Employing fuzzy DEA for Green-resilient supplier selection in an electronic industry of household appliances: a case study (Snowa)

The choice of green-resilient supplier selection as a complex multi-criterion decision-making problem that often involves some uncertain situations, has become a key issue in the development of electronics manufacturing. Decision-making models supporting the assessment of supply chain performance must consider comprehensive elements in the supply network, covering not only cost and technical capabilities, but also greenness and resilience aspects. Therefore, in order to fill the research gap, the present study proposed an integrated decision-making method based on the fuzzy set theory and data envelopment analysis (DEA) approach for supplier selection in a supply chain network to handle uncertainties caused by decision makers 'subjective judgments which could reduce the supply chain costs and environmental impact and, moreover, extend the value of resilience. A case study was used to validate the applicability of the proposed model. The sensitivity analysis was employed to examine the impact of the proposed model. Furthermore, the proposed DEA-based model has been compared with a supplier selection Fuzzy inference system based method in the literature to show its validation. The results indicated the proposed fuzzy DEA method can provide a reliable and consensus decision-making framework for enterprises to select green-resilient suppliers in the electronic industry of household appliances.