应用非径向DEA对不良产出进行可持续性分析

Yu-Jie Wang, T. Han
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引用次数: 1

摘要

企业认识到可持续性是管理中的一个重要问题。不幸的是,在可持续性测量中存在着增加理想产出和减少不理想产出的问题。过去,Hwang等人开发了一个径向DEA模型,该模型同时评估了不期望产出的减少和愿望产出的增加,重点是识别汽车工业的低效率。实际上,径向DEA模型不能反映具有众多输入和输出的决策单元(DMU)的所有效率/低效率,而非径向DEA模型则可以。为了解决上述问题,本文将非径向数据包络分析(DEA)应用于可持续发展的不良产出。我们的应用非径向DEA提供了产生生计效率(如暴力犯罪的效率)或生态效率(如碳排放、气体排放、水污染和固体废物的效率)的测量方法,并进一步提高效率,同时最大限度地减少可持续性的不良产出。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Applying non-radial DEA on undesirable outputs for sustainability
Enterprises recognize sustainability as an important issue in management. Unfortunately, there are problems of increasing desirable outputs and decreasing undesirable outputs in sustainability measurement. In the past, Hwang et al. developed a radial DEA model that simultaneously evaluated decrease of undesirable outputs and increase of desire outputs with a focus on identifying inefficiency of automobile industry. Practically, a radial DEA model doesn't reflect all efficiency/inefficiency of a decision-making unit(DMU) with numerous inputs and outputs, whereas a non-radial DEA model does. To solve the tie above, we apply non-radial data envelopment analysis(DEA) on undesirable outputs for sustainability in this paper. Our applied non-radial DEA provides measurement to yield the livelihood-efficiency such as the efficiencies number of violent crimes or the eco-efficiency such as the efficiencies of carbon emissions, gas emissions, water pollution and solid wastes, and further improving efficiencies while minimizing the undesirable outputs in sustainability.
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