Fuzzy clustering of homogeneous decision making units with common weights in data envelopment analysis
Document Type
Journal Article
Publication Title
Journal of Intelligent & Fuzzy Systems
Volume
40
Issue
1
First Page
813
Last Page
832
Publisher
IOS Press
School
School of Business and Law
RAS ID
32490
Abstract
© 2021 - IOS Press. All rights reserved. Data Envelopment Analysis (DEA) is the most popular mathematical approach to assess efficiency of decision-making units (DMUs). In complex organizations, DMUs face a heterogeneous condition regarding environmental factors which affect their efficiencies. When there are a large number of objects, non-homogeneity of DMUs significantly influences their efficiency scores that leads to unfair ranking of DMUs. The aim of this study is to deal with non-homogeneous DMUs by implementing a clustering technique for further efficiency analysis. This paper proposes a common set of weights (CSW) model with ideal point method to develop an identical weight vector for all DMUs. This study proposes a framework to measuring efficiency of complex organizations, such as banks, that have several operational styles or various objectives. The proposed framework helps managers and decision makers (1) to identify environmental components influencing the efficiency of DMUs, (2) to use a fuzzy equivalence relation approach proposed here to cluster the DMUs to homogenized groups, (3) to produce a common set of weights (CSWs) for all DMUs with the model developed here that considers fuzzy data within each cluster, and finally (4) to calculate the efficiency score and overall ranking of DMUs within each cluster.
DOI
10.3233/JIFS-200962
Access Rights
subscription content
Comments
Kazemi, S., Mavi, R. K., Emrouznejad, A., & Kiani Mavi, N. (2021). Fuzzy clustering of homogeneous decision making units with common weights in data envelopment analysis. Journal of Intelligent & Fuzzy Systems, 40(1), 813-832. https://doi.org/10.3233/JIFS-200962