Abstract
The supply chain (SC) represents a network of activities that seeks to deliver products to consumers all around the world. Globalization has led to fluctuations and disruptions in the SC. Presently, alarming disruptions are caused by increasing amounts of industrial waste, greenhouse gasses, and other types of wastage that have engendered environmental pollution. To reduce these disruptions and control environmental impacts, the notion of the green-resilient (G-resilient) SC can prove to be particularly helpful. One of the most important processes of the G-resilient SC is supplier selection. The purpose of this study was to identify the criteria for evaluating G-resilient suppliers. To accomplish its objectives, the study proposed two hypotheses: (a) G-resilient supplier selection could bring about acceptable results and (b) the proposed hesitant fuzzy multi-criteria decision-making model could help to validly select G-resilient suppliers. To test the above hypotheses, the criteria were primarily extracted through reviewing the literature. The hesitant fuzzy best–worst method was used to determine the weights of the criteria, while the hesitant fuzzy evaluation based on distance from average solution method was employed to rank the G-resilient suppliers. Then, sensitivity analysis was conducted to test the hypotheses. The results revealed that, to evaluate G-resilient suppliers, four dimensions must be considered: production, green quality, organizational aspects, and resilience. Considering these four dimensions would provide a more comprehensive insight into evaluating G-resilient suppliers. Results of the ranking also clarified that the suppliers were similarly ranked through different hesitant fuzzy methods. As such, the two hypotheses were confirmed. Findings also demonstrated that “technology” was the most important indicator in evaluating G-resilient suppliers. Using new technologies, organizations cannot only select best suppliers by having full access to their information, but also they can register smart orders, which would help to desist from wasting resources, improve organizational performance, and reduce environmental pollution. This study suggested practical implications that could guide decision-makers in organizations on how to implement G-resilient factors in their supplier selection process, especially when they faced hesitations in supplier evaluation. The novelty of the study were the construction of a G-resilient supplier evaluation model and the application of hesitant fuzzy methods in analyzing the data.
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Abbreviations
- SCs:
-
Supply chains
- G-resilient:
-
Green-resilient
- MCDM:
-
Multi-criterion decision-making
- HFS:
-
Hesitant fuzzy sets
- BWM:
-
Best–worst method
- HFBWM:
-
Hesitant fuzzy best–worst method
- HFEDAS:
-
Hesitant fuzzy evaluation based on distance from average solution
- HFCODAS:
-
Hesitant fuzzy combinative distance-based assessment
- HFARAS:
-
Hesitant fuzzy additive ratio assessment
- HFCOPRAS:
-
Hesitant fuzzy complex proportional assessment
- HFWASPAS:
-
Hesitant fuzzy weighted aggregated sum product assessment
- HFVIKOR:
-
Hesitant fuzzy vlse kriterijumsk optimizacija kompromisno resenje
- HFMULTIMOORA:
-
Hesitant fuzzy multiple-objective optimization on the basis of ratio analysis plus full multiplicative form
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Alimohammadlou, M., Khoshsepehr, Z. Green-resilient supplier selection: a hesitant fuzzy multi-criteria decision-making model. Environ Dev Sustain (2022). https://doi.org/10.1007/s10668-022-02454-9
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DOI: https://doi.org/10.1007/s10668-022-02454-9