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Reconceptualizing Entrepreneurial Exit

Reconceptualizing Entrepreneurial Exit. Karl Wennberg Stockholm School of Economics Johan Wiklund Syracuse University Dawn R. DeTienne Colorado State University Melissa S. Cardon Pace University. Entrepreneurial Exit. Exit: Confusing evidence to date?. Entrepreneurial Exit.

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Reconceptualizing Entrepreneurial Exit

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  1. Reconceptualizing Entrepreneurial Exit Karl Wennberg Stockholm School of Economics Johan Wiklund Syracuse University Dawn R. DeTienne Colorado State University Melissa S. Cardon Pace University Entrepreneurial Exit

  2. Exit: Confusing evidence to date? Entrepreneurial Exit

  3. Problems in Prior Research • 1. Theoretical frameworks? • Expected Utility (EU) – most empirical work • - Sociology – disconnect between theories of class vs. theories of network/homphily • -Psychology (e.g. Prospect theory, Theory of Planned Behavior) -high internal validity but reliance on experiments 2.Underspecification problem - Need to distinguish different exit choices/routes from each other 3. Role of economic performance? - Low correlation performance – exit - “Irrational” entreprenuerial career choices(Hamilton, 2000) - Entrepreneurs as “skewness lowers” (Åsterbro, 2003) or “Hubris” (Griffith et al. 2006) Entrepreneurial Exit

  4. This paper Definition Entrepreneurial Exit: Whenever individuals exit the firm they started Theretical/Conceptual framework We view entrepreneurial exit as liquidation of a financial investment. (individual heterogeneity in intended longevity, emotional attachment ,etc.). • Empirical approach: • 1.Expected Utility (EU) vs. Prospect theory (PT) • -PT higher internal validity but sometimes difficult to distinguish from EU • -Relative explanatory power of EU / PT vary with domain and demographics (e.g. Harrison & Ruthström, 2007) • 2. Underspecification problem: • Need to distinguish the different choice sets from each other (i.e. by specification tests or computing marginal effects/competing models) • 3. Performance designed away (incorporated in outcome variable) Entrepreneurial Exit

  5. Methods Matched individual-firm data: Owner-managed firms in high-tech and knowledge-intensive services 1,735 new ventures followed for eight years (full population – no sample) Career history of owners: Human capital, demographics, class background Firm data: age, size, industry controls, performance measures allows us to differentiate three exit routes: Dissolution, harvest sale, and distress sale (first research to prove distinctiveness of various sales routes (Storey, Parker & Van Wittelstoltjin, 2005) Multinomial logit model with marginal effects of individual-level predictors Hypotheses tested by binary logit models testing each outcome against alternatives Entrepreneurial Exit

  6. Hypotheses: Entrepreneurial Experience Continuation Complementary Individual factors: * Entrepreneurial learning * Habitual entrepreneurship Dissolution Harvest Sale Distress Sale Entrepreneurial Exit

  7. Hypotheses: Education Continuation Competing Individual factors: * Higher performance (Bates, 1990) * More outside options (Gimeno et al., 1997) Harvest Sale Distress Sale Dissolution Entrepreneurial Exit

  8. Hypotheses: Industry Experience Continuation Competing Individual factors: Utility-maximizing arguments: * Experienceperformance (Cooper et al., 1994) Harvest Sale Distress Sale Dissolution Behavioral arguments: inexperience positively related to overconfident entry (Delmar & Shane, 2004; Hayward, Shepherd, & Griffin, 2006) and unwillingess to dissolve unsuccessful exploration (Lowe & Ziedonis, 2006) Entrepreneurial Exit

  9. Hypotheses: Age Continuation Complementary Individual factors: * $1 today more valuable than $2 tomorrow * Value of discounted future cash flow decreases with age, relative to selling (Becker, 1965; Lévesque & Minniti, 2006) Harvest Sale Distress Sale Dissolution Entrepreneurial Exit

  10. Results Specification tests: 1. Akike / Bayesian information criterion (AIC/ BIC) lowest value for the trinomial exit specification Dissolution, Harvest sale, andDistress sale 2. Independence of irrelevant alternatives (IIA)test was insignificant prior work with exit as a binary outcome has pooled conceptually as well as mathematically distinct events. Competing Cramer-Ridder tests rejected pooling the 3 alternatives -Valid model, but what about the appropriateness of utility theory and prospect theory to explain the different exit routes? Entrepreneurial Exit

  11. 1.86% 4.72% 1.81% Results : EntrepreneurialExperience -fullysupported! Continuation Dissolution Harvest Sale Distress Sale Entrepreneurial Exit

  12. 1.38% 0.61% Results : Education -not supported. Continuation Dissolution Harvest Sale Distress Sale Entrepreneurial Exit

  13. 2.05% 1.37% Results : Industry Experience -mixed supported! Continuation 3.10% Dissolution Harvest Sale Distress Sale Entrepreneurial Exit

  14. 1.29% 1.93% 1.40% 1.37% Results : Age -fullysupported! Continuation Dissolution Harvest Sale Distress Sale Entrepreneurial Exit

  15. Conclusions and future research: - Research on exit needs theoretical frameworkthat motivates distinct exit routes and what leads entrepreneurs to seek (or end up in) one or the other - Relative explanatory power of EU / PT vary between demographics, hence both are valuable for studies of entrepreneurial exit (e.g. Harrison & Ruthström, 2007) - Prior research has tended to treat exit as an underspecified event – e.g. Entrepreneurial Experience Further research --Failure-reducing strategies: -Income substitution :decreases probability of dissolution and distress sale, but no effect on the harvest sale -Reinvestment: Decrease all types of exit Related research: -Emotional investment  exit decision (Shepherd, Wiklund & Haynie, 2008) -Team decision  exit decision (Hellerstedt, Aldrich, Wiklund, ) Monday 14:30! Entrepreneurial Exit

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