Sage Publications/RM Division Best Paper Award Nominee
Bayesian Data Analysis (BDA) offers a consistent framework for integrating prior knowledge with empirical data, which is particularly beneficial in fields with complex datasets or substantial prior information, such as management and organizational sciences. This paper presents a comprehensive literature review assessing the adoption and implications of BDA in this domain from 2001 to 2022. The review provides the first comprehensive examination of how BDA is applied in these fields, with a special focus on the clarity of these applications, including the specification and disclosure of prior distributions. A critical finding from the review is the widespread shortfall in transparency, particularly in the justification and reporting of prior distributions. Notably, the analysis shows that a substantial 33\% of the reviewed papers fail to adequately disclose their prior distributions. These issues could undermine the reliability of research findings and hinder the broader adoption of Bayesian methods. To address these challenges, researchers, reviewers, and editors should adopt and promote standardized reporting guidelines for BDA in organizational research, aiming to improve the reproducibility and trustworthiness of the results.
