Efficiency measures in DEA with grey interval data under the hypotheses of data consistency

Abstract

Purpose

The purpose of this paper is to solve the DEA model with grey interval data while the inputs/outputs have large interval length.

Design/methodology/approach

Some methods have been developed to calculate the interval efficiencies of the decision‐making unit (DMU) in DEA model with interval data, in which there are two shortcomings. One is that the evaluated DMU and referenced DMUs are not be dealt with fairly, as they are not counterparts in locations of inputs and outputs within possible ranges. Another is that efficiency intervals may be too wide to provide valuable information. This paper proposes the hypotheses of data consistency in DEA model. Under the hypotheses, linear programming (LP) models to solve the upper and lower bounds of interval efficiencies are established.

Findings

It is found that lengths of efficiency intervals under the hypotheses are shorter, which produces more reliable and informative evaluation results and DMUs are dealt with more fairly.

Practical implications

The method proposed in the paper could be used in efficiencies evaluation of enterprises, governments, etc. when the classic methods are invalid for the high uncertainty evaluation results.

Originality/value

The paper succeeds in proposing the hypotheses of data consistency and solving the DEA model with interval grey data under that.

Citation

Wang, J. and Liu, S. (2012), "Efficiency measures in DEA with grey interval data under the hypotheses of data consistency", Grey Systems: Theory and Application, Vol. 2 No. 1, pp. 63-69. https://doi.org/10.1108/20439371211197686