Supply chain risk mitigation: modeling the enablers

Abstract

Purpose – Supply chain risk management assumes importance in the wake of organizations understanding that their risk susceptibility is dependent on other constituents of their supply chain. The purpose of this paper is to present an approach to effective supply chain risk mitigation by understanding the dynamics between various enablers that help to mitigate risk in a supply chain. Design/methodology/approach – Using interpretive structural modeling the research presents a hierarchy-based model and the mutual relationships among the enablers of risk mitigation. Findings – The research shows that there exists a group of enablers having a high driving power and low dependence requiring maximum attention and of strategic importance while another group consists of those variables which have high dependence and are the resultant actions. Practical implications – This classification provides a useful tool to supply chain managers to differentiate between independent and dependent variables and their mutual relationships which would help them to focus on those key variables that are most important for effective risk minimization in a supply chain. Originality/value – Presentation of enablers in a hierarchy and the classification into driver and dependent categories is unique effort in the area of supply chain risk management.