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Optimal weights in DEA models with weight restrictions

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journal contribution
posted on 2016-05-16, 09:45 authored by Victor PodinovskiVictor Podinovski
According to a conventional interpretation of a multiplier DEA model, its optimal weights show the decision making unit under the assessment, denoted DMUo, in the best light in comparison to all observed DMUs. For multiplier models with additional weight restrictions such an interpretation is known to be generally incorrect (specifically, if weight restrictions are linked or nonhomogeneous), and the meaning of optimal weights in such models has remained unclear. In this paper we prove that, for any weight restrictions, the optimal weights of the multiplier model show DMUo in the best light in comparison to the entire technology expanded by the weight restrictions. This result is consistent with the fact that the dual envelopment DEA model benchmarks DMUo against all DMUs in the technology, and not only against the observed DMUs. Our development overcomes previous concerns about the use of weight restrictions of certain types in DEA models and provides their rigorous and meaningful interpretation.

History

School

  • Business and Economics

Department

  • Business

Published in

European Journal of Operational Research

Citation

PODINOVSKI, V.V., 2016. Optimal weights in DEA models with weight restrictions. European Journal of Operational Research, 254 (3), pp. 916-924.

Publisher

© Elsevier

Version

  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

2016-04-18

Publication date

2016

Notes

This paper was accepted for publication in the journal European Journal of Operational Research and the definitive published version is available at http://dx.doi.org/10.1016/j.ejor.2016.04.035

ISSN

1872-6860

Language

  • en