S T A N F O R D U N I V E R S I T Y • Management Science & Engineering CUTTING YOUR TEETH 1 Cutting Your Teeth: Learning from Entrepreneurial Experience Chuck Eesley (Stanford), Edward B. Roberts (MIT) Organization Science Winter Conference Feb. 3-7 th , 2010
Presentation on serial entrepreneurs for the West Coast Research Symposium in Seattle, WA at the Univ. of Washington.
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S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
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Cutting Your Teeth: Learning from Entrepreneurial Experience
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H Motivation
When do new ventures benefit from the prior entrepreneurial experience of their founders?
Under what conditions does organizational learning get transferred by individuals to new organizations (what type of learning in the case of entrepreneurial experience)?
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Simon (1991):1) by ‘ingesting’ new members who have knowledge not previously in the organization, or 2) by its members learning
Huckman and Pisano (2006) - experience within particular organization
Hire employees / management to access internally (rather than externally) the accumulated learning – strategy/OT (Beckman & Burton, 2008; Ahuja & Katila, 2001)
Hypothesis 1: The benefit from learning transferred by an individual will be higher with greater levels of prior experience.
Hypothesis 2: The benefit from learning transferred by an individual will be higher with prior successful experience.
Motivation: Types of learning experiences
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Transfer effects - loss of performance if skill is wrongly applied in a different context (Haleblian & Finkelstein, 1999; March, 1991)
Hypothesis 3a: The benefit from learning transferred by an individual will be higher with prior experience in the same industry.
Industry evolution - automobiles (Abernathy, 1978) typesetters (Tripsas, 1997)
Major disruptions - learning in the previous environment no longer relevantFind the right causal relationships and models to fit the changed environment (Kaplan & Tripsas, 2008)
Hypothesis 3b: The benefit from learning transferred by an individual with prior experience will be lower after a significant shift in the industry.
Hypothesis 4: The benefit from learning transferred by an individual will be higher with more recent prior experience.
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Existing work mainly argues that processes and routines are learned from operating experience (Nelson & Winter, 1982; Winter, 2000)
Bingham, Eisenhardt, and Davis (2009) - rather than routines, increasingly sophisticated and refined portfolios of heuristics to guide actions
Content knowledge as important or more so than process knowledge
Hypothesis 5: The benefit from learning transferred by an individual will come from content learning about the industry gained from prior experience rather than about process learning.
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Shedding light on what the individual is learning
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H MIT Data
Long time horizon in the cross section (1930s-2003)Note: not MIT-originated technology
Alumni: 105,000 surveyed; 42,930 records in 2001– Date of birth, country of citizenship, gender, major at
MIT, highest attained degree– 7,798 indicated founding at least one company
Survey of self-identified MIT alumni entrepreneurs in 2003
– 2,067 respondents (r.r. 27%) – More detailed info; new venture founding history
(multi-founder r.r. of 30.4%, 1.79 vs. 2.13 reported)
80% of the company names D&B database (obtain a credit rating) no bias towards larger firms (Aldrich, Kalleberg, Marsden and Cassell, 1989)
VEIC SIC codes (Dushnitsky & Lenox, 2005)
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H Univariate t-tests of means
Panel A No prior founding experience At least 1 prior founding experience
Revenues 13.957 14.219*
Exits 0.205 0.240**
Panel BPrior founding exper. in a
different industryPrior founding exper. in the same
industry
Revenues 14.042 14.854**
Exits 0.060 0.173***
Panel C+Before dotcom boom, no prior
founding exper. Before dotcom boom, has prior
founding exper.
Revenues 14.614 15.227*
Exits 0.275 0.391*
Panel D+After dotcom boom, no prior
founding experience After dotcom boom, has prior
founding experience
Revenues 12.810 13.375
Exits 0.182 0.061**8
S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
(2.549)Age founded -0.021* -0.029 -0.0537* -0.0663* 0.024 0.022 -0.015
Software firms only; N=205Controls: age founded, num. cofounders, Bachelor’s, Master’s, initial capital, firm age
Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1
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Content vs. process
1063 firms, 234 events and 16,068 years at risk. All models include controls for Master’s and Doctorate degrees, the number of cofounders, log(firm age), functional diversity and constant terms, but the coefficients are not shown to save space. Model (6-3) excludes firms that were VC funded. Models (6-4), (6-5) and (6-6) exclude firms that were funded by angel investors. The results are robust to leaving these firms in as well.
Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1
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HAlternative stories/Robustness checks
1. Unique to particular measures of “performance”
2. More talented or persistent individuals select into serial entrepreneurship (individual fixed effects)
3. Learning about the start-up process (evidence on industries)
4. Increased social network size (evidence on location)- most communication is with those in closer physical proximity
5. Wealth
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H Conclusion and Implications
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Hypothesis:Supported
?
H1The benefit from learning transferred by an individual will be higher with greater levels of prior experience. Y
H2 “… higher with prior successful experience Y
H3a
“… higher with prior experience in the same industry Y
H3b
“… lower after a significant shift in the industry Y
H4 “… higher with more recent prior experience Y
H5“… will come from content learning about the industry gained from prior experience rather than about process learning. Y
Organizational Learning and Entrepreneurship Literatures:
Individual Level• Learning by ingesting new members
Strategy• Micro-foundations of competitive advantage – content vs.
process (Haliblian & Finkelstein, 2002) diversification• Active view on identification of valuable resources (routines)• Level playing field after disruptions• Challenge of sectors with more serial entrepreneurs
Institutions• Fostering this type of experience (exit events, non-competes)
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H Relationship to Broader Research Stream
Drivers of entrepreneurial entry and performance (different contexts)
Developed economy Entrepreneurs from Technology-Based Universities - with David Hsu
(Wharton), Ed Roberts (MIT) Bringing Ideas to Life – Conditions when types of assets performance
Developing economy The Right Stuff
– Role of institutional environment in selection of high human capital entrepreneurs
Entrepreneurial Performance in a Developing Country: Evidence from China
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