Affiliations: [a] School of Business, Sichuan Normal University, Chengdu, P.R. China
| [b] School of Statistics, Southwestern University of Finance and Economics, Chengdu, P.R. China
| [c] School of Finance, Southwestern University of Finance and Economics, Chengdu, P.R. China
| [d] School of Finance, Yunnan University of Finance and Economics, Kunming P.R. China
Correspondence:
[*]
Corresponding author. Lu Xiao, School of Business, Sichuan Normal University, Chengdu, 610101, P.R. China. E-mail: [email protected].
Abstract: Since people around the world have gradually attached importance to resource conservation, various countries are actively taking measures to promote environmental protection and sustainable development. Green supply chain management (GSCM) have emerged in this context. Thus, in this essay, a novel intuitionistic fuzzy multiple attribute group decision making (MAGDM) method is designed to tackle this issue. First of all, CRITIC (Criteria Importance Through Inter-criteria Correlation) method is utilized to determine the weights of criteria. Later, the conventional Taxonomy method is extended to the intuitionistic fuzzy environment to compute the value of development attribute of each supplier. Then, the optimal one can be determined. Eventually, an application about green supplier selection in steel industry is presented, and a comparative analysis is made to demonstrate the superiority of the proposed method. The main features of the proposed algorithm are that they provide a practical solution for selecting GSCM and presents an objective weighting method to enhance the effectiveness of the algorithm.
Keywords: Multiple attribute group decision making (MAGDM), green supply chain management (GSCM), intuitionistic fuzzy sets (IFSs), taxonomy method, CRITIC method, steel industry
