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两阶段 DEA 方法用于环境效率测度。

A two-stage DEA approach for environmental efficiency measurement.

机构信息

School of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Bengbu, 233030, China,

出版信息

Environ Monit Assess. 2014 May;186(5):3041-51. doi: 10.1007/s10661-013-3599-z. Epub 2014 Jan 8.

Abstract

The slacks-based measure (SBM) model based on the constant returns to scale has achieved some good results in addressing the undesirable outputs, such as waste water and water gas, in measuring environmental efficiency. However, the traditional SBM model cannot deal with the scenario in which desirable outputs are constant. Based on the axiomatic theory of productivity, this paper carries out a systematic research on the SBM model considering undesirable outputs, and further expands the SBM model from the perspective of network analysis. The new model can not only perform efficiency evaluation considering undesirable outputs, but also calculate desirable and undesirable outputs separately. The latter advantage successfully solves the "dependence" problem of outputs, that is, we can not increase the desirable outputs without producing any undesirable outputs. The following illustration shows that the efficiency values obtained by two-stage approach are smaller than those obtained by the traditional SBM model. Our approach provides a more profound analysis on how to improve environmental efficiency of the decision making units.

摘要

基于不变规模报酬的松弛测度(SBM)模型在处理废水和水煤气等不良产出的环境效率衡量方面取得了一些较好的成果。然而,传统的 SBM 模型无法处理期望产出为常数的情况。基于生产力的公理化理论,本文对考虑不良产出的 SBM 模型进行了系统研究,并进一步从网络分析的角度扩展了 SBM 模型。新模型不仅可以进行考虑不良产出的效率评估,还可以分别计算期望产出和不良产出。后一个优势成功解决了产出的“依赖性”问题,即我们不能在不产生任何不良产出的情况下增加期望产出。下面的例子表明,两阶段方法得到的效率值小于传统 SBM 模型得到的效率值。我们的方法为如何提高决策单元的环境效率提供了更深入的分析。

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