TY - JOUR
T1 - Alternative solutions for classifying inputs and outputs in data envelopment analysis
AU - Toloo, Mehdi
N1 - Funding Information:
Mehdi Toloo would like to thank the anonymous reviewers and the editor, Prof. E. Y. Rodin, for their insightful comments and suggestions. This study was supported in part by Islamic Azad University, Central Tehran Branch, Tehran, Iran.
PY - 2012/3
Y1 - 2012/3
N2 - In conventional data envelopment analysis (DEA) models, a performance measure whether as an input or output usually has to be known. Nevertheless, in some cases, the type of a performance measure is not clear and some models are introduced to accommodate such flexible measures. In this paper, it is shown that alternative optimal solutions of these models has to be considered to deal with the flexible measures, otherwise incorrect results might occur. Practically, the efficiency scores of a DMU could be equal when the flexible measure is considered either as input or output. These cases are introduced and referred as share cases in this study specifically. It is duplicated that share cases must not be taken into account for classifying inputs and outputs. A new mixed integer linear programming (MILP) model is proposed to overcome the problem of not considering the alternative optimal solutions of classifier models. Finally, the applicability of the proposed model is illustrated by a real data set.
AB - In conventional data envelopment analysis (DEA) models, a performance measure whether as an input or output usually has to be known. Nevertheless, in some cases, the type of a performance measure is not clear and some models are introduced to accommodate such flexible measures. In this paper, it is shown that alternative optimal solutions of these models has to be considered to deal with the flexible measures, otherwise incorrect results might occur. Practically, the efficiency scores of a DMU could be equal when the flexible measure is considered either as input or output. These cases are introduced and referred as share cases in this study specifically. It is duplicated that share cases must not be taken into account for classifying inputs and outputs. A new mixed integer linear programming (MILP) model is proposed to overcome the problem of not considering the alternative optimal solutions of classifier models. Finally, the applicability of the proposed model is illustrated by a real data set.
KW - Data envelopment analysis
KW - Efficiency
KW - Flexible measure
KW - Mixed integer linear program
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U2 - 10.1016/j.camwa.2011.12.016
DO - 10.1016/j.camwa.2011.12.016
M3 - Article
AN - SCOPUS:84857792758
SN - 0898-1221
VL - 63
SP - 1104
EP - 1110
JO - Computers and Mathematics with Applications
JF - Computers and Mathematics with Applications
IS - 6
ER -