Volume 8 Issue 3 ( September 2021 )


A novel hybrid MCDM approach followed by fuzzy DEMATEL-ANP-TOPSIS to evaluate Low Carbon Suppliers

Vivek Gupta, Arvind Jayant


Environmental protection has globally driven the encouragement of design and development of low carbon supply chain management systems at global level. It is known that “Low carbon” approaches and principles play an effective role for industries to minimize the carbon emission from environment. In the real business environment, it becomes very difficult to select more relevant factors among various qualitative and quantitative variables involved in low carbon business operations. A novel hybrid MCDM model, which involved Decision making trial & evaluation laboratory (DEMATEL), Analytical network process (ANP) and techniques for order performance by similarly to ideal solution (TOPSIS) followed by fuzzy methodologies has been developed for evaluation & selection low carbon suppliers. In this paper, a novel hybrid framework has been proposed, which can provide sound support for implementations of LCSCM practices by effective evaluation of concerned criterions. However, some previous fuzzy methods are not capable to consider decision making randomness due to lack of concerned information. The result shows that the novel hybrid MCDM approach to evaluate low carbon supplier to the improvement of LCSCM alternatives is the one which have greater final performance index having value of 0.2350 with corresponding index of supplier (T3), which is the best criteria in this method. Therefore, present work proposed a hybrid multi-criteria decision-making method using fuzzy DEMATEL-ANP-TOPSIS, which measured the cause and effect relationship shows the best result.

Keywords: Low carbon supply chain management (LCSCM), (MCDM) Multiple Criteria Decision Making; Fuzzy Analytic Network Process (FANP); Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS), Fuzzy decision-making trial and evaluation laboratory’ (fuzzy DEMATEL), Supplier selection, Decision making randomness.