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Models for Identifying Target Units in Data Envelopment Analysis: Comparison and Extension

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  • T. Joro

Abstract

In addition to the efficiency scores, Data Envelopment Analysis also provides the inefficient DMUs with information on reference units which lie on the efficient frontier. Reference units are traditionally found by projecting the inefficient DMUs radially to the efficient surface. However, there may exist some other efficient solutions, which are better targets. This means that it is possible to find an input-output mix that is more suitable for example from a managerial point of view. The purpose of this paper is to compare and contrast existing models for searching the most preferred reference units as targets for inefficient units, and based on that to present a dynamic and interactive way to provide these targets in Data Envelopment Analysis based on Multiple Objective Linear Programming.

Suggested Citation

  • T. Joro, 1998. "Models for Identifying Target Units in Data Envelopment Analysis: Comparison and Extension," Working Papers ir98055, International Institute for Applied Systems Analysis.
  • Handle: RePEc:wop:iasawp:ir98055
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    References listed on IDEAS

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    1. Tarja Joro & Pekka Korhonen & Jyrki Wallenius, 1998. "Structural Comparison of Data Envelopment Analysis and Multiple Objective Linear Programming," Management Science, INFORMS, vol. 44(7), pages 962-970, July.
    2. P. Korhonen, 1997. "Searching the Efficient Frontier in Data Envelopment Analysis," Working Papers ir97079, International Institute for Applied Systems Analysis.
    3. Thanassoulis, E. & Dyson, R. G., 1992. "Estimating preferred target input-output levels using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 56(1), pages 80-97, January.
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    5. Pekka Korhonen & Jyrki Wallenius, 1988. "A pareto race," Naval Research Logistics (NRL), John Wiley & Sons, vol. 35(6), pages 615-623, December.
    6. P. Korhonen, 1998. "Multiple Objective Programming Support," Working Papers ir98010, International Institute for Applied Systems Analysis.
    7. M. Halme & T. Joro & P. Korhonen & S. Salo & J. Wallenius, 1998. "Value Efficiency Analysis for Incorporating Preference Information in Data Envelopment Analysis," Working Papers ir98054, International Institute for Applied Systems Analysis.
    8. Charnes, A. & Cooper, W. W. & Golany, B. & Seiford, L. & Stutz, J., 1985. "Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 91-107.
    9. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    10. Korhonen, Pekka J. & Laakso, Jukka, 1986. "A visual interactive method for solving the multiple criteria problem," European Journal of Operational Research, Elsevier, vol. 24(2), pages 277-287, February.
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    Cited by:

    1. Y-W Chen & M Larbani & Y-P Chang, 2009. "Multiobjective data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(11), pages 1556-1566, November.
    2. M P Estellita Lins & L Angulo-Meza & A C Moreira Da Silva, 2004. "A multi-objective approach to determine alternative targets in data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(10), pages 1090-1101, October.

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