Research On Sustainable Supply Chain Suppliers Selection Of Company F

Due to an increased awareness of ecological protection and resultant stringent legislations,business organizations are highly motivated to improve the sustainable performance of their supply chain in order to achieve sustainable development goals,and it’s also a challenge for decision makers to choose sustainable suppliers based on the triple bottom line.And among many industries,the chemical industry,as a high-risk and high-pollution industry,requires particular attention to sustainability issues.So far,many methods and models have been proposed to solve the sustainable supplier selection problem,but no research has been conducted to match the appropriate evaluation methods according to the different characteristics of each dimension of the triple bottom line separately,especially for the in-depth analysis of the characteristics of the chemical industry.This research first analyzes and summarizes its problems in the decision-making of sustainable supplier selection.Secondly,based on specific characteristics of the chemical industry,this study proposed a hybrid multi-method and multi-criteria decision-making framework for SSS in the chemical industry.The model framework applies Fuzzy Grey Relational Analysis(FGRA),Failure Mode and Effects Analysis(FMEA),and cloud computing-entropy weight method(EWM)to analyze the economic,social,and environmental dimensions,respectively.Subsequently,this study normalizes the evaluation results in the three dimensions using the Decision-making Trial and Evaluation Laboratory(DEMATEL).The results show that the sustainable supplier selection model based on the triple bottom line in this research can help managers of sustainable supply chains in the Company F to choose more sustainable suppliers,respond to market demands quickly,maintain high competitiveness in the market.Finally,this study further verifies the stability and robustness of the proposed framework and decision model through sensitivity analysis and comparative analysis.