Integration of AHP-TOPSIS method for prioritizing the solutions of reverse logistics adoption to overcome its barriers under fuzzy environment

Abstract

Reverse logistics practices are gaining attention due to industrial ecology, enforced legislation and corporate citizenship but presence of barriers make reverse logistics (RL) implementation difficult and hence reduce the success rate. To increase RL adoption, robust and flexible strategies are required to overcome its barriers. This study focuses on identification and ranking the solutions of reverse logistics adoption in electronics industry to overcome its barriers. It aids firms to ponder on high rank solutions and develop strategies to implement them on priority. This paper proposes a methodology based on fuzzy analytical hierarchy process (AHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) to identify and rank the solutions of RL adoption to overcome its barriers. Fuzzy AHP is applied to get weights of the barriers as criteria by pairwise comparison and final ranking of the solutions of RL adoption is obtained through fuzzy TOPSIS. The empirical case of Indian electronics industry is shown to illustrate the use of the proposed method. This proposed method offers a more precise, efficient and effective decision support tool for stepwise implementation of the solutions due to consideration of fuzzy environment. Finally sensitivity analysis is performed to illustrate the robustness of the method.