Fuzzy AHP-TOPSIS approaches to prioritizing solutions for reverse logistics barriers

Abstract

Fuzzy AHP and fuzzy TOPSIS method are proposed.The case of Thailands electronics industry is used in the proposed method.Technological barriers are the highest weightage barrier for RL practices.Infrastructural barriers are the lowest weightage barrier for RL practices.Top management awareness and support is the highest ranking value of solutions. Due to an increasing demand for green products and also pressures from customers and other players along the supply chain, which now pay more attention to environmental awareness and sustainable management, many companies especially in the electronics industry have begun to realize the importance of applying green supply chain management concepts into their activities; reverse logistics (RL) practice is one of the important strategies to provide efficient resource utilization and minimize waste from end of life (EOL) products by following legislation and green concepts. But recently reverse logistics practices are faced with some barriers which make the implementation of reverse logistics difficult and unsuccessful. To increase efficiency in reverse logistics adaptation of the electronics industry, companies need to understand and consider the priorities of both barriers and solutions for developing policies and strategies to overcome these barriers. Therefore, this study focused on the classification of reverse logistics barriers and ranking of both barriers and solutions of reverse logistics implementation in the electronics industry. This paper proposes a methodology based on fuzzy analytical hierarchy process (Fuzzy AHP) and fuzzy technique for order performance by similarity to ideal solution (Fuzzy TOPSIS) in which fuzzy AHP is applied to get the weights of each barrier by using pairwise comparison, and fuzzy TOPSIS is applied for the final ranking of the solutions of reverse logistics implementation. The case of Thailands electronics industry is used in the proposed method. To illustrate the robustness of the method, sensitivity analysis is used in this study.