Bayesian networks supporting management practices: A multifaceted perspective based on the literature

Abstract

Bayesian network is a probabilistic graphical model within machine learning that supports decision-making under conditions of uncertainty in different domains. Although the scientific literature has increasingly addressed the implementation of Bayesian networks to support management practices (BNM), a thorough review is currently lacking. This bibliometric review investigates the transformative potential of Bayesian networks in reshaping decision-making paradigms across multidisciplinary domains. The knowledge set findings reveal a predominant focus on risk management within the Engineering domain; the scientific openings involve significant progress in both theoretical frameworks and practical applications across Computer Science, Engineering, Medicine, and Environmental Science; and research trends indicate a progressive BNM within Engineering and Medicine, contrasting with a decline in innovative studies related to Computer Science. This study acts as a catalyst, propelling inventive BNM applications and fostering interdisciplinary advancements. It lays a foundation for pioneering BNM strategies.

Keywords

• Bayesian networks
• Management practices
• Bibliometrics
• Knowledge set
• Scientific openings
• Research directions