Hierarchical fuzzy DEA model with double frontiers combined with TOPSIS technique: application on mobile money agents locations

Jacob Muvingi (), Arshad Ahmud Iqbal Peer (), Josef Jablonský (), Hossein Azizi () and Farhad Hosseinzadeh Lotfi ()
Additional contact information
Jacob Muvingi: Harare Institute of Technology
Arshad Ahmud Iqbal Peer: University of Technology, Mauritius
Josef Jablonský: Prague University of Economics and Business
Hossein Azizi: Islamic Azad University
Farhad Hosseinzadeh Lotfi: Islamic Azad University

OPSEARCH, 2024, vol. 61, issue 3, No 7, 1154-1191

Abstract: Abstract Hierarchical data envelopment analysis (DEA) models evaluate the efficiency of decision-making units (DMUs) with a hierarchical group structure, where sub-DMUs are grouped into main DMUs. Contrary to early hierarchical DEA models, which were based on crisp input and output data, the model adopted in this study considers fuzziness attributes in the input and output data. The efficiency analysis was mainly based on the optimistic frontier in the early conventional fuzzy DEA models. To get a full view of the efficiency of the DMUs, we incorporated a second frontier based on the pessimistic assumption. In this study, two levels of analysis were implemented for the sub-DMUs and main DMUs. A combination of the optimistic and pessimistic efficiency ratings for both levels of analysis was done to get the overall performance measures. We applied the proposed approach to analyse the mobile money agents’ locations. Aggregating sub-DMUs with ratings of the main DMUs improved the segregation of sub-DMUs in different groups. However, within groups, most sub-DMUs had similar ratings, making it difficult to distinguish the performance of the DMUs. To further improve the segregation of the DMUs, we applied the technique for order preference by similarity to the ideal solution (TOPSIS) based on the overall performance measures. The performance of 75% of the sub-DMUs was completely segregated, whilst 100% was achieved for the main DMUs. The final TOPSIS results were validated using the principal component analysis (PCA). A Spearman correlation of 50% was observed between the TOPSIS and the PCA results. The accuracy of the district location TOPSIS rankings on the final suburb location TOPSIS rankings was 72%.

Keywords: Hierarchical models; Data envelopment analysis; Double frontiers; TOPSIS (search for similar items in EconPapers)
JEL-codes: C44 C61 C67 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s12597-023-00734-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:opsear:v:61:y:2024:i:3:d:10.1007_s12597-023-00734-0

Ordering information: This journal article can be ordered from
http://www.springer. ... search/journal/12597

DOI: 10.1007/s12597-023-00734-0

Access Statistics for this article

OPSEARCH is currently edited by Birendra Mandal

More articles in OPSEARCH from Springer, Operational Research Society of India
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().