Integrated approach for computing aggregation weights in cross-efficiency evaluation

Abstract

Cross-efficiency evaluation is an extension of data envelopment analysis that has been widely used in many different applications aimed at producing a ranking of the set of decision making units. Besides the traditional self-appraisal of units, cross-evaluation methods also take into account peer-appraisals, which are then summarized into an overall performance measure. The standard approach for this aggregation process relies on an equally-weighted average that disregards that some cross-efficiency scores might be considered more relevant or reliable than others. This paper focuses on the aggregation process of cross-efficiency scores and proposes a new approach for deriving meaningful aggregation weights for a more comprehensive evaluation of the units. Our method integrates two complementary perspectives that weights should reflect: the discriminatory ability of the information contained in the cross-efficiency matrix and the relative importance that can be attributed to each of the peer-appraisals. In this sense, the approach presented here provides a more accurate evaluation of the units than previous approaches and therefore it is likely to produce more meaningful rankings. Some numerical examples are provided that validate the approach proposed and examine the results obtained in comparison with previous known methods.