The ranking of the decision making units (DMUs) is an essential problem in data envelopment analysis (DEA). Numerous approaches have been proposed for fully ranking of units. Majority of these methods consider DMUs with optimistic approach, whereas their weaknesses are ignored. In this study, for fully ranking of the units, a modified optimistic–pessimistic approach, which is based on game cross efficiency idea is proposed. The proposed game like iterative optimistic-pessimistic DEA procedure calculates the efficiency scores according to weaknesses and strengths of units and is based on non-cooperative game. This study extends the optimistic-pessimistic DEA approach to obtain robust rank values for DMUs. The proposed approach yields Nash equilibrium solution, thus overcomes the problem of non-uniqueness of the DEA optimal weights that can possibly reduce the usefulness of cross efficiency. Finally, in order to verify the validity of the proposed model and to show the practicability of algorithm, we apply a real-world example for selection of industrial R&D projects. The proposed model can increase the discriminating power of DMUs and can fully rank the DMUs.
Mots-clés : Optimistic-pessimistic DEA, game cross efficiency, fully ranking
@article{RO_2020__54_4_1215_0, author = {\"Orkc\"u, Mediha and \"Ozsoy, Volkan Soner and \"Orkc\"u, H. Hasan}, title = {An optimistic-pessimistic {DEA} model based on game cross efficiency approach}, journal = {RAIRO - Operations Research - Recherche Op\'erationnelle}, pages = {1215--1230}, publisher = {EDP-Sciences}, volume = {54}, number = {4}, year = {2020}, doi = {10.1051/ro/2019052}, language = {en}, url = {http://archive.numdam.org/articles/10.1051/ro/2019052/} }
TY - JOUR AU - Örkcü, Mediha AU - Özsoy, Volkan Soner AU - Örkcü, H. Hasan TI - An optimistic-pessimistic DEA model based on game cross efficiency approach JO - RAIRO - Operations Research - Recherche Opérationnelle PY - 2020 SP - 1215 EP - 1230 VL - 54 IS - 4 PB - EDP-Sciences UR - http://archive.numdam.org/articles/10.1051/ro/2019052/ DO - 10.1051/ro/2019052 LA - en ID - RO_2020__54_4_1215_0 ER -
%0 Journal Article %A Örkcü, Mediha %A Özsoy, Volkan Soner %A Örkcü, H. Hasan %T An optimistic-pessimistic DEA model based on game cross efficiency approach %J RAIRO - Operations Research - Recherche Opérationnelle %D 2020 %P 1215-1230 %V 54 %N 4 %I EDP-Sciences %U http://archive.numdam.org/articles/10.1051/ro/2019052/ %R 10.1051/ro/2019052 %G en %F RO_2020__54_4_1215_0
Örkcü, Mediha; Özsoy, Volkan Soner; Örkcü, H. Hasan. An optimistic-pessimistic DEA model based on game cross efficiency approach. RAIRO - Operations Research - Recherche Opérationnelle, Tome 54 (2020) no. 4, pp. 1215-1230. doi : 10.1051/ro/2019052. http://archive.numdam.org/articles/10.1051/ro/2019052/
[1] Ranking ranges in cross efficiency evaluations. Eur. J. Oper. Res. 226 (2013) 516–521. | DOI | Zbl
, and , ,[2] Measuring the efficiency of decision-making units. Eur. J. Oper. Res. 2 (1978) 429–444. | DOI | Zbl
, and ,[3] Optimizing the rank position of the DMU as secondary goal in DEA cross-evaluation. Appl. Math. Model. 36 (2012) 2642–2648. | DOI | Zbl
,[4] Applied Nonparametric Statistics, Boston, Houghton Mifflin (1978). | Zbl
,[5] Efficiency and cross efficiency in DEA: derivations, meanings and uses. J. Oper. Res. Soc. 45 (1994) 567–578. | DOI | Zbl
and ,[6] Cross-Evaluation in DEA: improving discrimination among DMUs, INFOR: Inf. Syst. Oper. Res. 33 (1995) 205–222. | Zbl
, ,[7] A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016. Socio-Economic Planning Sci. 61 (2018) 4–8. | DOI
and ,[8] A mean-maverick game cross-efficiency approach to portfolio selection: an application to Paris stock exchange. Expert Syst. Appl. 113 (2018) 161–185. | DOI
, and ,[9] Preference voting and project ranking using DEA and cross-evaluation. Eur. J. Oper. Res. 90 (1996) 461–472. | DOI | Zbl
, , ,[10] Selecting symmetric weights as a secondary goal in DEA cross efficiency evaluation. Appl. Math. Model. 35 (2011) 544–549. | DOI | Zbl
, , , ,[11] Ranking all units in data envelopment analysis. Appl. Math. Lett. 25 (2012) 2066–2070. | DOI | Zbl
and ,[12] The cross efficiency in the optimistic– pessimistic framework. Oper. Res. 17 (2017) 619–632.
and ,[13] A balanced data envelopment analysis cross-efficiency evaluation approach. Expert Syst. Appl. 106 (2018) 154–168. | DOI
, , and ,[14] Allocating a fixed cost based on a DEA- game cross efficiency approach. Expert Syst. Appl. 96 (2018) 196–207. | DOI
, and ,[15] Alternative secondary goals in DEA cross-efficiency evaluation. Int. J. Prod. Econ. 113 (2008a) 1025–1030. | DOI
, , and ,[16] The DEA game cross-efficiency mode and its Nash equilibrium. Oper. Res. 56 (2008b) 1278–1288. | DOI | Zbl
, , and ,[17] Minimax and maximin formulations of cross efficiency in DEA. Comput. Ind. Eng. 62 (2012) 726–731. | DOI
,[18] An aggressive game cross efficiency evaluation in data envelopment analysis. Ann. Oper. Res. 259 (2017) 241–258. | DOI
, and ,[19] A DEA ranking method based on cross efficiency intervals and signal-to-noise ratio. Ann. Oper. Res. 261 (2018) 207–232. | DOI
,[20] A methodology for collective evaluation and selection of industrial R&D projects. Manage. Sci. 37 (1991) 871–885. | DOI | Zbl
, and ,[21] Maximum appreciative cross efficiency in DEA: a new ranking method. Comput. Ind. Eng. 81 (2015) 14–21. | DOI
and ,[22] Goal programming approaches for data envelopment analysis cross efficiency evaluation. Appl. Math. Comput. 218 (2011) 346–356. | Zbl
and ,[23] On the choice of weights profiles in cross efficiency evaluations. Eur. J. Oper. Res. 207 (2010) 1564–1572. | DOI
, and ,[24] Reducing differences between profiles of weights: a ``peer-restricted’’ cross efficiency evaluation. Omega 39 (2011) 634–641. | DOI
, and ,[25] Cross efficiency evaluation with directional distance functions. Eur. J. Oper. Res. 228 (2013) 181–189. | DOI
,[26] Data envelopment analysis: critique and extensions. New Directions Eval. 32 (1986) 73–105. | DOI
, and ,[27] DEA game cross-efficiency model to urban public infrastructure investment comprehensive efficiency of China. Math. Prob. Eng. (2016) 1–10.
, and ,[28] Some alternative models for DEA cross efficiency evaluation. Int. J. Prod. Econ. 128 (2010a) 332–338. | DOI
and ,[29] A neutral DEA model for cross efficiency evaluation and its extension. Expert Syst. Appl. 37 (2010b) 3666–3675. | DOI
and ,[30] The use of OWA operator weights for cross efficiency aggregation. Omega 39 (2011) 493–503. | DOI
and ,[31] Weight determination in the cross efficiency evaluation. Comput. Ind. Eng. 61 (2011a) 497–502. | DOI
, and ,[32] Cross efficiency evaluation based on ideal and anti-ideal decision-making units. Expert Syst. Appl. 38 (2011b) 10312–10319. | DOI
, and ,[33] Determination of the weights for the ultimate cross efficiency using Shapley value in cooperative game. Expert Syst. Appl. 36 (2009a) 872–876. | DOI
, and ,[34] Determination of cross efficiency under the principle of rank priority in cross-evaluation. Expert Syst. Appl. 36 (2009b) 4826–4829. | DOI
, , and ,[35] Determination of weights for ultimate cross efficiency using Shannon entropy. Expert Syst. Appl. 38 (2011) 5162–5165. | DOI
, , and ,[36] Cross efficiency evaluation method based on weight-balanced data envelopment analysis model. Comput. Ind. Eng. 63 (2012) 513–519. | DOI
, and ,[37] Extended secondary goal models for weights selection in DEA cross efficiency evaluation. Comput. Ind. Eng. 93 (2016) 143–151. | DOI
, , , and ,[38] The environmental efficiency analysis of China’s power generation sector based on game cross-efficiency approach. Struct. Change Econ. Dyn. 46 (2018) 126–135. | DOI
, , , and ,[39] Modelling efficient and anti-efficient frontiers in DEA without explicit inputs. Int. J. Oper. Res. 35 (2019) 505–528. | DOI
and ,[40] Estimating Malmquist indices and semi-parametric censored regressions with a coherent data-generating process. IMA J. Manage. Math. 26 (2015) 63–81.
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