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The State of the Art in Fuzzy Data Envelopment Analysis

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Performance Measurement with Fuzzy Data Envelopment Analysis

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 309))

Abstract

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. Crisp input and output data are fundamentally indispensable in conventional DEA. However, the observed values of the input and output data in real-world problems are sometimes imprecise or vague. Many researchers have proposed various fuzzy methods for dealing with the imprecise and ambiguous data in DEA. This chapter provides a taxonomy and review of the fuzzy DEA (FDEA) methods. We present a classification scheme with six categories, namely, the tolerance approach, the α-level based approach, the fuzzy ranking approach, the possibility approach, the fuzzy arithmetic, and the fuzzy random/type-2 fuzzy set. We discuss each classification scheme and group the FDEA papers published in the literature over the past 30 years.

An earlier version of this chapter was published as Hatami-Marbini et al. [1].

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Authors and Affiliations

  1. Aston Business School, Aston University, Birmingham, UK

    Ali Emrouznejad

  2. Lindback Distinguished Chair of Information Systems and Decision Sciences, Business Systems and Analytics Department, La Salle University, Philadelphia, PA, 19141, USA

    Madjid Tavana

  3. Business Information Systems Department, Faculty of Business Administration and Economics, University of Paderborn, 33098, Paderborn, Germany

    Madjid Tavana

  4. Louvain School of Management, Center of Operations Research and Econometrics (CORE), Université catholique de Louvain, L1.03.01, 1348, Louvain-la-Neuve, Belgium

    Adel Hatami-Marbini

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  1. Ali Emrouznejad
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  2. Madjid Tavana
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  3. Adel Hatami-Marbini
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  1. Operations and Information Management Group, Aston Business School, Aston University, Birmingham, United Kingdom

    Ali Emrouznejad

  2. Business Systems and Analytics Department, La Salle University, Philadelphia, Pennsylvania, USA

    Madjid Tavana

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Emrouznejad, A., Tavana, M., Hatami-Marbini, A. (2014). The State of the Art in Fuzzy Data Envelopment Analysis. In: Emrouznejad, A., Tavana, M. (eds) Performance Measurement with Fuzzy Data Envelopment Analysis. Studies in Fuzziness and Soft Computing, vol 309. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41372-8_1

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