The Origin of Entrepreneurial Opportunities in a Data-Driven Era

Bhatia, A and Dushnitsky, G (2023) The Origin of Entrepreneurial Opportunities in a Data-Driven Era. Academy of Management Proceedings, 2023 (1). ISSN 2151-6561

Abstract

The main theories about the origin of entrepreneurial opportunities were developed at a time when information was scarce. Nowadays, in contrast, we face an information-rich environment where data-driven analytics (e.g., Artificial Intelligence and Machine Learning) are common across many facets of business. To understand the impact of a data-driven approach to the discovery of entrepreneurial opportunities, we study venture capital investors. Traditionally, VCs relied on their business acumen and networks. Recently, some VC funds have adopted data-driven methods as means to discover (i.e., enhance sourcing or selection) entrepreneurial ventures. We document the characteristics of portfolio companies in which data-driven VCs were ‘first money in’; and further compare to the portfolio characteristics of traditional VCs. We observe differences in geographical coverage (e.g., backing founders based in ‘startup hubs’), CEO gender (e.g., a higher fraction of female founders), and educational background (e.g., backing graduates of ‘elite’ universities). Our findings inform the origin of entrepreneurial opportunities in an information-rich analytics-intense environment. It further alludes to the role of organizational norms in leading to notable differences in the ultimate application of AI.