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Article

MSC: 90Bxx, 90C05
Keywords:
data envelopment analysis; least distance; FDH; target unit
Summary:
Recently, some authors used the Least-Distance Measure model in order to obtain the shortest distance between the evaluated Decision Making Unit (DMU) and the strongly efficient production frontier. But, their model is not applicable for situation in which the production possibility set satisfies free disposability property. In this paper, we propose a new approach to this end in FDH model which improves the application potential of the Least-Distance Measure and overcomes the mentioned shortcoming. The applicability of the proposed method is illustrated with two numerical examples and proves to be persuasive and acceptable to real-world problem.
References:
[1] Baek, C., Lee, J.: The relevance of DEA benchmarking information and the least-distance measure. Math. Comput. Modelling 49 (2009), 265-275. DOI 10.1016/j.mcm.2008.08.007 | MR 2480049 | Zbl 1165.90484
[2] Bogetoft, P., Hougaard, J. L.: Efficiency evaluations based on potential (non-proportional) improvements. J. Productivity Anal. 12 (1998), 233-249. DOI 10.1023/A:1007848222681
[3] Bogetoft, P., Nielsen, K.: Internet based benchmarking. Group Decision and Negotiation 14 (2005), 195-215. DOI 10.1007/s10726-005-6493-4
[4] Charnes, A., Cooper, W., Rhodes, E.: Measuring the efficiency of decision making units. European J. Oper. Res. 2 (1978), 429-444. DOI 10.1016/0377-2217(78)90138-8 | MR 0525905 | Zbl 0425.90086
[5] Cherchye, L., Puyenbroeck, T. V.: A comment on multi-stage DEA methodology. Oper. Res. Lett. 28 (2001), 93-98. DOI 10.1016/S0167-6377(00)00068-7 | MR 1822694 | Zbl 1016.91022
[6] Coelli, T.: A multi-stage methodology and for the solution of oriented DEA models. Oper. Res. Lett. 23 (1998), 143-149. DOI 10.1016/S0167-6377(98)00036-4 | MR 1677668
[7] Cooper, W. W., Park, K. S., Pastor, J. T., RAM: A range adjusted measure of inefficiency for use with additive models and relations to other models and measures in DEA. J. Productivity Anal. 11 (1999), 5-42.
[8] Deprins, D., Simar, L., Tulkens, H.: Measuring labor inefficiency in post offices. In: The Performance of Public Enterprises: Concepts and Measurements (M. Marchand, P. Pestieau, and H. Tulkens, eds.), North-Holland, Amsterdam 1984.
[9] Lins, M. P. Estellita, Angulo-Meza, L., Silva, A. C. Moreira da: A multi-objective approach to determine alternative targets in data envelopment analysis. J. Oper. Res. Soc. 55 (2004), 1090-1101. DOI 10.1057/palgrave.jors.2601788
[10] Ebrahimnejad, A., Lotfi, F. Hosseinzadeh: Equivalence relationship between the general combined-oriented CCR model and the weighted minimax MOLP formulation. J. King Saud Univ. Sci. 24 (2012), 47-54. DOI 10.1016/j.jksus.2010.08.007
[11] Frei, F. X., Harker, P. T.: Projections onto efficient frontier: Theoretical and computational extension to DEA. J. Productivity Anal. 11 (1999), 275-300. DOI 10.1023/A:1007746205433
[12] Golany, B.: An interactive MOLP procedure for the extension of DEA to effectiveness analysis. J. Oper. Res. Soc. 39 (1988), 725-734. Zbl 0655.90042
[13] González, E., Álvarez, A.: From efficiency measurement to efficiency improvement: The choice of a relevant benchmark. European J. Oper. Res. 133 (2001), 512-520. DOI 10.1016/S0377-2217(00)00195-8 | Zbl 1002.90530
[14] Li, X. B., Reeves, G. R.: A multiple criteria approach to data envelopment analysis. European J. Oper. Res. 115 (1999), 507-517. DOI 10.1016/S0377-2217(98)00130-1 | Zbl 0953.91022
[15] Pastor, J. T., Aparicio, J.: The relevance of DEA benchmarking information and the least-distance measure: Comment. Math. Comput. Modelling 52 (2010), 397-399. DOI 10.1016/j.mcm.2010.03.010 | MR 2645951 | Zbl 1201.65001
[16] Portela, M. C. A. S., Borges, P. C., Thanassoulis, E.: Finding closest targets in non-oriented DEA models: The case of convex and non-convex technology. J. Productivity Anal. 19 (2003), 251-269. DOI 10.1023/A:1022813702387
[17] Post, T., Spronk, J.: Performance benchmarking using interactive data envelopment analysis. European J. Oper. Res. 115 (1999), 472-487. DOI 10.1016/S0377-2217(98)00022-8 | Zbl 0947.91051
[18] Thanassoulis, E., Dyson, R. G.: Estimating preferred target input output levels using data envelopment analysis. European J. Oper. Res. 56 (1992), 80-97. DOI 10.1016/0377-2217(92)90294-J | Zbl 0825.90088
[19] Tone, K.: A slack-based measure of efficient in data envelopment analysis. European J. Oper. Res. 130 (2001), 498-509. DOI 10.1016/S0377-2217(99)00407-5 | MR 1816667
[20] Yang, J. B., Wang, B. Y., Xu, D. L., Stewart, T.: Integrating DEA-oriented performance assessment and target setting using interactive MOLP methods. European J. Oper. Res. 195 (2009), 205-222. DOI 10.1016/j.ejor.2008.01.013
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