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Improving the discrimination power and weights dispersion in the data envelopment analysis. (English) Zbl 1171.90418
Summary: Data envelopment analysis (DEA) has been a very popular method for measuring and benchmarking relative efficiency of peer decision making units (DMUs) with multiple input and outputs. Beside of its popularity, DEA has some drawbacks such as unrealistic input-output weights and lack of discrimination among efficient DMUs. In this study, two new models based on a multi-criteria data envelopment analysis (MCDEA) are developed to moderate the homogeneity of weights distribution by using goal programming (GP). These goal programming data envelopment analysis models, GPDEA-CCR and GPDEA-BCC, also improve the discrimination power of DEA.

90B50 Management decision making, including multiple objectives
90C29 Multi-objective and goal programming
Full Text: DOI
[1] Charnes, A.; Cooper, W.W.; Rhodes, E., Measuring the efficiency of decision making units, European journal of operational research, 2, 429-444, (1978) · Zbl 0416.90080
[2] Andersen, P.; Petersen, N., A procedure for ranking efficient units in data envelopment analysis, Management science, 39, 10, 1261-1264, (1993) · Zbl 0800.90096
[3] Meza, L.A.; Lins, M.P.E., Review of methods for increasing discrimination in data envelopment analysis, Annals of operations research, 116, 225-242, (2002) · Zbl 1013.90133
[4] Li, X.B.; Reeves, G.R., A multiple criteria approach to data envelopment analysis, European journal of operational research, 115, 507-517, (1999) · Zbl 0953.91022
[5] Baker, R.C.; Talluri, S., A closer look at the use of data envelopment analysis for technology selection, Computers and industrial engineering, 32, 1, 101-108, (1997)
[6] Sexton TR, Silkman RH, Hogan AJ. Data envelopment analysis: critique and extension. In: Silkman RH. (editor). Measuring efficiency: an assesment of data envelopment analysis, Jossey-Bass, San Fransisco, vol. 32, 1986, pp. 73-105.
[7] Anderson, T.R.; Hollingsworth, K.B.; Inman, L.B., The fixed weighting nature of a cross evaluation model, Journal of productivity analysis, 18, 1, 249-255, (2002)
[8] Doyle, J.R.; Green, R., Efficiency and cross-efficiency in data envelopment analysis: derivatives, meanings and uses, Journal of operational research society, 45, 5, 567-578, (1994) · Zbl 0807.90016
[9] Charnes, A.; Cooper, W.W.; Huang, Z.M.; Sun, D.B., Polyhedral cone-ratio models with an illustrative application to large commercial banks, Journal of econometrics, 46, 73-91, (1990) · Zbl 0712.90015
[10] Thompson, R.G.; Singleton, F.G.; Thrall, R.M.; Smith, B.A., Comparative site evaluations for locating a high-energy physics lab in Texas, Interfaces, 16, 35-49, (1986)
[11] Thompson, R.G.; Langemeier, L.N.; Lee, C.T.; Thrall, R.M., The role of multiplier bounds in efficiency analysis with application to kansas farming, Journal of econometrics, 46, 93-108, (1990)
[12] Wong, Y.H.B.; Beasley, J.E., Restricting weight flexibility in data envelopment analysis, Journal of the operational research society, 41, 9, 829-835, (1990) · Zbl 0711.90005
[13] Allen, R.; Athanassopoulos, A.; Dyson, R.G.; Thanassoulis, E., Weight restrictions and value judgement in data envelopment analysis: evolution, development and future directions, Annals of operations research, 73, 13-34, (1997) · Zbl 0890.90002
[14] Podinovski, V.V.; Athanassopoulos, A., Assessing the relative efficiency of decision making units in DEA models with weight restrictions, Journal of the operational research society, 49, 500-508, (1998) · Zbl 1131.90397
[15] Halme, M.; Joro, T.; Korhonen, P.; Salo, S.; Wallenius, J., A value efficiency approach to incorporating preference information in data envelopment analysis, Management science, 45, 103-115, (1999) · Zbl 1231.90279
[16] Jahanshahloo, G.R.; Memariani, A.; Hosseinzadeh, F.; Shoja, N., A feasible interval for weights in data envelopment analysis, Applied mathematics and computation, 160, 155-168, (2005) · Zbl 1057.90028
[17] Jahanshahloo, G.R.; Damaneh, M.S., A note on simulating weights restrictions in DEA: an improvement of thanassoulis and Allen’s method, Computers & operations research, 32, 1037-1044, (2005) · Zbl 1071.90549
[18] Kousmanen, T.; Cherchye, L.; Sipilainen, T., The law of one price in data envelopment analysis: restricting weight flexibility across firms, European journal of operational research, 170, 735-757, (2006) · Zbl 1091.90520
[19] Bernroider, E.; Stix, V., A method using weight restrictions in data envelopment analysis for ranking and validity issues in decision making, Computers & operations research, 34, 2637-2647, (2007) · Zbl 1141.90439
[20] Podinovski, V.V., Suitability and redundancy of non-homogeneous weight restrictions for measuring the relative efficiency in DEA, European journal of the operational research, 154, 380-395, (2004) · Zbl 1146.90451
[21] Bal, H.; Örkcü, H.H.; Çelebioğlu, S., A new method based on the dispersion of weights in data envelopment analysis, Computers and industrial engineering, 54, 3, 502-512, (2008)
[22] Cooper, W.W.; Seiford, L.M.; Tone, K., Data envelopment analysis, (2000), Kluwer Academic Publishers Boston, USA
[23] Banker, R.D.; Charnes, A.; Cooper, W.W., Some models for estimating technical and scale efficiencies in data envelopment analysis, Management science, 30, 1078-1092, (1984) · Zbl 0552.90055
[24] Ignizio, J.P., Goal programming and extension, (1976), Lexington Books Lexington · Zbl 1052.90584
[25] Zeleny, M., Multiple criteria decision making, (1982), McGraw-Hill New York, USA · Zbl 0588.90019
[26] Romero, C.; Rehman, T., Multiple criteria analysis for agricultural decisions, (1989), Elseiver Science Publishing Company New York, USA
[27] Handbook of critical issues in goal programming, (1991), Pergamon press Oxford · Zbl 0817.68034
[28] ⟨www.oecd.org⟩.
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