrepreneurship entrepreneurship vary considerably across scientific fields
