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- W2990351738 abstract "Appropriate supplier selection due to its direct impact on profitability and maintaining the competitive status of an organization is one of the vital decisions for each company. Data envelopment analysis (DEA) is a proper tool for measuring the sustainability of suppliers. Classic DEA models suppose that inputs and outputs are deterministic; consequently, the relative efficiencies of suppliers are also deterministic. However, in real-life applications, all inputs and outputs are not deterministic. Some could be stochastic and/or fuzzy. This study consists of four types of supplier selection models in supply chains and provides a decision making scheme for selecting appropriate model for supplier selection under deterministic, stochastic and fuzzy conditions. The proposed stochastic-fuzzy DEA model (SFDEA) can be solved as crisp program for each α∈01 using α-cut method. This is the first study to a present a flexible approach for evaluating supplier’s sustainability in supply chain management. A case study is presented for validating the proposed model." @default.
- W2990351738 created "2019-12-05" @default.
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- W2990351738 date "2020-01-01" @default.
- W2990351738 modified "2023-10-03" @default.
- W2990351738 title "Assessing sustainability of suppliers: A novel stochastic-fuzzy DEA model" @default.
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- W2990351738 doi "https://doi.org/10.1016/j.spc.2019.11.001" @default.
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