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A grey-based green supplier selection model for uncertain environments

机译:不确定环境的基于灰色的绿色供应商选择模型

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The concept of green supply chain management emerged as a response to increasing public awareness of environmental protection in the past few decades. As companies tend to outsource a variety of their activities, green supplier selection as an imperative function of green supply chain management, has a crucial role in helping companies to maintain their strategic competitiveness. Despite the plethora of studies introducing supplier selection models based on economic criteria, studies that take into account the environmental issues are rather limited. In this study, a comprehensive grey-based green supplier selection model is proposed that incorporates both economic and environmental criteria. A novel weight assignment model is proposed by combining best-worst method and fuzzy grey cognitive maps to capture the interdependencies among the criteria. Improved grey relational analysis is advanced to be able to use grey weights of criteria to evaluate green suppliers which are subsequently ranked using an interval analysis approach. This study contributes to the decision-making theory by addressing the shortcomings of the available green supplier selection models. A real-world case study is also presented to show the applicability and effectiveness of the proposed model. The results of this study proved the proposed comprehensive model to be well capable of addressing the green supplier selection problem by taking in to account the interdependencies between criteria as well as the uncertainties associated with experts' judgments. (C) 2019 Elsevier Ltd. All rights reserved.
机译:绿色供应链管理的概念成为过去几十年来增加公众对环境保护意识的回应。随着公司倾向于外包各种活动,绿色供应商作为绿色供应链管理的命令函数,在帮助公司保持战略竞争力方面具有至关重要的作用。尽管普遍研究了基于经济标准的供应商选择模型,但考虑到环境问题的研究相当有限。在本研究中,提出了一种综合的灰色绿色供应商选择模型,包括经济和环境标准。通过组合最佳方法和模糊灰色认知图来提出一种新颖的重量分配模型来捕获标准中的相互依赖性。改进的灰色关系分析是能够使用灰度的标准来评估随后使用间隔分析方法排列的绿色供应商。本研究通过解决可用绿色供应商选择模型的缺点来促进决策理论。还提出了一个真实的案例研究以表明所提出的模型的适用性和有效性。本研究的结果证明了拟议的综合模式,能够通过考虑标准与专家判决的不确定性来解决绿色供应商选择问题。 (c)2019 Elsevier Ltd.保留所有权利。

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