TY - JOUR
T1 - Some comments on improving discriminating power in data envelopment models based on deviation variables framework
AU - Mahdiloo, Mahdi
AU - Lim, Sungmook
AU - Duong, Thach Thao
AU - Harvie, Charles
N1 - Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/11/16
Y1 - 2021/11/16
N2 - 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.
AB - 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.
KW - Cross-inefficiency
KW - Data envelopment analysis
KW - Deviation variables
KW - Discriminating power
KW - Ranking
UR - http://www.scopus.com/inward/record.url?scp=85103044361&partnerID=8YFLogxK
U2 - 10.1016/j.ejor.2021.02.056
DO - 10.1016/j.ejor.2021.02.056
M3 - Article
AN - SCOPUS:85103044361
SN - 0377-2217
VL - 295
SP - 394
EP - 397
JO - European Journal of Operational Research
JF - European Journal of Operational Research
IS - 1
ER -