City Research Online

Abstract

We examine the performance differences among startups in nascent industries, taking account of the distinct knowledge contexts from which they arise. Specifically, we investigate the effect of pre-entry experience on the performance of startups originating within the same industry (i.e. inside–industry spinouts) and those from related knowledge contexts along the value chain (i.e. outside–industry spinouts). Analyzing a novel dataset that includes all U.S. artificial intelligence industry startup entrants during the period 1980 to 2014, we find that inside–industry spinouts and outside–industry spinouts have comparable survival and successful exit rates, outperforming startups with no pre-entry experience related to AI. Exploring the heterogeneity among outside–industry spinouts, we also find that the higher survival rate of this category of entrants is driven by startups founded by individuals who previously worked for firms operating in upstream supplier industries. We discuss the implications of our findings for research on strategy and industry evolution.

Publication Type:	Article
Additional Information:	This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Publisher Keywords:	Pre-entry experience, Startup performance, Nascent industries, Artificial intelligence
Subjects:	H Social Sciences > H Social Sciences (General) H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Departments:	Bayes Business School Bayes Business School > Faculty of Management
SWORD Depositor:	Symplectic Administrator

Export

Downloads