Abstract
PURPOSE: The existing literature on the success of startup enterprises is thorough in investigating individual factors, but relatively weak in testing those factors in combination. This research tests for interactive effects, i.e., complementarities, between those factors. METHODOLOGY: We use a Cox proportional hazard model to estimate longevity in startups, supplementing it with maximum likelihood estimation of two metrics of success (employment and revenue). In each model, we explicitly test for interactions between terms, thus advancing the literature. FINDINGS: Panel data analysis shows that financing strategy matters to startup success, especially when combined with specific human and social capital attributes of the founders. For example, angel investors and venture capital investors benefit differently from founders with industry experience; founders with higher educational achievement generate more revenue than their peers specifically when their startups collaborate in university partnerships. IMPLICATIONS FOR THEORY AND PRACTICE: The paper suggests specific ways in which entrepreneurs should think about financing options that are complementary with their founder attributes. Further, it suggests that the literature must be very thoughtful, not only about the indicators of success but about advice to policymakers, financiers and entrepreneurs because of the nuanced nonlinearities and interactions we demonstrate. ORIGINALITY AND VALUE: We contribute to the literature on startup financing with a large dataset, careful modelling of interactive complementarities of between inputs, correction of the potential sample selection bias in previous studies, and a suite of modelled outcomes (survival, employment, and revenue) which allow for nuanced results.
Highlights
There is a long literature about why new businesses fail
That combination of facts has led to the development of new capitalization strategies, including venture capitalists (VCs) and angel investors, exclusively for high-risk investment scenarios
Given that venture capital investment in startups exceeded $300 billion in 2020 despite the pandemic (Teare, 2021), it is expensive if we place the wrong bets
Summary
There is a long literature about why new businesses fail. Yet that literature appears inadequate in light of the fact that the failure rate of new businesses is 90% (Carrigan, 2020) in the United States, where those same new businesses account for as much as 50% of new job creation year-to-year across a host of industries (Fairlie et al, 2016). That combination of facts has led to the development of new capitalization strategies, including venture capitalists (VCs) and angel investors, exclusively for high-risk investment scenarios. Our research here improves existing models of startup survival and success, adding to the literature in several critical ways. Others take a special interest in specific industries, with investment decisions informed largely by their familiarity and expertise in a certain field. These investment philosophies have likened startup investing to horse racing: one can bet on the jockey (the entrepreneur), the horse (the business), or the race (the industry/market), as pointed out by Kaplan et al (2009). While the literature has thoughtfully explored the separate contributors of success, it has been very limited in measuring the interactions between those same factors
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