Xu, Jin and Zervopoulos, Panagiotis and Qian, Zhenhua and Cheng, Gang (2012): A universal solution for units-invariance in data envelopment analysis.
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Abstract
The directional distance function model is a generalization of the radial model in data envelopment analysis (DEA). The directional distance function model is appropriate for dealing with cases where undesirable outputs exist. However, it is not a units-invariant measure of efficiency, which limits its accuracy. In this paper, we develop a data normalization method for DEA, which is a universal solution for the problem of units-invariance in DEA. The efficiency scores remain unchanged when the original data are replaced with the normalized data in the existing units-invariant DEA models, including the radial and slack-based measure models, i.e., the data normalization method is compatible with the radial and slack-based measure models. Based on normalized data, a units-invariant efficiency measure for the directional distance function model is defined.
Item Type: | MPRA Paper |
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Original Title: | A universal solution for units-invariance in data envelopment analysis |
Language: | English |
Keywords: | Data Envelopment Analysis; Data normalization; Units-invariance; Directional distance function |
Subjects: | C - Mathematical and Quantitative Methods > C0 - General > C02 - Mathematical Methods C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C61 - Optimization Techniques ; Programming Models ; Dynamic Analysis C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C67 - Input-Output Models D - Microeconomics > D2 - Production and Organizations > D24 - Production ; Cost ; Capital ; Capital, Total Factor, and Multifactor Productivity ; Capacity |
Item ID: | 41633 |
Depositing User: | Panagiotis Zervopoulos |
Date Deposited: | 01 Oct 2012 13:35 |
Last Modified: | 27 Sep 2019 01:02 |
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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/41633 |