广义数据包络分析模型回归尺度性质的充要条件

Q. Wei, Gang Yu, Jianshou Lu
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引用次数: 12

摘要

在广义数据包络分析(GDEA)模型下,给出了规模收益递增、不变和递减的定义。GDEA模型处理锥体结构来描述评估者对不同决策单元(DMU)和不同输入/输出类别的偏好。GDEA模型包含了许多重要的DEA模型作为它的子类。在此基础上,讨论并严格证明了一个DMU在GDEA模型下具有规模收益递增、不变和递减的充分必要条件,并讨论和阐明了这些条件在GDEA模型不同子类下的区别和关系。此外,我们还描述了一种基于两阶段线性规划的方法来测试比例属性的回报。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The necessary and sufficient conditions for returns to scale properties in generalized data envelopment analysis model
We give definitions on increasing, constant and decreasing returns to scale under the generalized data envelopment analysis (GDEA) model. The GDEA model prossesses cone structures for describing evaluators’ preferences toward different decision making units (DMU) and toward different input / output categories. The GDEA model contains many important DEA models as its subclasses. Based upon the definition, we discuss and rigorously prove the necessary and sufficient conditions for a DMU to have increasing, constant and decreasing returns to scale under a GDEA model, and discuss and clarify the differences and relationships of these conditions under different subclasses of the GDEA model. Furthermore, we describe a method based on a two-stage linear program to test returns to scale properties.
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