Analytical insights into firm performance: a fuzzy clustering approach for data envelopment analysis classification
by Amir Karbassi Yazdi; Yong J. Wang; Abotorab Alirezaei
International Journal of Operational Research (IJOR), Vol. 33, No. 3, 2018

Abstract: Many companies use data envelopment analysis (DEA) as a method for measuring performance and benchmarking with other organisations. The aim of this study is to describe a new approach for data envelopment analysis (DEA) classification based on fuzzy clustering. The new method is used for clustering decision-making units (DMUs) and ranks them from the least priority cluster to highest priority cluster. Thus, inefficient clusters can be identified as compared to efficient clusters. This study evaluates 25 insurance companies based on output oriented CCR methods, and the result shows that ten companies belong to the efficient cluster. Thus, decision makers in the inefficient cluster can benchmark with their efficient counterparts to achieve better performance.

Online publication date: Tue, 16-Oct-2018

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Operational Research (IJOR):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com