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Ranking Decision Making Units: The Cross-Efficiency Evaluation

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Handbook of Operations Analytics Using Data Envelopment Analysis

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 239))

Abstract

This chapter surveys the literature on the cross-efficiency evaluation, which is a methodology for ranking decision making units (DMUs) involved in a production process regarding their efficiency. Cross-efficiency evaluation has been developed in the context of analyses of relative efficiency carried out with Data Envelopment Analysis (DEA). It is usually claimed that the DEA efficiency scores cannot be used for ranking, because they result from a self-evaluation of units based on DMU-specific input and output weights. Cross-efficiency evaluation, in contrast, provides a peer-appraisal in which each DMU is evaluated from the perspective of all of the others by using their DEA weights. This makes it possible to derive an ordering. We make an exhaustive review of the existing work on the different issues related to the cross-efficiency evaluation. Other uses of this methodology different from the ranking of DMUs as well as the extensions that have been developed are also outlined.

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Authors and Affiliations

  1. Centro de Investigación Operativa, Universidad Miguel Hernández, Avd. de la Universidad, s/n, Elche (Alicante), 03202, Spain

    José L. Ruiz & Inmaculada Sirvent

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  1. José L. Ruiz
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  2. Inmaculada Sirvent
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Correspondence to José L. Ruiz .

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Editors and Affiliations

  1. Dept of Business Administration, Ming Chuan University, Taipei, Taiwan

    Shiuh-Nan Hwang

  2. College of Maritime Science & Mgmt, National Taiwan Ocean University, Keelung, Taiwan

    Hsuan-Shih Lee

  3. School of Business, Worcester Polytechnic Institute, Worcester, Massachusetts, USA

    Joe Zhu

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Ruiz, J.L., Sirvent, I. (2016). Ranking Decision Making Units: The Cross-Efficiency Evaluation. In: Hwang, SN., Lee, HS., Zhu, J. (eds) Handbook of Operations Analytics Using Data Envelopment Analysis. International Series in Operations Research & Management Science, vol 239. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7705-2_1

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