Fuzzy Data Envelopment Analysis:An Adjustable Approach


Possibilistic Data Envelopment Analysis (PDEA) is one of the most applicable and popular approaches in the literature to deal with imprecise and ambiguous data in DEA models. In this approach, with respect to tendency of decision maker (DM) in taking optimistic, pessimistic and compromise attitude, three measures including possibility, necessity and credibility measures are used to form the Fuzzy DEA (FDEA) models, respectively. However, decision makers may have different preference and so it is necessary to customize fuzzy DEA models according to properties of DMUs. This paper proposes a novel fuzzy DEA model based on general fuzzy measure in which the attitude of DMUs could be determined by the optimistic-pessimistic parameters. As a result, the proposed FDEA model is general, applicable, flexible, and adjustable based on each DMUs. A numerical example is used to explain the proposed approach while usefulness and applicability of this approach have been illustrated using a real data set to measure efficiency of 38 hospital in United States.

Publication DOI: https://doi.org/10.1016/j.eswa.2019.06.039
Divisions: College of Business and Social Sciences > Aston Business School > Operations & Information Management
College of Business and Social Sciences > Aston Business School
Additional Information: © 2019, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords: Fuzzy data envelopment analysis,General fuzzy measure,Hospital efficiency,Possibility theory,Uncertainty,Engineering(all),Computer Science Applications,Artificial Intelligence
Publication ISSN: 1873-6793
Last Modified: 29 Apr 2024 07:32
Date Deposited: 20 Jun 2019 07:30
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Related URLs: https://www.sci ... 957417419304397 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2019-12-01
Published Online Date: 2019-06-19
Accepted Date: 2019-06-18
Authors: Peykani, P.
Mohammadi, E.
Emrouznejad, Ali (ORCID Profile 0000-0001-8094-4244)
Pishvaee, M.S.
Rostamy-Malkhalifeh, M.

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