Some comments on improving discriminating power in data envelopment models based on deviation variables framework
Article
Article Title | Some comments on improving discriminating power in data envelopment models based on deviation variables framework |
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ERA Journal ID | 148 |
Article Category | Article |
Authors | Mahdiloo, Mahdi (Author), Lim, Sungmook (Author), Duong, Thach-Thao (Author) and Harvie, Charles (Author) |
Journal Title | European Journal of Operational Research |
Journal Citation | 295 (1), pp. 394-397 |
Number of Pages | 4 |
Year | 2021 |
Publisher | Elsevier |
Place of Publication | Netherlands |
ISSN | 0377-2217 |
1872-6860 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.ejor.2021.02.056 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S0377221721001697 |
Abstract | Ghasemi, Ignatius, and Rezaee (2019) (Improving discriminating power in data envelopment models based on deviation variables framework. European Journal of Operational Research 278, 442– 447) propose a procedure for ranking efficient units in data envelopment analysis (DEA) based on the deviation variables framework. They claim that their procedure improves the discriminating power of DEA and can be an alternative to the super-efficiency model that is well-known to have the infeasibility problem and the cross-efficiency approach which suffers from the presence of multiple optimal solutions. However, we demonstrate, in this short note, that their procedure is developed based upon inappropriate use of deviation variables which leads to the development of a ranking approach that does not meet their expectations and as a result, an unreasonable ranking of decision making units (DMUs). We also show that the use of deviation variables, if interpreted and used correctly, can lead to developing a cross-inefficiency matrix and approach. |
Keywords | Cross-inefficiency; Data envelopment analysis; Deviation variables; Discriminating power; Ranking |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
Byline Affiliations | University of Wollongong |
Dongguk University, Korea | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q710x/some-comments-on-improving-discriminating-power-in-data-envelopment-models-based-on-deviation-variables-framework
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