Ranking methods within data envelopment analysis

Nicole Adler*, Nicola Volta

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

4 Scopus citations

Abstract

Within the field of data envelopment analysis is a sub-group of papers in which many researchers have sought to improve the differential capabilities of DEA and to fully rank both efficient, as well as inefficient, decision-making units. We have divided the ranking concepts into seven general areas based on the following concepts: Super-efficiency, benchmarking, cross-efficiency, common set of weights, multivariate statistics, multi-criteria decision-making and inefficiency dominance. After describing the approaches, we compare and contrast them using an illustration drawn from a set of universities. It is apparent that the approaches succeed in strengthening the results of the non-parametric data envelopment analysis models and frequently enable an almost complete ranking of decision-making units. However, the results may diverge substantially between the different models, suggesting that the choice of framework must be context dependent and chosen with great care.

Original languageAmerican English
Title of host publicationThe Palgrave Handbook of Economic Performance Analysis
PublisherPalgrave Macmillan
Pages189-224
Number of pages36
ISBN (Electronic)9783030237271
ISBN (Print)9783030237264
DOIs
StatePublished - 1 Jan 2019

Bibliographical note

Publisher Copyright:
© The Editor(s) (if applicable) and The Author(s) 2019.

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