Measuring the efficiency of hospitals: a fully-ranking DEA–FAHP approach

The goal of this study is to present a DEA-based fuzzy multi-criteria decision making model for firms in the health care industry in order to enhance their business performance. The study demonstrates a real-life use of the proposed model, mainly designed for hospitals. Data envelopment analysis enh...

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Bibliographic Details
Published in:Annals of operations research Vol. 278; no. 1-2; pp. 361 - 378
Main Authors: Rouyendegh, Babak Daneshvar, Oztekin, Asil, Ekong, Joseph, Dag, Ali
Format: Journal Article
Language:English
Published: New York Springer US 01.07.2019
Springer
Springer Nature B.V
Subjects:
Administration
Analysis
Analytic hierarchy process
Analytical hierarchy process
Business and Management
Business performance management
Combinatorics
Data envelopment analysis
DEA in Data Analytics
Decision making
Decision making models
Hospitals
Methods
Multiple criteria decision making
Multiple criterion
Operations research
Operations Research/Decision Theory
Theory of Computation
United States
Turkey
Fuzzy logic
Data envelopment analysis (DEA)
Analytic hierarchy process (AHP)
Multi-criteria decision making
Healthcare analytics
ISSN:0254-5330, 1572-9338
Online Access:Get full text
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Summary:The goal of this study is to present a DEA-based fuzzy multi-criteria decision making model for firms in the health care industry in order to enhance their business performance. The study demonstrates a real-life use of the proposed model, mainly designed for hospitals. Data envelopment analysis enhanced with fuzzy analytic hierarchy process are collectively utilized to quantify the data and structure the model in decision-making. The juxtaposition of the two methods is used to compile a ranked list of multiple proxies containing diverse input and output variables which occur in two stages. This hybrid model provides several benefits, one of which is the ability to make the most appropriate decision considering the value of the weights determined by the data from the hybrid model.
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ISSN:0254-5330
1572-9338
DOI:10.1007/s10479-016-2330-1