Detailed Information

Cited 3 time in webofscience Cited 3 time in scopus
Metadata Downloads

Some comments on improving discriminating power in data envelopment models based on deviation variables framework

Authors
Mahdiloo, MahdiLim, SungmookDuong, Thach-ThaoHarvie, Charles
Issue Date
16-Nov-2021
Publisher
ELSEVIER
Keywords
Data envelopment analysis; Ranking; Discriminating power; Deviation variables; Cross-inefficiency
Citation
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, v.295, no.1, pp 394 - 397
Pages
4
Indexed
SCIE
SCOPUS
Journal Title
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Volume
295
Number
1
Start Page
394
End Page
397
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/4163
DOI
10.1016/j.ejor.2021.02.056
ISSN
0377-2217
1872-6860
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. (c) 2021 Elsevier B.V. All rights reserved.
Files in This Item
There are no files associated with this item.
Appears in
Collections
Dongguk Business School > Department of Business Administration > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Lim, Sung Mook photo

Lim, Sung Mook
Dongguk Business School (Department of Business Administration)
Read more

Altmetrics

Total Views & Downloads

BROWSE