Eesley research overview MS&E
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Transcript of Eesley research overview MS&E
Tech-based Entrepreneurship and the Institutional Environment
Research Overv iew:
Chuck [email protected]
stvp.stanford.edu
Influence of the External Environment on Tech-Based Entrepreneurship
• Individual characteristics, network ties, and strategy
• Effective institutional change influences who starts firms, not just how many firms are started.
• Study a single country (China, Chile, Japan, and the U.S.) before and after a major institutional change
• natural experiments
• Empirical/large dataset, international fieldwork/interviews
stvp.stanford.edu
Three Streams
1. Formal Institutions
2. Industry Environment
3. Informal Institutions
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Stream 1: Formal Institutions• Prior literature focuses on barriers to entry, self-employment
• Entrepreneurial activities of high human capital individuals – focus on high-growth, technology-based firms.
•Eesley, C. 2016. Institutional Barriers to Growth: Entrepreneurship, Human Capital and Institutional Change. Organization Science
•Armanios, D., C.E. Eesley, K.M. Eisenhardt, J. Li. 2016. How entrepreneurs leverage institutional intermediaries in emerging economies to acquire public resources, Strategic Management Journal•Eesley, C.; J.B. Li, and D. Yang. 2016. Does Institutional Change in Universities Influence High-Tech Entrepreneurship?: Evidence from China’s Project 985. Organization Science, 27(2): 446-461.•Eberhart, R.; C. Eesley, and K. Eisenhardt. 2016 Failure IS an Option: Institutional Barriers to Failure, Bankruptcy and New Firm Performance, Organization Science, cond. acceptance
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Stream 1: Formal Institutions
Eesley, C. 2016. Institutional Barriers to Growth: Entrepreneurship, Human Capital and Institutional Change. Organization Science
• Amendment to the Chinese constitution reversing regulations that favored firms with foreign investors and state-owned enterprises
• Lowering BTG stimulates the founding of firms by high human capital individuals
stvp.stanford.edu
stvp.stanford.edu
• Eberhart, R.; C. Eesley, and K. Eisenhardt. 2016. Failure IS an Option: Institutional Barriers to Failure, Bankruptcy and New Firm Performance, Organization Science
• 2003 bankruptcy reform in Japan
• COSMOS2 database from Teikoku Databank, Ltd. 50,000 firms over a 20 year time period, 10 variables, 10 million observations
• Lowering barriers to failure – increase churn, but also venture growth rates (due to elites)
Stream 1: Formal Institutions – Barriers to Failure
Stream 2: Industry Environment
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Industry Environment
• Eesley, Charles E.; Hsu, D.; Roberts, E.B. 2013. The Contingent Effects of Top Management Teams on Venture Performance: Aligning Founding Team Composition with Innovation Strategy and Commercialization Environment. Strategic Management Journal, 35(12): 1798–1817.
• Eesley, Charles E. and Roberts, E.B. 2012. Are You Experienced or Are You Talented?: When Does Innate Talent versus Experience Explain Entrepreneurial Performance. Strategic Entrepreneurship Journal. 6(3): 207-219. (Winner, Best Paper Proceedings Award, AOM conference, Montreal, 2010.)
• Hsu, D.; Roberts, E.B.; Eesley, Charles. 2007. Entrepreneurs from Technology-Based Universities: Evidence from MIT. Research Policy 36, 768–788.
stvp.stanford.edu
stvp.stanford.edu
stvp.stanford.edu
Stream 2: On-going work on digital platforms
• 30 months of firm-level data on around 10,000 merchant ventures – Sales data– # of distinct items sold– pricing– product categories– customer review scores – gender of owner– age of owner – registration date – location (province &
city)• 200+ hours of interviews
• Alibaba – 1,000 Faces, platform change (with Wesley Koo)
• Customizing search results to each individual consumer
• Forced merchants to focus on particular consumer segments
Stream 3: Informal Institutions
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Stream 3: Informal Institutions
• Eesley, C.; Decelles, K.; Lenox, M. 2015. Through the Mud or in the Boardroom: Activist Types and their Strategies in Targeting Firms for Social Change. Strategic Management Journal,
• Lenox, M. and Eesley, C. 2009. Private Environmental Activism and the Selection and Response of Firm Targets. Journal of Economics & Management Strategy, 18(1), 45-73.
• Eesley, Charles; Lenox, Michael. 2006. Firm Responses to Secondary Stakeholder Action. Strategic Management Journal, 27(8):765-781.
stvp.stanford.edu
stvp.stanford.edu
Influence of the External Environment on Tech-Based Entrepreneurship
• Policy leaders wish to foster high growth, technology-based start-ups
• Institutional changes can significantly influence the types of firms that are created, who creates them, and how they perform.
• Theoretical contributions – institutional barriers to
growth and failure, founding team alignment, informal inst.
• Methods contributions– look beyond developed
North American and European economies.
– differences-in-differences, randomized field experiments, regression discontinuity, instrumental variables
Institutions and High-Tech Entrepreneurship
Chuck [email protected]
stvp.stanford.edu
Backup slides
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Social Influence in Entrepreneurial Career Choice
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stvp.stanford.edu
Methods contributions• Alumni Surveys
• Platform/Field Randomized Experiments
• Web scraping, platform data – Alibaba/Taobao (Wesley), Chinese regional government websites (Daniel), LinkedIn (Xinyi),
• Lab experiment – Tsinghua Executive MBAs (Xinyi)• QCA analysis, In-person interview surveys (Daniel, Jamber)
• (A) showing how to measure talent, (B) using alumni surveys to reduce success bias, (C) collecting data internationally, (D) using randomized field experiments, and (E) analyzing multi-industry databases with state-of-the-art statistics (Regression discontinuity, instrumental variables, differences-in-differences)
Why study high-tech entrepreneurship?
• Driver of economic growth and technical progress
• Driver of economic and social mobility
• Important intersection of technical and social science issues
• Young field, interesting methodological, statistical issues
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Public Research Institutions and EntrepreneurshipScience Parks• How entrepreneurs leverage institutional
intermediaries in emerging economies to acquire public resources. (Strategic Management Journal with D. Armanios, J. Li and K. Eisenhardt),
• Provide multiple paths that expand the set of people who can become successful entrepreneurs.
• Distinguish which entrepreneurs benefit from certification v. capability-building – new constructs: skill adequacy and context relevance.
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Chinese Academy of Sciences Reform
• w/ Daniel Armanios (Carnegie Mellon)
• Combining web scraping via Python script and government database of high tech certification
• Dataset of >10,000 Chinese high tech ventures
R&R at Administrative Sciences Quarterly
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Social Influence in Entrepreneurial Career Choice
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Randomized Treatment Groups
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stvp.stanford.edu
Stanford Alumni Survey
% of firms
median emp#
median rev ($mil)
Est. aggregate total emp#
Est. aggregate total sales ($mil)
Less than 1000 97% 10 $1 1,762,000 $1,711,000
1,000–10,000 2.6% 1,947 $250 2,248,000 $704,000More than 10,000 0.3% 16,000 $1,950 1,377,000 $251,452
Total 100% 11 $1.2 5,387,000 $2,667,000
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Heavy Innov Moderate Innov Little Innov TotalPercent of firms 25% 25% 50% 100%Revenue (in millions of $) $1,270,000 $531,000 $864,000 $2,667,000% of total revenues by all Stanford firms 48% 20% 32% 100%Employees 1,141,000 2,003,000 2,242,000 5,387,000% of total employment by all Stanford firms 21% 37% 42% 100%
Stanford Alumni Survey
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Stanford Alumni Survey
Overall
Tech. InnovatorsFounders
Quick Founders (VC funded w/in 3 years)0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
Program Participation By Stanford Alumni
Entrepreneurship Courses
Competitions and Programs (STVP, CES, E-Challenge, Dschool, BioDesign, TLO)
Alumni Network for funding, cofounders, customers, partnerships or advisors/mentors
Perc
enta
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artic
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Start-Up Chile
The Economist – October 2012
The Experiment• Analytic Strategy
– Regression Discontinuity Design. (Imbens & Lemieux, 2008)• Treated: Domestic entrepreneurs who were barely accepted into
the program.• Control: Domestic entrepreneurs who were barely rejected from
the program.– Self-reported value assessment comparison. – Interviews.
• Treatment– Participation in Start-Up Chile.
• Data– Pre- and post-treatment surveys. (Shadish, Cook & Campbell, 2002)– Self-assessment survey of beliefs and behaviors, corrected by
socially desirable responding. (Paulhus, 2002)– Relative change comparison. (Hennig, Mullensiefen & Bargmann, 2010)