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A generalized model for weight restrictions in data envelopment analysis

Author

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  • D L Tracy

    (The University of Tennessee at Martin)

  • B Chen

    (Washington State University)

Abstract

Data envelopment analysis (DEA) is designed to maximize the efficiency of a given decision-making unit (DMU) relative to all other DMUs by the choice of a set of input and output weights. One strength of the original models is the absence of any need of a priori information about the process of transforming inputs into outputs. However, in the practical application of DEA models, this strength has also become a weakness. Incorporation of process knowledge is more a norm than an exception in practice, and typically involves placing constraints on the input and/or output weights. New DEA formulations have evolved to address this issue. However, existing formulations for weight restrictions may underestimate relative efficiency or even render a problem infeasible. A new model formulation is introduced to address this issue. This formulation represents a significant improvement over existing DEA models by providing a generalized, comprehensive treatment for weight restrictions.

Suggested Citation

  • D L Tracy & B Chen, 2005. "A generalized model for weight restrictions in data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(4), pages 390-396, April.
    • Handle: RePEc:pal:jorsoc:v:56:y:2005:i:4:d:10.1057_palgrave.jors.2601823
    DOI: 10.1057/palgrave.jors.2601823
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    References listed on IDEAS

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    Cited by:

    1. M Khalili & A S Camanho & M C A S Portela & M R Alirezaee, 2010. "An improvement on the Tracy and Chen model ‘A generalized model for weight restrictions in DEA’," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(12), pages 1789-1793, December.
    2. J-L Hu & C-Y Fang, 2010. "Do market share and efficiency matter for each other? An application of the zero-sum gains data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(4), pages 647-657, April.
    3. Ströhl, Florian & Borsch, Erik & Souren, Rainer, 2018. "Integration von Gewichtsrestriktionen in das DEA-Modell nach Charnes, Cooper und Rhodes: Exemplarische Optionen und Auswirkungen," Ilmenauer Schriften zur Betriebswirtschaftslehre, Technische Universität Ilmenau, Institut für Betriebswirtschaftslehre, volume 3, number 32018.
    4. Khalili, M. & Camanho, A.S. & Portela, M.C.A.S. & Alirezaee, M.R., 2010. "The measurement of relative efficiency using data envelopment analysis with assurance regions that link inputs and outputs," European Journal of Operational Research, Elsevier, vol. 203(3), pages 761-770, June.
    5. Rezaeiani, M.J. & Foroughi, A.A., 2018. "Ranking efficient decision making units in data envelopment analysis based on reference frontier share," European Journal of Operational Research, Elsevier, vol. 264(2), pages 665-674.
    6. Panagiotis Ravanos & Giannis Karagiannis, 2022. "On VEA, Production Trade-offs and Weight Restrictions," Discussion Paper Series 2022_04, Department of Economics, University of Macedonia, revised Jun 2022.
    7. Ahn, Heinz & Neumann, Ludmila & Vazquez Novoa, Nadia, 2012. "Measuring the relative balance of DMUs," European Journal of Operational Research, Elsevier, vol. 221(2), pages 417-423.

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