Academic Perspectives

This page collects articles and books from scholars on the reasons why startups fail; startup failure rates; and how to cope with and learn from entrepreneurial failure. Many of the listings below are adapted from footnotes in my book, Why Startups Fail.

A companion page shares practitioners’ perspectives on these topics.

Causes of Startup Failure

  • Part I of Dean Shepherd and Randall Tobias, eds., Entrepreneurial Failure (Northampton, MA: Edward Elgar, 2013), compiles 18 academic articles on the causes of entrepreneurial failure

  • Grace Walsh and James Cunningham, “Business Failure and Entrepreneurship: Emergence, Evolution and Future Research,” Foundations and Trends in Entrepreneurship, 12, no. 3 (2016) surveys the academic literature on the causes of business failure and its personal consequences for entrepreneurs

  • Jesper Sorensen and Patricia Chang, “Determinants of Successful Entrepreneurship: A Review of the Recent Literature” surveys academic research on startup performance drivers

  • Michael Song et al., “Success Factors in New Ventures: A Meta-analysis,” Journal of Product Innovation Management 25 (2008): 7-27 presents a meta-analysis of factors contributing to new venture success and failure

  • My HBS working paper, "Determinants of Early-Stage Startup Performance: Survey Results" summarizes analysis of a survey of founder/CEOs of 470 early-stage startups regarding a broad range of factors related to their venture’s customer value proposition, product management, marketing, technology and operations, financial management, funding choices, team management, and founder attributes. Regression analysis shows that startups that employed lean startup management practices—in particular, an optimal rate of pivoting—had stronger seed equity valuation growth, as did new ventures that struck the right balance in recruiting for skill versus attitude and that professionalized human resource policies earlier. High levels of confidence in financial metrics—including estimates of unit economics, the ratio of customer lifetime value to customer acquisition cost, and total addressable market size—were also associated with strong growth in seed equity value. Valuation outcomes were not related to several founder/CEO attributes, including age, educational background, personality traits, and motivations for becoming an entrepreneur. Likewise, choosing angels versus venture capital firms as lead seed round investors did not predict subsequent growth in equity valuation, nor did decisions about partnerships to provide technology, operational capacity, or marketing support.

Research on “Horse vs. Jockey” as Drivers of Startup Performance

  • Steven Kaplan, Berk Sensoy, and Per Stromberg, “Should Investors Bet on the Jockey or the Horse? Evidence from the Evolution of Firms from Early Business Plans to Public Companies,” Journal of Finance 64, no. 1 (2009): 75–115 shows that most successful startups have stable business lines over time, and concludes that early-stage investors should therefore put more weight on business concept (the “horse”) than founder attributes (the “jockey”)

  • By contrast, Ian Macmillan, Lauriann Zemann, and P. N. Subbanarasimha, “Criteria Distinguishing Successful from Unsuccessful Ventures in the Venture Screening Process,” Journal of Business Venturing 2, no. 2 (1987): 123–137 cite survey data in which VCs blame 68% of portfolio company failures on management team flaws

  • Paul Gompers, Anna Kovner, Josh Lerner, and David Scharfstein, “Performance Persistence in Entrepreneurship,” Journal of Financial Economics 96, no. 1 (2010): 18–32 show that 30% of serial entrepreneurs who were successful in their first venture succeeded in subsequent ventures, compared to 22% of serial entrepreneurs who failed in their first attempt and 21% of first-time founders. These differences suggest that learning from experience isn’t decisive and suggest that successful serial entrepreneurs had some edge that other founders lacked: either better skills or superior access to resources, or both

Research on the Link Between Industry Experience and Startup Performance

  • Rajshree Agarwal, Raj Echambadi, April Franco, and M. B. Sarkar, “Knowledge Transfer through Inheritance: Spin-out Generation, Development, and Survival,” Academy of Management Journal 47, no. 4 (2004): 501–522

  • Aaron Chatterji, “Spawned with a Silver Spoon? Entrepreneurial Performance and Innovation in the Medical Device Industry,” Strategic Management Journal 30, no. 2 (2009): 185–206

    Charles Eesley and Edward Roberts, “Are You Experienced or Are You Talented? When Does Innate Talent Versus Experience Explain Entrepreneurial Performance?” Strategic Entrepreneurship Journal 6 (2012): 207–219

  • J. P. Eggers and Lin Song, “Dealing with Failure: Serial Entrepreneurs and the Cost of Changing Industries Between Ventures,” Academy of Management Journal 58, no. 6 (2015): 1785–1803, shows that serial founders whose previous venture failed are more inclined to blame the external environment than their own ability, and thus are more likely to change industries when pursuing a new venture, compared to counterparts whose previous venture was successful. Furthermore, Eggers and Song show that changing industries hurts the performance of a serial entrepreneur’s subsequent venture—regardless of the entrepreneur’s success or failure with their previous venture. This lends support to the notion that industry experience drives success odds

Research on How Entrepreneurs’ Psychological Attributes Influence Startup Performance

  • Robert Baron and Gideon Markman, “Beyond Social Capital: The Role of Entrepreneurs’ Social Competence in Their Financial Success,” Journal of Business Venturing 18 (2003): 41– 60 shows that higher scores on measures of social competence (e.g., adaptability, persuasiveness) predict higher income for entrepreneurs

  • Hao Zhao, Scott Seibert, and G. T. Lumpkin, “The Relationship of Personality to Entrepreneurial Intentions and Performance: A Meta-Analytical Review,” Journal of Management 36, no. 2 (2010): 381–404, shows that four of the “Big Five” stable personality attributes—conscientiousness, openness to experience, extraversion, and emotional stability—were positively correlated with entrepreneurial firm performance

  • By contrast, M. Ciavarella, A. Bucholtz, C. Riordan, R. Gatewood, and G. Stokes, “The Big Five and Venture Survival,” Journal of Business Venturing 19 (2004): 465–483, finds that the only statistically significant Big Five predictor of venture survival is a positive relationship with conscientiousness

  • Mathew Hayward, Dean Shepherd, and Dale Griffin, “A Hubris Theory of Entrepreneurship,” Management Science 52, no. 2 (2006): 160–172, analyzes attributes of ventures that are likely to increase founder overconfidence and posits reasons why overconfident founders are more likely to fail

  • Sabrina Artinger and Thomas Powell, “Entrepreneurial Failure: Statistical and Psychological Explanations,” Strategic Management Journal 37, no. 6 (2016): 1047–1064, shows that overconfident entrepreneurs are more prone to enter overcrowded markets in lab experiments

  • Robin Hogarth and Natalia Karelaia, “Entrepreneurial Success and Failure: Confidence and Fallible Judgment,” Organization Science 23, no. 6 (2012): 1733–1747 examine the performance consequences of entrepreneurs’ overconfidence

  • Colin Camerer and Dan Lovallo, “Overconfidence and Excess Entry: An Experimental Approach,” American Economic Review 89, no. 1 (1999): 306–318, presents experimental results showing that overconfident individuals are, in a simulation, more likely to launch ventures in a market with uncertain prospects, resulting in excess entry and financial losses

  • For additional research on entrepreneurs’ overconfidence and its impact, see Arnold Cooper, Carolyn Woo, and William Dunkelberg, “Entrepreneurs’ Perceived Chances for Success,” Journal of Business Venturing 3, no. 2 (1988): 97–108; L. W. Busenitz and Jay Barney, “Differences between Entrepreneurs and Managers in Large Organizations: Biases and Heuristics in Strategic Decision-Making,” Journal of Business Venturing 12, no. 1 (1997): 9–30; Daniel Forbes, “Are Some Entrepreneurs More Overconfident Than Others?” Journal of Business Venturing, 20 (2015), 623-640; and Antonio Bernardo and Ivo Welch, “On the Evolution of Overconfidence and Entrepreneurs,” Journal of Economics & Management Strategy 10, no. 3 (2001)

  • Chad Navis and O. Ozbek, “The Right People in the Wrong Places: The Paradox of Entrepreneurial Entry and Successful Opportunity Realization,” Academy of Management Review 41, no. 1 (2016): 109–129, argues that overconfident and narcissistic individuals are more likely to be drawn to bold, novel opportunities because they will overestimate success odds (due to overconfidence) and will crave the attention that comes with doing something big and new (due to narcissism). Navis and Ozbek also argue that overconfidence and narcissism inhibit learning in ways that reduce success odds with novel ventures

  • Y. Liu, Y. Li, X. Hao, and Y. Zhang, “Narcissism and Learning from Entrepreneurial Failure,” Journal of Business Venturing 34 (2019): 496–512, presents survey data that shows that narcissistic founders are less likely to learn from a prior startup failure

  • Barry Staw, “The Escalation of Commitment to a Course of Action,” Academy of Management Review 6, no. 4 (1981): 577–587 describes a propensity—for ego-defensive and other reasons—to “double down,” increasing one’s commitment to an existing strategy in the wake of a bad outcome. This propensity is also consistent with the core tenet of prospect theory: that individuals tend to be risk averse in the domain of gains (i.e., when they’ve experienced good outcomes and have a lot to lose if a bet goes badly) and risk seeking in the domain of losses, as shown in Daniel Kahneman and Amos Tversky, “Prospect Theory: An Analysis of Decision under Risk,” Econometrica 47, no. 2 (1979): 263–292. Likewise, escalation of commitment is broadly consistent with a threat-rigidity response: a tendency by individuals or organizations, when under duress, to revert to a familiar strategy rather than search for a new one, as described in Barry Staw, Lance Sandelands, and Jane Dutton, “Threat-Rigidity Effects in Organizational Behavior: A Multilevel Analysis,” Administrative Science Quarterly 26, no. 4 (1981): 501–524

Research on Capital Market Boom-Bust Cycles

  • Paul Gompers and Josh Lerner, The Venture Capital Cycle (Cambridge, MA: MIT Press, 2004)

  • Paul Gompers, Anna Kovner, Josh Lerner, and David Scharfstein, “Venture Capital Investment Cycles: The Impact of Public Markets,” Journal of Financial Economics 87 (2008)

  • Ramana Nanda and Matthew Rhodes-Kropf, “Investment Cycles and Startup Innovation,” Journal of Financial Economics 110 (2013): 403–418; Nanda and Rhodes-Kropf, “Financing Risk and Innovation,” Management Science 63, no. 4 (2017): 901–918.

  • Tom Nicholas, VC: An American History (Cambridge, MA: Harvard University Press, 2019), Ch. 8

Startup Failure Rates

  • Grace Walsh and James Cunningham, “Business Failure and Entrepreneurship: Emergence, Evolution and Future Research,” Foundations and Trends in Entrepreneurship 12, no. 3 (2016): 163–285, summarizes startup failure rate estimates from various academic studies

  • Robert Hall and Susan Woodward, “The Burden of the Non-Diversifiable Risk of Entrepreneurship,” American Economic Review 100, no. 3 (2010): 1163–1194, finds that three-quarters of venture capital–backed companies never return any equity proceeds to their entrepreneurs

  • Deborah Gage, “The Venture Capital Secret: 3 Out of 4 Startups Fail,” Wall Street Journal, Sept. 20, 2012, summarizes unpublished research by HBS professor Shikhar Ghosh that is consistent with Hall and Woodward’s finding. Ghosh examined investments in over two thousand startups that received at least $1 million in venture capital funding from 2004 through 2010. He determined that 75 percent did not return investors’ capital

  • Using a methodology similar to Ghosh’s and analyzing returns for all startups that received a first round of venture capital financing between 1985 and 2009, a 55 percent failure rate is reported in William Kerr, Ramana Nanda, and Matthew Rhodes-Kropf, “Entrepreneurship as Experimentation,” Journal of Economic Perspectives 28, no. 3 (2014): 25–48. This estimate is lower than Ghosh’s due in part to the fact that Kerr et al. assume that all acquired startups that did not announce the value of their exit proceeds—the preponderance of acquisitions—were sold at a profit, for 1.5x the total capital they’d raised

  • In fact, many acquisitions yield a loss for investors. Most other estimates of startup failure rates fall between 50 percent and 90 percent. Differences in startup failure rate estimates depend largely on researchers’ definitions of “startup” and “failure.” Reported rates tend to be lower when failure is defined as an outright shutdown due to financial distress. However, this definition excludes “living dead” startups that survive but will never earn a positive return for investors, and also excludes acquisitions with proceeds less than total capital raised. Mortality rates tend to be higher if startups are defined as any entity that aims to pursue an entrepreneurial opportunity rather than just those that have raised a threshold amount of external funding

Coping with and Learning from Startup Failure

  • Part II of Dean Shepherd and Randall Tobias, eds., Entrepreneurial Failure (Northampton, MA: Edward Elgar, 2013), compiles 18 academic articles on the consequences of venture failure and how entrepreneurs recover and learn from it

  • Dean Shepherd, Trenton Williams, Marcus Wolfe, and Holger Patzelt, Learning from Entrepreneurial Failure: Emotions, Cognitions, and Actions (Cambridge, UK: Cambridge University Press, 2016) provides a comprehensive view of the psychological impact of entrepreneurial failure, its consequences, and how individuals can learn and recover from failure

  • Diego Zunino, Gary Dushnitsky, and Mirjam van Praag, “How Do Investors Evaluate Past Entrepreneurial Failure? Unpacking Failure Due to Lack of Skill versus Bad Luck,” Academy of Management Journal, in press (published online June 2, 2021) shows, in an experiment with crowdfunding investors, that investors do not exhibit outright aversion to failure. They do discount ventures when their founders previously failed, but the discount is reversed when investors receive signals of founder skill.

  • J. P. Eggers and Lin Song, “Dealing with Failure: Serial Entrepreneurs and the Cost of Changing Industries Between Ventures,” Academy of Management Journal 58, no. 6 (2015): 1785–1803 present survey results in which the top two reasons cited by founders for their ventures’ demise were industry conditions beyond their control—an example of the fundamental attribution error first described by Lee Ross in “The Intuitive Psychologist and His Short- comings: Distortions in the Attribution Process,” Advances in Experimental Social Psychology 10 (1977): 173–220

  • In this Wall Street Journal article, Edinburgh University professor Francis Greene summarizes research on 8,400 German startups showing that failed founders are less likely than first-time founders to succeed in subsequent founding efforts, due to: 1) the difficulty of drawing accurate inferences from a protracted prior failure — one in which the founder probably based decisions on biased information; and 2) ego-defensive and other psychological biases, including a tendency to oversimplify explanations for failure (working paper PDF here)

  • Dawn DeTienne, Dean Shepherd, and Julio De Castro, “The Fallacy of ‘Only the Strong Survive’: The Effects of Extrinsic Motivation on the Persistence Decisions for Under-Performing Firms,” Journal of Business Venturing 23 (2008): 528–546, presents a theoretical model for why entrepreneurs may persist with a struggling venture, and tests the model through conjoint analysis. According to DeTienne et al., previously successful entrepreneurs are more apt to persist because they assume they have a winning formula

  • Jason Cope, “Learning from Entrepreneurial Failure: An Interpretive Phenomenological Analysis,” Journal of Business Venturing 26 (2011): 604–623 explores entrepreneurs’ learning in the wake of venture failure

  • This Scientific American article describes large sample analysis by Dashun Wang and Northwestern University colleagues of NIH grants, terrorist attacks, and startup funding rounds that shows that the interval between successive attempts is correlated with success outcomes. The researchers assert that shorter intervals indicate learning from prior failures, which boosts subsequent success odds (PDF of Nature article here).

  • In his seminal paper, “Learning through Failure: The Strategy of Small Losses,” Research in Organizational Behavior 14 (1992): 231–266, Sim Sitkin argues that “failure is an essential prerequisite for learning” because it stimulates experimentation. Sitkin explores factors that promote learning in organizational settings

  • A. Bandura, Social Learning Theory (Englewood Cliffs, NJ: Prentice Hall, 1977), describes the process of vicarious learning and contrasts it to learning from direct experience.

  • Jerker Denrell, “Vicarious Learning, Undersampling of Failure, and the Myths of Management,” Organization Science 14, no. 3 (2003): 227–243, argues that when individuals in organizations learn vicariously, they are too likely to focus on successful rather than failed initiatives. According to Denrell, if risky strategies are more likely to result in both more successes and more failures, compared to safer strategies, then undersampling failures may lead to an inference that risky strategies are more attractive than they really are