Selection of third‐party reverse logistics provider using fuzzy extent analysis

Purpose – The purpose of this paper is to propose a structured model for the selection of a third‐party reverse logistics provider (3PRLP) under fuzzy environment for the battery industry, which establishes the relative weights for attributes and sub‐attributes. Design/methodology/approach – This paper uses fuzzy extent analysis to solve the 3PRLP selection problem. Findings – Owing to growing environmental legislations, reverse logistics (RL) has attained more importance among practitioners and academicians. The important decision related to RL is whether the company should maintain the separate RL system or whether it can be outsourced. RL takes 12 times as many steps to process returns as it does to manage outbound logistics (Accenture supply chain management practice), consequently many companies decided to outsource the RL activities or functions through 3PRLPs. The paper proposes a way of selecting the best 3PRLP using fuzzy extent analysis. Research limitations/implications – Fuzzy extent analysis is a highly multi‐faceted methodology which requires more numerical calculations and increases the time to take a decision. A limitation of this work is that in this study only fuzzy extent analysis has been concentrated on and other multi‐criteria decision‐making methods such as VIKOR, TOPSIS and ELECTRE can be applied in a fuzzy environment for solving such problems. Originality/value – In this research, seven attributes and 34 sub‐attributes are considered and the interpretation of RL attributes in terms of their pair‐wise comparisons has been carried out. Those attributes possessing lower priorities in the fuzzy extent analysis need to be taken care of on a selection of the best 3PRLP.