Dea数据标准化方法及其在方向距离函数模型中的应用
[Data normalization for data envelopment analysis and its application to directional distance function]
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.Download Info
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 31995.Length:
Date of creation: 10 Mar 2011
Date of revision:
Handle: RePEc:pra:mprapa:31995
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Related research
Keywords: Data Envelopment Analysis; Data Normalization; Units Invariance; Directional Distance Function;Find related papers by JEL classification:
- C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-07-13 (All new papers)
- NEP-EFF-2011-07-13 (Efficiency & Productivity)
References
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- Cook, Wade D. & Seiford, Larry M., 2009. "Data envelopment analysis (DEA) - Thirty years on," European Journal of Operational Research, Elsevier, vol. 192(1), pages 1-17, January.
- R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
- Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
- Fare, Rolf & Knox Lovell, C. A., 1978. "Measuring the technical efficiency of production," Journal of Economic Theory, Elsevier, vol. 19(1), pages 150-162, October.
- Chambers, Robert G. & Chung, Yangho & Fare, Rolf, 1996. "Benefit and Distance Functions," Journal of Economic Theory, Elsevier, vol. 70(2), pages 407-419, August.
- Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
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