Eesley China Performance

610
-1

Published on

Presentation for STVP Research Day 3-8-10

Published in: Business, Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
610
On Slideshare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
10
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide
  • Admission highly competitive – Hu Jintao, the current Chinese president is a Tsinghua alum
  • Wide range of work backgrounds, but not formally randomized. The Tsinghua Alumni Association set up interviews, specifically asked to talk with some who were not successful. Probably weighted towards more successful entrepreneurs
  • Next steps – establish a campus wide effort and collaboration with academic units on school and department levels Some Schools, GSB, DAPER, School of Medicine and RDE have already started and have sustainability programs in place at various stages of development.SEM would like to assist the schools in establishing and advancing sustainability programs, and wants to learn from best practices they develop for application at the campus-wide level. SEM and Sustainable Stanford have resources to helpTraining, education, collaboration- working together to establish a cohesive sustainability program at both levels that supports Schools needs and the overall university visionJoint Marketing- website, fact sheets, presentations- we can be an emissary for their Schools in higher education sustainability circles and other non-academic arenas we attendJoint academic conferences, technology and process development, pilot tests
  • Next steps – establish a campus wide effort and collaboration with academic units on school and department levels Some Schools, GSB, DAPER, School of Medicine and RDE have already started and have sustainability programs in place at various stages of development.SEM would like to assist the schools in establishing and advancing sustainability programs, and wants to learn from best practices they develop for application at the campus-wide level. SEM and Sustainable Stanford have resources to helpTraining, education, collaboration- working together to establish a cohesive sustainability program at both levels that supports Schools needs and the overall university visionJoint Marketing- website, fact sheets, presentations- we can be an emissary for their Schools in higher education sustainability circles and other non-academic arenas we attendJoint academic conferences, technology and process development, pilot tests
  • Eesley China Performance

    1. Performance in a Developing Economy Entrepreneurial Performance in a Developing Economy: Evidence from China Chuck Eesley March 8th, 2010 1 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    2. Performance in a Developing Economy Institutional Environments and Entrepreneurship Drivers of entrepreneurial entry and performance (different contexts) Developed economy  Entrepreneurs from Technology-Based Universities - with David Hsu (Wharton), Ed Roberts (MIT)  Bringing Entrepreneurial Ideas to Life  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 2 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    3. Performance in a Developing Economy Most Work on Entrepreneurship Done in Developed Economy Individual Level Institutional Level Overall Economic growth ++ Entrep. Entry ++ + Entrep. Performance ++ ? •Representative entrepreneurship •Self-employment (include lawyers and doctors) •Tech-based entrepreneurship 3 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    4. Performance in a Developing Economy Who is an entrepreneur?  Entrepreneurs (self-employed) tend to have wealth (Blanchflower, Oswald, 1998; Nanda, 2010), self employed parents (Sorensen, 2007; Dunn and Holtz-Eakin, 2000), low opportunity costs (Amit et al., 1995), more educated (Fairlie, Woodruff, 2007), in their 30s-40s (Levesque and Minniti, 2006), generalists (Lazear, 2004), tend to be brokers (Burt, Raider, 2002), low on uncertainty avoidance/higher on individualism (McGrath, MacMillan and Scheinberg, 1992), and achievement need (Johnson, 1990; Roberts, 1991)  Tech entrepreneurs are more highly educated (Roberts, 1991), come from VC- backed firms (Gompers et al., 2005) and often male, engineering/management background, and non-U.S. citizens (Saxenian, 1999; Hsu, Roberts & Eesley, 2007)  In developing world? Entrep. family, friends, value work, wealth (Djankov et al., 2006)  Human capital, overseas, academics less likely (Eesley, 2010)  Interaction between individual and institutional environment characteristics 4 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    5. Performance in a Developing Economy Who is a successful entrepreneur? (developed economy)  Self-efficacy (Baum, 2004) Education - Master‘s degree (Roberts, 1991)  Prior entrepreneurial experience (Roberts and Eesley, 2010; Shane and Khurana, 2003)  Managerial achievements (Eisenhardt&Schoonhoven, 1990)  Work in an entrepreneurial prominent organization (Burton, Sorensen, & Beckman, 2002)  Cohesive social network (Shane, Cable, 2002)  Growth market (Eisenhardt and Schoonhoven, 1990)  Planning (Delmar, Shane, 2003)  Tech-entrepreneurs also: attract VC funding (Chemmanur, Krishnan, and Nandy, 2008), larger founding teams, transfer tech. from parent organizations, product and marketing orientation (Roberts, 1991; 1992) 5 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    6. Performance in a Developing Economy Factors that Drive Founding Do Not Drive Performance Founding Performance Parental entrepreneurship Managerial Experience, prior founding Wealth Lower wealth Low opportunity costs High opportunity costs Male Either gender VC-backed firm work experience Entrep. prominent organization Broker network Cohesive network Need for achievement Self-efficacy Education Education Low uncertainty avoidance, high individualism Product, marketing orientation Generalists Growth market Non-U.S. citizen Either In 30s-40s Any age Planning, VC 6 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    7. Performance in a Developing Economy Institutional Environment and Competitive Advantage  Successful entrepreneur, developing economy?  Individual characteristics, context characteristics, and their interaction drive performance – Team and industry (Eisenhardt and Schoonhoven, 1990)  As institutional environment changes, individual and context characteristics that drive performance change  Institutions – political, social, legal (formal and informal) constraints on indiv. and orgs. (Scott, 2001; North, 1990)  Transition – government planning and control  free market institutions 7 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    8. Performance in a Developing Economy Emerging Economies and Government Ties  Firms with government and managerial ties outperform (Peng and Luo, 2000)  Picking winners, providing resources (nefarious)  Privatization auctions that are not fully competitive (Schamis, 2002)  Closer relationships with state-owned firms (Backman, 2001)  Better access to credit (Khwaja and Mian, 2005; Leuz and Oberholzer-Gee, 2006; Li, et al, 2009)  Government bailouts (Faccio, Masulis and McConnell, 2006)  Over time?  Ties to sociopolitical elites increase the propensity to form cross-border alliances yet when the regime changed, these ties became a liability (Siegel, 2007)  Elites in transitional economies have been able to translate their power into economic benefits? (Nee, 1996; Walder, 2002; Walder, 2003) 8  New firms? Technology firms? S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    9. Performance in a Developing Economy Elite Entrepreneurs in a Developing Economy  Push vs. pull entrepreneurship  Eliminates subsistence entrepreneurship  Focus on form of entrepreneurship tends to result in economic growth, not poverty alleviation  Desired homogeneity in skills, opportunity costs, more narrow, well-defined set, at risk for technology-based entrepreneurship  Comparing apples to apples 9 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    10. Performance in a Developing Economy Model/Hypotheses  Relaxing constraints on entry/markets, allowing market institutions  Providing information on opportunities  Stepping away, other institutions play a role  Incentives for entrepreneurial behavior Central Transition Free Markets Planning/Control Phase I Phase II Phase III Entry is difficult Other institution or Entrep. gov. driven process/skill driven Government ties Other institutional Entrep. experience or govt. programs and innovation 10 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    11. Performance in a Developing Economy Hypotheses: H1: In the beginning, in institutional environments transitioning from an emphasis of government central planning and control, entrepreneurs in locations where government control was initially relaxed will create larger firms. H2: In institutional environments characterized by an emphasis on government central planning and control, entrepreneurs with government ties will create larger firms compared to entrepreneurs without such ties. H3: As institutional environments transition from government central planning and control to market-based incentives, entrepreneurs who can access programs by non-gov. institutions (such as science parks) to create entrepreneurial behavior will create larger firms. H4: In institutional environments that have transitioned from government central planning and control to market-based institutions, greater competition will make entrepreneurs with exposure to the firm creation 11 process and those who are innovating create larger firms. S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    12. Performance in a Developing Economy Context Alumni survey Tsinghua University 26,700 mailed (correct addresses) 3,000 surveys 11% r.r. Growing tradition: Stanford GSB, Chicago, HBS Disadvantages: Biased towards tech., other response bias? Advantages: Defined‗at risk‘ set, first abroad, detailed work history and founding data, less biased by govt. concerns Other surveys: business owners, self-employed and entrepreneurs merged together – Treiman and Walder, ―Life Histories and Social Change in Contemporary China‖  Self-employment (Chinese Health and Nutrition Survey, NBS HH Survey) 12 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    13. Performance in a Developing Economy Tsinghua Univ. •Established in Beijing in 1911 •1952 reorganized Soviet style •1966-1976 Battlefield during Cultural Revolution •1978 restored departments in sciences, economics and management, and humanities •1984 – First Graduate school in China created at Tsinghua •1998 – Tsinghua Science Park established 13 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    14. Performance in a Developing Economy 14 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    15. Performance in a Developing Economy Context - interviews 79 pages of notes from interviews with 42 individuals – 26 Tsinghua alumni entrepreneurs – 2 Tsinghua staff (TLO, Science Park) – 5 Chinese venture capitalists (VCs) – 2 Government officials – 3 Other Chinese entrepreneurs (non-Tsinghua) – 2 MIT Alumni (non-entrepreneurs) – 2 Tsinghua alumni (non-entrepreneurs). • Interviews were in Beijing, Shanghai and Xi‘an 15 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    16. Benchmarking Tsinghua Data Performance in a Developing Economy Categories Tsinghua CHNS NBS HH NBS HH survey survey Sample Urban Rural and Urban Urban – self- Urban – employed non.Entrep. Male 0.89 0.53 0.56 0.50 Age 50.13 41.45 36.2 37.2 Married 0.88 0.98 0.83 0.84 Years of 17.1 9.1 9.2 9.4 Education Household Size 3.40 3.9 -- -- Self-employed 0.26 0.14 (4% in 1999) -- (0.8% in 1999) Experienced a 0.13 -- 0.26 0.19 layoff Father’s Educ. 4.11 -- 5.4 5.2 Mother’s Educ. 4.89 -- 6.0 5.9 Parent Self-Empl. 0.08 -- 0.06 0.05 Comm. Party 0.62 -- 0.05 0.18 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    17. Why China? Performance in a Developing Economy  "The storm center of the world has shifted . . . to China, whoever understands that mighty Empire . . . has a key to world politics for the next five hundred years.‖ --U.S. Secretary of State John Hay, 1899  Tech-based entrepreneurship in developing countries rarely appears in academic literature (Lu 1997, 2000; Puga and Trefler, 2005)  Vernon‘s (1966) product-cycle model  19892004 China 29% vs. US 1% (State Statistics Bureau) 19782004 # employed in private business up 300X  Policies and institutions changing rapidly (Cull &Xu, 2006; Nee, 1998; 1992; 1996; Peng& Heath, 1996; Steinfeld, 2007) S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    18. Performance in a Developing Economy China’s S&T Policy Reform Experimental Structural Deepening S&T reform Firm-centered (PRO centered) Reform of S&T innovation system 78-85 85-95 95-2005 2005+ Gradual, local and sectoral experimentation, partial reforms dual-track approach (Gregory, Tenev, &Wagle, 2000; Nee, 1996) Economic, not political liberalization National Key Tech. Bankruptcy law Private Join WTO R&D Program for SOEs (1986) ownership (2001) Promotions and tax revenue were tied to local economic development (―eating from (1984) separate kitchens‖, or fenzaochifan) (1999) Univ. reform Stock Exchange Tsinghua 2006 Adoption TVEs (getihu) FDI, 1988 (saying qiye) (1985) (1990) Science of medium and Park(1998) Long Term SE Zones (zhuanzhi) or “restructuring of ownership” (suoyouzhigaizao) 1995 – 1996 Privatization created (1980) National Natural Promotion of S&T Strategic “Grasping the large, letting go of the small.” Science Fndtn. VC/PE (1998) Plan Open door policy (1986) (1978) CAS Knowledge >7 emp. Innov. Prog. permitted (1998) Deng Xiao Ping Innov. Fund for (Thanks OECD reform report Torch Program Tech. SMEs Review, 2007) (1975) (1988) (1999) S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    19. Performance in a Developing Economy S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    20. Performance in a Developing Economy Comparison of Key Demographic Characteristics by Survey Wave Variable Respondents Non-respondents t-stat for equal (N=2,667) (N=299) means Age 49.3 54.1 -4.216** Age (founders only) 38.4 37.4 0.602 Bachelor’s Graduation Yr 1980.9 1977.4 3.777** Bach. Grad yr (founders only) 1991.6 1993.2 0.941 Years of Education 17.2 17.0 2.381** Entrepreneur parents 0.09 0.12 -0.713 Entrepreneur 0.29 0.40 -2.168** Privatized 0.10 0.05 1.392 First start-up founded 2000.3 2001.1 -0.661 Tech only 0.28 0.29 0.757 Business only 0.10 0.09 0.235 Gender 0.88 0.90 0.901 Family economic status 3.75 3.85 -1.871* High Salary 3.21 2.93 3.351** Avg. Tenure 6.94 8.01 -2.045* Overseas work exp. 0.26 0.26 -0.126 Number of positions 2.39 2.26 -2.012* High government 0.03 0.03 -0.239 Low government 0.18 0.17 0.617 Last job academia 0.19 0.19 -0.051 Ever job academia 0.32 0.27 2.323** Last job business 0.62 0.61 0.348 Student Leader 0.61 0.57 0.874 GPA Rank 2.28 2.58 -2.661** Bach. Grad Yr. 10th percentile 1954 1953 -- Bach. Grad Yr. 25th percentile 1965 1961 -- Bach. Grad Yr. 50th percentile 1986 1979 -- Bach. Grad Yr. 75th percentile 1996 1993 -- Bach. Grad Yr. 90th percentile 2001 2001 -- ***, **, and * indicate statistical significance at the 1%, 5%, and 10% levels, respectively. 20 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering Back
    21. Performance in a Developing Economy First Foundings by Year 35 30 Number of Start-ups 25 20 15 10 5 0 First Founding Year S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    22. Performance in a Developing Economy Industries INDUSTRY NUMBER OF FIRMS % AEROSPACE 3 0.90 ARCHITECTURE 13 3.88 BIOTECH AND DRUGS 7 1.09 CHEMICALS 8 2.39 CONSUMER PRODUCTS 17 5.07 ELECTRIC 12 3.58 ELECTRONICS 69 20.60 ENERGY 14 4.18 FINANCE 10 2.99 INTERNET 33 9.85 LAW, ACCOUNTING 22 6.57 MACHINERY 19 5.67 MANAGEMENT 21 6.27 MATERIALS 13 3.88 MED DEVICES 4 1.19 OTHER MFG 16 4.78 PUBLISHING 11 3.28 SOFTWARE 34 10.15 TELECOM 9 2.69 TOTAL 335 100 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    23. Performance in a Developing Economy Descriptive results  Could create a figure or t-tests of means across time periods here 23 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    24. Performance in a Developing Economy Interview Quotes China is more state-led than a market economy still. The government controls many resources. For firms the quickest way to make a lot of money is through the government. The government has incentives for firms to put up good numbers (it‘s good for the politicians‘ careers). In the 1990s … government was giving them less support. Many universities created “university –run” enterprises and were basically selling off the periphery of campus. Even high schools had school—run enterprises that were considered acceptable. There is a Tsinghua name to many of them. - GC – 2nd generation investor S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    25. Performance in a Developing Economy Interview Quotes, cont. In the US you don‘t see the government, but in China the role of the government is seen from the very beginning. They could be a major funding source, help in penetrating the markets, and in protecting the competitive advantage. There is some over-emphasis of the role of the government however. - GY– VC investor There is a big government legacy. In the early days the government connections and system were the currency. Power was the currency, but that is changing to a system whose currency is monetary. There was an opportunity to monetize that power. - GC - investor 25 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    26. Performance in a Developing Economy Interviews Historically, investors in China see fewer experienced, serial entrepreneurs ―Forced to rely more on work experience outside of an entrepreneurial context to judge the quality of entrepreneurs – GY – VC investor Tsinghua alumni, entrepreneurship among alumni has a meta-effect where some learn the process and mentor each other so in the future there will be more and more entrepreneurs from Tsinghua as has already happened with MIT alumni. – RC – Wave Communications (his 6th start-up firm) 26 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    27. Performance in a Developing Economy Analysis:  E[yi | x] = α + ρ’zi + ’xi + ’yi + ’pre xi + ’Xi + pre, mid, post + η + φ + i   Dep. Variables: yi represents our measures of firm performance  xi is government ties (father in government, privatized, coastal province)  yi is government programs (specifically science parks)  zi is separate measures for exposure to entrepreneurship, prior founding experience, or innovation  Xi vector of control variables - Everjob_govt, Comm. Party, Govt. customer, Privatized, Entrep. parents, Entrep. index, rural, EECS, Overseas, SEZ, software, electronics, wealthy family, Master’s, PhD, number of cofounders  η and φ represent year and industry sector dummies 27  >0 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    28. Performance in a Developing Economy Results: firm performance VARIABLES Log(rev) Log(rev) Log(rev) Log(rev) Log(rev) Coastal 1989-2000 2.637** (1.049) Privatize 1989-2000 2.406** (1.058) Gov. dad 1989-2002 0.868** (0.403) Park x 2000-02 1.391* (0.712) Park x 2004-07 -1.545** (0.646) E-index x 2004-07 0.214** (0.100) Serial x 2003-07 1.409** (0.689) Innovation x 03-07 1.939** -0.912 1989-2002 5.021** (1.942) 1989-2002 0.834 (0.925) 2000-02 -3.396** (1.388) Log(firm age) 0.360 0.448** 0.417** 0.450** 0.007 0.085 (0.243) (0.190) (0.183) (0.180) (0.458) -0.431 N=230; (R2 0.627) ***, **, and * indicate statistical significance at the 1%, 5%, and 10% levels, respectively. Everjob_govt, Comm. Party, Govt. customer, Privatized, Entrep. parents, Entrep. index, rural, EECS, Overseas, SEZ, software, 28 electronics, wealthy family, Master’s, PhD, number of cofounders, industry and year fixed effects were included as controls but coefficients are not shown to save space. S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    29. Performance in a Developing Economy Robustness Checks / Limitations  Deeper analysis of how gov. father and other factors helped (doesn’t appear to be through gov. purchases or more government funding) Information on opportunities?  Broad set of controls  Next Steps – Additional analysis – government role in certain industries remains? Limitations  Representativeness, response rates, self-reporting  Reverse causality, lobbying for reforms  Effect of higher competition  May be some shift back towards government connections with more recent govt. focus on standards 29 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    30. Performance in a Developing Economy Conclusions H1: In the beginning, … entrepreneurs in locations where government control was initially relaxed will create larger firms. (coastal regions, privatized) H2: …, entrepreneurs with government ties will create larger firms compared to entrepreneurs without such ties. (father in government) H3: … entrepreneurs who can access programs by non-gov. institutions (such as science parks) to create entrepreneurial behavior will create larger firms. (science parks) H4: In institutional environments that have transitioned … to market-based institutions, greater competition will make entrepreneurs with exposure to the firm creation process and those who are innovating create larger firms. (entrep. index, serial, innovation)  Factors driving which individuals start larger, more successful firms is not constant over time.  Shifts in the directions consistent with the model that the drivers of performance follow the institutional changes: government, science parks, market-based free competition S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    31. Performance in a Developing Economy Implications Institutions guide macro-level economic performance Institutions – may guide (or constrain) the individual characteristics and firm creation strategies leading to performance Individual and institutional characteristics interact to generate performance, no single blueprint Comparable process at University Level MIT Case Study – cite Entrepreneurial Impact From Administration/TLO central control to relaxing constraints Next, University programs – b-plan competitions, etc. Finally, faculty/student/alumni entrepreneurial behavior grows outside of programs May explain mixed-results in university entrepreneurship literature - Rothaermel review Entrepreneurship Literature Drive to find “universal” drivers of performance  Context-specific  Opportunity recognition vs. resource mobilization S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    32. Performance in a Developing Economy Boundary Conditions  China had gradual economic reforms while political system remained largely unchanged.  Contrast with Russia where economic liberalization was sudden and accompanied political changes as well  Careful study of Western models and intention to move from government- centered innovation to firm-centered innovation  Regional experimentation, incentives for local economic development  Focus on tertiary education reform  Strong historical culture of entrepreneurship (esp. in certain locations)  Focus on firm performance, not social welfare or aggregate economic impact 32 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    33. Performance in a Developing Economy Thank you! Chuck Eesley Stanford University Management Science & Engineering (MS&E) cee@stanford.edu S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    34. Performance in a Developing Economy 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. 34 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    35. Performance in a Developing Economy 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) Controls Work 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. 35 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering
    36. Performance in a Developing Economy 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 36 S T A N F O R D U N I V E R S I T Y • Management Science & Engineering

    ×