Eesley Ideas To Life

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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Bringing Entrepreneurial Ideas to Life

Chuck Eesley (Stanford), David Hsu (Wharton), Edward B. Roberts (MIT)

Organization Science Winter ConferenceFeb. 3-7th, 2010


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Two basic views on performance of firms:

Resource-based view (RBV) - strategic resources, firm performance (Penrose 1959, Peteraf 1993, Barney 1991, Wernerfelt 1984)

Theory of the firm - organization of activity, making efficient decisions on governance (Grossman and Hart 1986, Hart and Moore 1990, Holmstrom 1999)

When each is most important and how interact?assembling ‘the right assets’ ‘organizing assets the right way’


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Entrepreneurial firms:

Resource constrained, lack reputation

Assumption: means of acquiring resources or standard set of options for organizational structure is equally important and available

stringent resource constraints (which may foreclose the ability to vertically integrate)

lacking organizational experience and reputation (which may raise transaction costs of inter-organizational production)


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Agenda

1.Theory2.Hypotheses3.Empirical context – novel survey data4.Descriptive statistics5.Analysis/Results6.Endogeneity Concerns7.Conclusion and Implications8.Robustness checks

9. Why do some firms perform better than others when they appear to have developed identical resources?

10.…when they appear to have structured their economic relationships in the same ways?

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Goal: Origins of firms have been under-theorized

Ideas paired with expertise in other areas (Hellmann and Perotti, 2007)

First stage development of a new idea 2nd stage - pairing with expertise for commercialization

(contracting/governance)

Possession of a valuable asset today = result of a successful pairing of a potentially high value idea + expertise in how to form the web of relationships to realize full extent of value


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Theory: Venture Idea Assets (strategic resources)

Novel combination of existing factors - startup idea (Schumpeter 1942, Hellmann, Perotti

2007, Weitzman 1998) New venture - the unique strategic resource is intangible venture idea

Assembling sets or bundles of complementary and unique assets, activities or resources (Rumelt 1984, Montgomery and Wernerfelt, 1988) Resource combinations, integrated sets of activities, and interconnected asset stocks (Dierickx, Cool 1989, Amit and Shoemaker 1993, Lippman and Rumelt 2003)

When is it important?The market for ideas - dampened by weak appropriation (Gans et al. 2002; Anton and Yao,

2002)

Stronger appropriability incentives to invest in idea novelty, innovations more ubiquitous. Dampens

properties making them rent-generating assets – ex ante limits to competition, value, immobility, rarity (Barney 1991, Peteraf 1993)


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Hypotheses:

H1a: Initial venture idea assets will be associated with higher performing firms. H1b: Initial venture idea assets will be an especially important determinant of new venture performance when the firm operates in a weak appropriability environment.


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Theory of the Firm

•TCE (Williamson 1975), property rights (Hart, Moore 1990, Grossman, Hart, 1986), and networks (Powell 1990) •All three theories share view of contracting as critical ingredient

•VCs may bring reputation, resources, and this expertise

H2a: Founding team contracting experience will be positively related to new venture performance.

H2b: Founding team contracting experience will be an

especially important determinant of new venture performance when the firm has no venture capital funding


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Hypotheses:

•Venture idea represents not a single determinative value, but actually a distribution of potential values

•Pairing with founder knowledge and expertise in organizing, structuring, and contracting arrangements - appropriate value from the venture idea

•Ideas brought into contact and under the control of individuals with experience in how to embed them in a web of firm and market contractual relationships

H3: Founding team contracting experience complements venture idea assets in generating additional value so that startups with both will be associated with higher performance.


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Results: Preview


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Data

Unique data on firm origins, early composition and multiple stages of performance measures

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%)

– Hsu, Roberts, Eesley 2007

Alliances & Acq. - SDC Platinum Patents – USPTOVC - VentureXpert


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Characteristics of Non-Respondents

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Variable Responded to 2001 survey(N=43,668)

Did not respond to 2001 survey (N=62,260)

t-stat for equal means

Male 0.83 0.86 10.11Engineering major 0.48 0.47 -4.49Management major 0.16 0.15 -5.75Science major 0.23 0.23 0.37Social sciences major 0.05 0.06 4.07Architecture major 0.06 0.08 11.82Non-US citizen 0.81 0.82 3.77North American (not US) citizen 0.13 0.11 -4.14Latin American citizen 0.13 0.12 -1.44Asian citizen 0.33 0.34 1.45European citizen 0.30 0.26 -5.08Middle Eastern citizen 0.05 0.08 6.32African citizen 0.03 0.05 6.25

Variable Responded to 2003 survey(N=2,111)

Did not respond to 2003 survey(N=6,131)

t-stat for equal means

Male 0.92 0.92 0.12Engineering major 0.52 0.47 -3.63Management major 0.17 0.21 4.17Science major 0.17 0.18 1.09Social sciences major 0.06 0.05 1.18Architecture major 0.09 0.09 1.06Non-US citizen 0.82 0.81 -1.36North American (not US) citizen 0.17 0.14 -1.34Latin American citizen 0.19 0.19 0.13Asian citizen 0.22 0.24 0.73European citizen 0.31 0.32 0.38Middle Eastern citizen 0.08 0.07 -0.59African citizen 0.04 0.04 0.17


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Industry Breakdown

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aerospace2%

arch6%

drugs7%

chemicals2%

consumer products4%

management11%

electronics16%

energy4%

finance5%

law accounting5%

machinery2%

other mfg4%

publishing3%

software25%

telecom4%

MIT


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Unique Data on Origins of the Team and Idea

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Analysis:

E[yi | x] = α + ρ’zi + ’xi + ’zi xi + ’Xi + η + φ + ηφ + i

Dep. Variables: yi represents our measures of firm

performance

xi is a vector of characteristics representing founding conditions concerning the venture idea assets

zi is a vector of characteristics encompassing the sophistication of the founding team in terms of contracting (governance and transactional arrangements) Xi vector of control variables

η and φ represent year and industry sector dummies

ρ>0 or > 0; Complementarity > 0?


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Results: firm performance

N=400; ***, **, and * indicate statistical significance at the 1%, 5%, and 10% levels, respectively. Models 4-3 and 4-4 substitute weak appropriability for the industry fixed effects. Team met via work, idea from work, and team met via family, industry sector, Master’s, PhD, age, firm age, Angel, number of cofounders, functional diversity, year and year founded*industry fixed effects were included as controls but coefficients are not shown to save space.

VARIABLESLn(Emp)

Pr(Exited) Ln(Emp)

Pr(Exited) Ln(Emp)

Pr(Exited) Ln(Emp) Pr(Exited) Ln(Emp)

Pr(Exited)

(4-1) (4-2) (4-3) (4-4) (4-5) (4-6) (4-7) (4-8) (4-9) (4-10)Idea assets 0.281 -0.120 -1.460** -1.164* 0.324 -0.117 -0.144 -1.153**

(0.261) (0.386) (0.670) (0.614) (0.252) (0.393) (0.348) (0.559)Contracting experience 0.599** 0.385 0.489* 0.040 0.963*** 0.954** 0.455* 0.041

(0.240) (0.337) (0.266) (0.188) (0.274) (0.405) (0.252) (0.365)

Idea assets*weak appr. 1.881*** 1.318**

(0.715) (0.639)

Contracting*VC -1.017*** -1.489***

(0.378) (0.523)

Idea assets*contracting 0.737* 1.824***

(0.424) (0.676)

VC 1.517*** 1.746*** 1.718***1.719*** 1.341*** .810*** 2.298*** 2.664*** 1.675*** 1.757***

(0.246) (0.365) (0.237) (0.361) (0.257) (0.189) (0.327) (0.506) (0.237) (0.371)


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Robustness Checks / Limitations

Multiple resource accumulation and performance measures

Inefficient matching subsampleAlternative measuresBroad set of controls

LimitationsRepresentativeness, response rates, self-reportingDirect measurements of contracting concepts / idea quality

– Asset specificity

Omitted variable bias Δxi , changes in the internal and external conditions from founding to the time performance is measured

– partially absorbed by the year and industry fixed effects

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Some identify and develop more valuable resources Yet in accordance with ToF, firms with experience in the founding team in

structuring transactional and governance arrangements outperform

Firms must both identify valuable ideas and also structure the organizational arrangements to commercialize those ideas and resources

Conclusions

H1a: Initial venture idea assets will be associated with higher performing firms.H1b: …will be an especially important in a weak appropriability environment.

H2a: Founding team contracting experience will be positively related to new venture performance. H2b: … will be an especially important determinant of new venture performance when the firm has no venture capital funding

H3: …complements venture idea assets in generating additional value so that startups with both will be associated with higher performance


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Process embedding new idea assets into web of firm activity/economy

Capabilities-based/Strategic Theory of the Firm Capabilities-based logics with org. economics-based theory of the

firm Complicating picture – capability sources and how resource value

is unlocked/realized Initial new firm / business line formation under-theorized

Entrepreneurship Literature Team Formation - demography/experience, less on context of

team formation, theoretical mechanism Sources of ideas/innovations Liability of Newness – firm structures/hierarchies

Implications

innovation


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Thank you!

Chuck EesleyStanford University

Management Science & Engineering (MS&E)[email protected]

mailto:[email protected]


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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) Cutting Your Teeth - Prior entrepreneurial experience

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

What Drives an Innovation Strategy?– Role of Institutional Env./funding of S&T in search for ideas

National Systems of Entrepreneurship: A Cross-National Comparison of Process and Performance

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Matching / Endogeneity Concerns

Efficient matching, endogenous screening, best human capital at commercializing pairs up with the best ideas

In a regression of performance on idea sources and teams, if only one is actually important, then both will appear to be significantly associated with firm performance.

Would never see a good idea paired with mediocre people or vice versa, a mediocre idea paired with high human capital individuals.

Attempt to condition on inefficient matches

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Results: Conditioning on “inefficient matching”

Use a subsample where we are more confident of seeing inefficient matching. Removing firms where the team and idea both came from the same source (less evidence of search for optimal pairings)

Coefficients remain significant and of similar magnitude reassuring us that endogeneity is not driving the results.

To further test whether our contracting variables might be serving as a proxy for higher human capital founders who would only become involved if there is a chance for a very high outcome …

Probit - in the top 5% of the revenue distribution or the valuation at exit distribution (in the case of IPO or acquisition). The results held, and likelihood of being in the extreme right tails of the distribution increased only when both capabilities and contracting expertise were present.

Unobservable heterogeneity, mainly in the form of individual ability is a concern, but mitigated by the relative homogeneity.


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Results

Ln(Alliances) Ln(Employees) Ln(Revenues) Pr(Public) Pr(Acquired)Capabilities 0.023 0.328 0.256 -0.266 -0.188

(0.094) (0.322) (0.284) (0.346) (0.242)Capab.*contract 0.203** 0.864*** 0.475* 0.861*** 0.433*

(0.101) (0.355) (0.323) (0.328) (0.246)Contracting -0.068 0.061 0.029 -0.004 0.273**

(0.049) (0.164) (0.153) (0.146) (0.119)ControlsWork Idea 0.242*** 0.452 0.801*** 0.607** 0.192

(0.087) (0.302) (0.274) (0.283) (0.212)

Social Idea 0.119 0.142 0.595* 0.418 0.444*

(0.104) (0.362) (0.324) (0.316) (0.252)

Military/Gov. Idea 0.325* -0.044 0.272 1.534*** 0.210

(0.168) (0.623) (0.511) (0.538) (0.416)

Work Team 0.048 0.183 0.286 -0.572** -0.114

(0.087) (0.297) (0.266) (0.292) (0.207)

Research Team 0.086 -0.333 -0.013 -0.630** 0.019

(0.093) (0.322) (0.289) (0.307) (0.222)

Social Team 0.203*** -0.089 -0.101 -0.417* -0.007

(0.075) (0.262) (0.236) (0.252) (0.182)

Family Team 0.022 -0.185 -0.147 -1.397** -0.531*

(0.115) (0.394) (0.348) (0.619) (0.313)

N=500; Controls: idea/team source, education, external funding, age, firm age, num. cofounders, industry, year. ***, **, and * indicate statistical significance at the 1%, 5%, and 10% levels, respectively. P-values represent one-tailed tests. All regressions include industry sector dummies, though the coefficients are not shown.


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Boundary Conditions

New Business Line & New Entrepreneurial Firms

Stable Institutional and Industry Environment

Frictions in Markets for Technology

Industry Life Cycle– Mature contracting– Fluid/Early-stage capabilities– High velocity – firms selected out more quickly

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