Abstract
We present a review of methods for increasing discrimination between efficient DMUs in Data Envelopment Analysis. These methods were classified into two groups: those that incorporate a priori information and those that do not use or minimize the use of such a priori information. We also compare these methodologies regarding their specific characteristics.
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Angulo-Meza, L., Lins, M.P.E. Review of Methods for Increasing Discrimination in Data Envelopment Analysis. Annals of Operations Research 116, 225–242 (2002). https://doi.org/10.1023/A:1021340616758
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DOI: https://doi.org/10.1023/A:1021340616758