Sustainable third-party reverse logistics provider evaluation and selection using fuzzy SWARA and developed fuzzy COPRAS in the presence of risk criteria

• Published in: Applied soft computing 2018-04, Vol.65, p.307-319
• Main Authors: Zarbakhshnia, Navid, Soleimani, Hamed, Ghaderi, Hadi
• Format: Article
• Language: English
• Subjects: Fuzzy COPRAS; Fuzzy SWARA; Risk criteria; Sustainable reverse logistics; Third-party reverse logistics provider
• ISSN: 1568-4946; 1872-9681
• DOI: 10.1016/j.asoc.2018.01.023

•A third party reverse logistic provider (3PRLP) selection and evaluation process is developed.•A multiple attribute decision making (MADM) model to evaluate and select 3PRLPs in the presence of risk factors is proposed.•A fuzzy step-wise weight assessment ratio analysis (SWARA) approach to weight the evaluation criteria is applied.•A fuzzy (COPRAS) is proposed to rank and select the sustainable third-party reverse logistics providers in the presence of risk factors.•A real world case study is used from automotive industry to validate the quality of our model. Reverse logistics is the backward process of collecting and redistributing products at the end-of-life from customers to producers and manufacturers for reuse, remanufacturing and disposal purposes. While reverse logistics brings several economic benefits, it seems to become a necessity for businesses to remain competitive in a world that environmental and social aspects of business activities are key to sustainable development. The operations and management of reverse logistics systems is a complex task that requires substantial level of infrastructure, technology, expertise and experience. Therefore, increasingly many business organizations tend to outsource their reverse logistics activities to third-party reverse logistics providers (3PRLPs). In this paper, we propose a multiple attribute decision making (MADM) model to rank and select 3PRLPs, using fuzzy step-wise weight assessment ratio analysis (SWARA) to weight the evaluation criteria. Accordingly, a developed fuzzy complex proportional assessment of alternatives (COPRAS) was proposed to rank and select the sustainable 3PRLPs in the presence risk factors. The suggested model was applied to a case study from automotive industry. Eventually, COPRAS and COPRAS-G methods were considered for the purpose of comparison and validation. As a result, the most sustainable 3PRLP was selected. While incorporating risk factors into our analysis, our study shows that environmental and social drivers are increasingly becoming dominant when selecting 3PRLPs.