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A new fuzzy DEA model for evaluation of efficiency and effectiveness of suppliers in sustainable supply chain management context

机译:在可持续供应链管理环境下评估供应商效率和有效性的新模糊DEA模型

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Sustainable supply chain management (SSCM) has received much consideration from corporate and academic over the past decade. Sustainable supplier performance evaluation and selection plays a significant role in establishing an effective SSCM. One of the techniques that can be used for sustainable supplier performance evaluation and selection is data envelopment analysis (DEA). In real world problems, the inputs and outputs might be imprecise. This paper develops an integrated DEA enhanced Russell measure (ERM) model in fuzzy context to select the best sustainable suppliers. A case study is presented to exhibit the efficacy of the proposed method for sustainable supplier selection problem in a resin production company. The case study demonstrates that the proposed model can measure effectiveness, efficiency, and productivity in uncertain environment with different α levels. Also, it shows that the proposed model aids decision makers to deal with economic, social, and environmental factors when selecting sustainable suppliers.
机译:在过去的十年中,可持续供应链管理(SSCM)得到了公司和学术界的广泛考虑。可持续的供应商绩效评估和选择在建立有效的SSCM中起着重要作用。可以用于可持续供应商绩效评估和选择的技术之一是数据包络分析(DEA)。在现实世界中,输入和输出可能不准确。本文在模糊背景下开发了集成的DEA增强Russell度量(ERM)模型,以选择最佳的可持续供应商。提出了一个案例研究,以展示所提出方法对树脂生产公司中可持续供应商选择问题的有效性。案例研究表明,所提出的模型可以在不确定的环境中(具有不同的α水平)测量有效性,效率和生产率。此外,它表明,该模型可以帮助决策者在选择可持续供应商时应对经济,社会和环境因素。

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