Assessing productive efficiency of banks using integrated Fuzzy-DEA and bootstrapping:a case of Mozambican banks


Performance analysis has become a vital part of the management practices in the banking industry. There are numerous applications using DEA models to estimate efficiency in banking, and most of them assume that inputs and outputs are known with absolute precision. Here, we propose new Fuzzy-DEA α-level models to assess underlying uncertainty. Further, bootstrap truncated regressions with fixed factors are used to measure the impact of each model on the efficiency scores and to identify the most relevant contextual variables on efficiency. The proposed models have been demonstrated using an application in Mozambican banks to handle the underlying uncertainty. Findings reveal that fuzziness is predominant over randomness in interpreting the results. In addition, fuzziness can be used by decision-makers to identify missing variables to help in interpreting the results. Price of labor, price of capital, and market-share were found to be the significant factors in measuring bank efficiency. Managerial implications are addressed.

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Divisions: College of Business and Social Sciences > Aston Business School
College of Business and Social Sciences > Aston Business School > Operations & Information Management
Additional Information: © 2015, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Uncontrolled Keywords: banking efficiency,bootstrapped regression,data envelopment analysis,fuzzy-DEA,Mozambique,Management Science and Operations Research,Modelling and Simulation,Information Systems and Management
Publication ISSN: 1872-6860
Last Modified: 15 Apr 2024 07:15
Date Deposited: 16 Dec 2015 13:45
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2016-02-16
Published Online Date: 2015-10-17
Accepted Date: 2015-10-01
Authors: Wanke, Peter
Barros, C.P.
Emrouznejad, Ali (ORCID Profile 0000-0001-8094-4244)

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