Assessing disaster risks in supply chains

Abstract

Purpose – As organizations increase their dependence on supply chain networks, they become more susceptible to their suppliers’ disaster risk profiles, as well as other categories of risk associated with supply chains. Therefore, it is imperative that supply chain network participants are capable of assessing the disaster risks associated with their supplier base. The purpose of this paper is to assess the supplier disaster risks, which are a key element of external risk in supply chains. Design/methodology/approach – The study participants are 15 automotive casting suppliers who display a significant degree of disaster risks to a major US automotive company. Bayesian networks are used as a methodology for examining the supplier disaster risk profiles for these participants. Findings – The results of this study show that Bayesian networks can be effectively used to assist managers in making decisions regarding current and prospective suppliers vis-à-vis their potential revenue impact as illustrated through their corresponding disaster risk profiles. Research limitations/implications – A limitation to the use of Bayesian networks for modeling disaster risk profiles is the proper identification of risk events and risk categories that can impact a supply chain. Practical implications – The methodology used in this study can be adopted by managers to assist them in making decisions regarding current or prospective suppliers vis-à-vis their corresponding disaster risk profiles. Originality/value – As part of a comprehensive supplier risk management program, organizations along with their suppliers can develop specific strategies and tactics to minimize the effects of supply chain disaster risk events.