Selecting Green Suppliers by Considering the Internet of Things and CMCDM Approach

Abstract

Selecting the suppliers in a green supply chain (GSC) improves supply chain capabilities by considering environmental policies. On the other hand, considering the development of technology and intelligence of the Internet of Things (IoT) and their help to meet goals better, it is essential to study them in this area. So, it is crucial to identify the influential factors of the IoT in selecting a green supplier and find its most important criteria for further monitoring and control. This paper aims to illustrate the ability of four different combinatorial multi-criteria decision-making (CMCDM) techniques in determining the best supplier in the rubber GSC. The suppliers are weighted using the fuzzy hierarchical analysis (FAHP) method, then ranked using four methods: VIKOR, TOPSIS, ELECTERE, and WASPAS. Then, their ranks are compared with each other. Eventually, Spearman’s rank correlation was examined to compare CMCDM methods. The results indicate that there is a similar ranking between all four CMCDM methods. Finally, it was found the second supplier is the best alternative for rubber companies looking for environmentally friendly suppliers. Also, FAHP-ELECTERE and FAHP-WASPAS methods have a high correlation with each other. The developed method can help decision-makers to make prompt decisions with less environmental pollution, which helps to achieve sustainable performance in the entire supply chain.