Reverse Logistics Risk Management; Identification, Clustering, and Risk Mitigation Strategies

Abstract

Purpose- Reverse Logistics (RL), an inseparable aspect of supply chain management, returns used products to recovery processes with the aim of reducing waste generation. Enterprises, however, seem reluctant to apply RL due to various types of risks which are perceived as posing an economic threat to businesses. This paper draws on a synthesis of supply chain and risk management literature to identify and cluster RL risk factors and to recommend risk mitigation strategies for reducing the negative impact of risks on RL implementation. Design/methodology/approach- The authors identify and cluster risk factors in RL by using risk management theory. Experts in RL and supply chain risk management validated the risk factors via a questionnaire. An unsupervised data mining method, Self-Organising Map (SOM), is utilised to cluster reverse logistics risk factors into homogeneous categories. Findings- 41 risk factors in the context of RL were identified and clustered into three different groups: strategic, tactical, and operational. Risk mitigation strategies are recommended to mitigate the RL risk factors by drawing on supply chain risk management approaches. Originality/value- This paper studies risks in RL and recommends risk management strategies to control and mitigate risk factors to implement RL successfully