Green Suppliers Performance Evaluation in Belt and Road Using Fuzzy Weighted Average with Social Media Information

Abstract

A decision model for selecting a suitable supplier is a key to reducing the environmental impact in green supply chain management for high-tech companies. Traditional fuzzy weight average (FWA) adopts linguistic variable to determine weight by experts. However, the weights of FWA have not considered the public voice, meaning the viewpoints of consumers in green supply chain management. This paper focuses on developing a novel decision model for green supplier selection in the One Belt and One Road (OBOR) initiative through a fuzzy weighted average approach with social media. The proposed decision model uses the membership grade of the criteria and sub-criteria and its relative weights, which consider the volume of social media, to establish an analysis matrix of green supplier selection. Then, the proposed fuzzy weighted average approach is considered as an aggregating tool to calculate a synthetic score for each green supplier in the Belt and Road initiative. The final score of the green supplier is ordered by a non-fuzzy performance value ranking method to help the consumer make a decision. A case of green supplier selection in the light-emitting diode (LED) industry is used to demonstrate the proposed decision model. The findings demonstrate (1) the consumer’s main concerns are the “Quality” and “Green products” in LED industry, hence, the ranking of suitable supplier in FWA with social media information model obtained the difference result with tradition FWA; (2) OBOR in the LED industry is not fervently discussed in searches of Google and Twitter; and (3) the FWA with social media information could objectively analyze the green supplier selection because the novel model considers the viewpoints of the consumer.