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A multiple criteria approach to two-stage data envelopment analysis

机译:多准则两阶段数据包络分析方法

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Two-stage data envelopment analysis (DEA) models are commonly used in the evaluation and benchmarldng of sustainable operations and processes across multiple research fields. To date, however, little attention has been given to the unrealistic weight distribution and weak discrimination power in the modeling and evaluation of the two-stage sustainable operations when using two-stage DEA models. In order to overcome this methodological weakness, we use the multiple criteria DEA (MCDEA) approach in the evaluation of the two-stage processes. The outcome is a multiple criteria two-stage DEA model which yields more realistic weights for the inputs and outputs and thus has better discrimination power than traditional two-stage DEA models. The developed model is tested and validated by assessing the sustainable design performances of a sample of car product designs. (C) 2016 Elsevier Ltd. All rights reserved.
机译:两阶段数据包络分析(DEA)模型通常用于跨多个研究领域的可持续运营和过程的评估和基准测试。但是,迄今为止,在使用两阶段DEA模型进行两阶段可持续运营的建模和评估中,很少有人关注不现实的权重分布和较弱的判别能力。为了克服这种方法上的弱点,我们在评估两个阶段的过程中使用了多准则DEA(MCDEA)方法。结果是一个多标准的两阶段DEA模型,该模型对输入和输出产生更现实的权重,因此比传统的两阶段DEA模型具有更好的判别能力。通过评估汽车产品设计样本的可持续设计性能来测试和验证开发的模型。 (C)2016 Elsevier Ltd.保留所有权利。

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