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Title Sustainable reverse logistics practices and performance evaluation with fuzzy TOPSIS: A study on Indian retailers
ID_Doc 19418
Authors Sharma, NK; Kumar, V; Verma, P; Luthra, S
Title Sustainable reverse logistics practices and performance evaluation with fuzzy TOPSIS: A study on Indian retailers
Year 2021
Published
Abstract Reverse Logistics (RL) is one of the crucial topics for discussion among academicians in the field of environmental performance and sustainability through businesses. RL is found an effective strategy for the business, environment, and sustainable development in many studies. RL is imperative due to various reasons such as reducing environmental problems, cost controlling, competitive advantage, and many more. But, still, the area of RL is not saturated enough; there are various issues that researchers need to address. In this paper, we have focused our concern towards the RL parameters and organised retailers in India. Retailers are one of the significant links in RL process and hence their role is also critical. The paper helps to analyze the RL practices adopted by the organised retailers and their performance. A Technique for Order of Preference by Similarity to Ideal Solution, which is usually abbreviated as TOPSIS generally referred to as the multi-criteria decision analysis method while fuzzy TOPSIS is incorporated to choose the best practitioner of RL among all retailers. The output of the study is based on multiple case studies. Based on the results of RL parameters, the second retailer has emerged as the top while the fifth retailer is found as the lowest among all the retailers. The findings of the study provided a rank of them that aid others to improve their performances. Further, the identified RL parameters as critical inputs indicate the retailers being extra proactive and well-arranged encompassed of twenty-four retailers in three groups. The study's emphasis on vital factors will support others to achieve higher productivity for higher sustainability in the retail sector context.
PDF https://doi.org/10.1016/j.clscn.2021.100007

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