DEA数据标准化方法及其在方向距离函数模型中的应用

Cheng, Gang and Qian, Zhenhua (2011): DEA数据标准化方法及其在方向距离函数模型中的应用.

Abstract

Directional distance function is the generalization of radial model in data envelopment analysis. It has the capacity of dealing with undesirable outputs, but the problem is that it has no unit-invariant measurement of efficiency, which hampers its application to empirical studies. Data normalization for data envelopment analysis is a universal solution for the problem of unit-invariance, and the efficiency keeps unchanged in radial and non-radial models after data normalization. A unit-invariant efficiency measure for directional distance function is developed based on DEA data normalization.

• Item Type: MPRA Paper
• English Title: Data normalization for data envelopment analysis and its application to directional distance function
• Language: Chinese
• Keywords: Data Envelopment Analysis; Data Normalization; Units Invariance; Directional Distance Function
• Subjects: C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling

References

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