Review of ranking methods in the data envelopment analysis context

Nicole Adler*, Lea Friedman, Zilla Sinuany-Stern

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

673 Scopus citations


Within data envelopment analysis (DEA) 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. The ranking methods have been divided in this paper into six, somewhat overlapping, areas. The first area involves the evaluation of a cross-efficiency matrix, in which the units are self and peer evaluated. The second idea, generally known as the super-efficiency method, ranks through the exclusion of the unit being scored from the dual linear program and an analysis of the change in the Pareto Frontier. The third grouping is based on benchmarking, in which a unit is highly ranked if it is chosen as a useful target for many other units. The fourth group utilizes multivariate statistical techniques, which are generally applied after the DEA dichotomic classification. The fifth research area ranks inefficient units through proportional measures of inefficiency. The last approach requires the collection of additional, preferential information from relevant decision-makers and combines multiple-criteria decision methodologies with the DEA approach. However, whilst each technique is useful in a specialist area, no one methodology can be prescribed here as the complete solution to the question of ranking.

Original languageAmerican English
Pages (from-to)249-265
Number of pages17
JournalEuropean Journal of Operational Research
Issue number2
StatePublished - 16 Jul 2002


  • Benchmarking
  • Cross-efficiency
  • Data envelopment analysis
  • MCDM
  • Multivariate statistics
  • Ranking techniques
  • Super-efficiency


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