دانلود رایگان مقاله انگلیسی تحلیل بیزی در تحقیقات تصمیم گیری کارآفرینی: مرور و جهت های آینده - امرالد 2017

Abstract

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.

Conclusion

This study reviewed Bayesian methods use in extant entrepreneurship research. In general, we found that these studies have infrequently employed Bayesian methods, despite the direct applicability of Bayesian methods to entrepreneurship topics and research situations (e.g. decision making under uncertainty). Specifically, only seven studies employed Bayesian logic or methods from 2000 to 2017. As a result, we highlighted additional topics where scholars could employ these methods in future research and provided examples from other organizational research illustrating applications of these methods to entrepreneurship research.

This review also demonstrates that this analysis may be particularly appropriate for entrepreneurship research, given the importance of both uncertainty and information asymmetry to the entrepreneurship process. By employing Bayesian methods, scholars may gain additional insight into entrepreneurial phenomenon by allowing researchers to examine entrepreneurial decision making. We hope that through this review and these recommendations, we help encourage greater Bayesian analysis usage in future entrepreneurship research.