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Efficiency measures and computational approaches for data envelopment analysis models with ratio inputs and outputs

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journal contribution
posted on 2017-03-16, 09:40 authored by Ole Bent Olesen, Niels Christian Petersen, Victor PodinovskiVictor Podinovski
In a recent paper to this journal, the authors developed a methodology that allows the incorporation of ratio inputs and outputs in the variable and constant returns-to-scale DEA models. Practical evaluation of efficiency of decision making units (DMUs) in such models generally goes beyond the application of standard linear programming techniques. In this paper we discuss how the DEA models with ratio measures can be solved. We also introduce a new type of potential ratio (PR) inefficiency. It characterizes DMUs that are strongly efficient in the model of technology with ratio measures but become inefficient if the volume data used to calculate ratio measures become available. Potential ratio inefficiency can be tested by the programming approaches developed in this paper.

History

School

  • Business and Economics

Department

  • Business

Published in

European Journal of Operational Research

Volume

261

Issue

2

Citation

OLESEN, O.B., PETERSEN, N.C. and PODINOVSKI, V.V., 2017. Efficiency measures and computational approaches for data envelopment analysis models with ratio inputs and outputs. European Journal of Operational Research, 261 (2), pp. 640-655.

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

2017-02-16

Publication date

2017-02-24

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.2017.02.021

ISSN

1872-6860

Language

  • en

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