Common benchmarking and ranking of units with DEA

This paper develops a common framework for benchmarking and ranking units with DEA. In many DEA applications, decision making units (DMUs) experience similar circumstances, so benchmarking analyses in those situations should identify common best practices in their management plans. We propose a DEA-...

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Bibliographic Details
Published inOmega (Oxford) Vol. 65; pp. 1 - 9
Main Authors Ruiz, José L., Sirvent, Inmaculada
Format Journal Article
LanguageEnglish
Published Oxford Elsevier Ltd 01.12.2016
Pergamon Press Inc
Subjects
Benchmarking
Benchmarks
Best practice
Data envelopment analysis
DEA
Decision making units
Efficiency
Efficiency measurement
Ranking
Ratings & rankings
Studies
Target setting
DEA
Benchmarking
Target setting
Efficiency measurement
Ranking
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Summary:This paper develops a common framework for benchmarking and ranking units with DEA. In many DEA applications, decision making units (DMUs) experience similar circumstances, so benchmarking analyses in those situations should identify common best practices in their management plans. We propose a DEA-based approach for the benchmarking to be used when there is no need (nor wish) to allow for individual circumstances of the DMUs. This approach identifies a common best practice frontier as the facet of the DEA efficient frontier spanned by the technically efficient DMUs in a common reference group. The common reference group is selected as that which provides the closest targets. A model is developed which allows us to deal not only with the setting of targets but also with the measurement of efficiency, because we can define efficiency scores of the DMUs by using the common set of weights (CSW) it provides. Since these weights are common to all the DMUs, the resulting efficiency scores can be used to derive a ranking of units. We discuss the existence of alternative optimal solutions for the CSW and find the range of possible rankings for each DMU which would result from considering all these alternate optima. These ranking ranges allow us to gain insight into the robustness of the rankings. •A common framework for the benchmarking of decision making units by using DEA.•Setting the closest targets on a common best practice frontier.•Measuring efficiency and ranking of units based on a common set of weights.•Analysis of robustness of the rankings against the alternate optima for the weights.
ISSN:0305-0483
1873-5274
DOI:10.1016/j.omega.2015.11.007