Bayesian analysis in entrepreneurship decision-making research Review and future directions

Purpose - The purpose of this paper is to review Bayesian analysis in recent entrepreneurship research to assess how scholars have employed these methods to study the entrepreneurship process. Researchers in other business fields (e.g. management science, marketing, and finance) have increasingly employed Bayesian methods to study issues like decision making. To date, however, Bayesian methods have seen only limited use in entrepreneurship research. Design/methodology/approach - After providing a general overview of Bayesian methods, this study examines how extant entrepreneurship research published in leading journals has employed Bayesian analysis and highlights topics these studies have investigated most frequently. It next reviews topics that scholars from other business disciplines have investigated using these methods, focusing on issues related to decision making, in particular. Findings - Only seven articles published in leading management and entrepreneurship journals between 2000 and 2016 employed or discussed Bayesian methods in depth when studying the entrepreneurship process. In addition, some of these studies were conceptual. Research limitations/implications - This review suggests that Bayesian methods may provide another important tool for researchers to employ when studying decision making in high uncertainty situations or the impact of entrepreneurial experience on decision making over time. Originality/value - This review demonstrates that Bayesian analysis may be particularly appropriate for entrepreneurship research. By employing these methods, scholars may gain additional insights into entrepreneurial phenomenon by allowing researchers to examine entrepreneurial decision making. Through this review and these recommendations, this study hopes to encourage greater Bayesian analysis usage in future entrepreneurship research.