A bi-level multi-objective data envelopment analysis model for estimating profit and operational efficiency of bank branches


Data Envelopment Analysis (DEA) is a powerful method for analyzing the performance of decision making units (DMUs). Traditionally, DEA is applied for estimating the performance of a set of DMUs through measuring a single perspective of efficiency. However, in recent years, due to increasing competition in various industries, modern enterprises focus on enhancing their performance by measuring efficiencies in different aspects, separately or simultaneously. This paper proposes a bi-level multi-objective DEA (BLMO DEA) model which is able to assess the performance of DMUs in two different hierarchical dimensions, simultaneously. In the proposed model, we define two level efficiency scores for each DMU. The aim is to maximize these two efficiencies, simultaneously, for each DMU. Since the objective functions at both levels are fractional, a fuzzy fractional goal programming (FGP) methodology is used to solve the proposed BLMO DEA model. The capability of the proposed model is illustrated by a numerical example. Finally, to practically validate the proposed model, a real case study from 45 bank’s branches is applied. The results show that the proposed model can provide a more comprehensive measure for efficiency of each bank’s branch based on simultaneous measuring of two different efficiencies, profit and operational efficiencies, and by considering the level of their importance.

Publication DOI: https://doi.org/10.1051/ro/2018108
Divisions: College of Business and Social Sciences > Aston Business School > Operations & Information Management
Additional Information: Copyright / Published by: EDP Sciences. A bi-level multi-objective data envelopment analysis model for estimating profit and operational efficiency of bank branches Hashem Omrani, Setareh Mohammadi and Ali Emrouznejad RAIRO-Oper. Res., Forthcoming article Received: 26 July 2017 / Revised: 25 October 2018 / Accepted: 25 November 2018 DOI: https://doi.org/10.1051/ro/2018108
Publication ISSN: 1290-3868
Last Modified: 25 Mar 2024 08:28
Date Deposited: 03 Dec 2018 12:45
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Related URLs: https://www.rai ... 1051/ro/2018108 (Publisher URL)
PURE Output Type: Article
Published Date: 2019-11-01
Published Online Date: 2018-11-30
Accepted Date: 2018-11-25
Authors: Omrani, Hashem
Mohammadi, Setareh
Emrouznejad, Ali (ORCID Profile 0000-0001-8094-4244)



Version: Accepted Version

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