Multi-expert performance evaluation of healthcare institutions using an integrated intuitionistic fuzzy AHP&DEA methodology

İrem Otay*, Basar Oztaysi, Sezi Cevik Onar, Cengiz Kahraman

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

148 Citations (Scopus)

Abstract

Healthcare management and healthcare industry have been one of the popular and complex topics that many researchers and professionals have focused on. This paper proposes a new multi-expert fuzzy approach integrating intuitionistic fuzzy Data Envelopment Analysis (DEA) and intuitionistic fuzzy Analytic Hierarchy Process (IF-AHP) for solving the performance evaluation problem of healthcare institutions. In this paper, intuitionistic fuzzy sets (IFS) have been preferred since they simultaneously provide information on the membership, non-membership, and hesitancy functions. A real life problem is demonstrated to validate the proposed methodology. A total number of 16 hospitals operating in Istanbul have been analyzed based on a broad set of inputs and outputs. Then, a comparison with crisp DEA has been performed.

Original languageEnglish
Pages (from-to)90-106
Number of pages17
JournalKnowledge-Based Systems
Volume133
DOIs
Publication statusPublished - 1 Oct 2017

Bibliographical note

Publisher Copyright:
© 2017 Elsevier B.V.

Keywords

  • Analytic Hierarchy Process (AHP)
  • Data Envelopment Analysis (DEA)
  • Fuzzy
  • Healthcare
  • Triangular Intuitionistic Fuzzy Set (TIFS)

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