Entrepreneurs: Clueless, Biased, Poor Heuristics, or Bayesian Machines?

Abstract

Entrepreneurship scholars are interested in understanding and describing how entrepreneurs make decisions under uncertainty, where the probabilities of outcomes are not known but perceived, resulting in ambiguous probabilities. In this context, ambiguity refers to the lack of precise and objective probability assessments and the presence of subjective judgments regarding potential outcomes. In this chapter, we discuss the development of thought on how entrepreneurs perceive and react to uncertainty from Frank Knight (1921) to the present day. Recognizing that entrepreneurs face uncertainty rather than risk and are unlikely to have estimates of all probabilities for all potential outcomes, it becomes difficult to accept Expected Utility Theory (EUT), developed by Savage (1951) and von Neumann and Morgenstern (1953), as a relevant model for entrepreneurial decision-making. We examine a range of decision theories, ranking them in an order starting from EUT and proceeding to the most structure-free models of entrepreneurial choice, allowing for comparisons and contrasts of the main components and underlying concepts as they apply to entrepreneurial decision making.