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

Peter Wanke*, C.P. Barros, Ali Emrouznejad

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish
Pages (from-to)378-389
Number of pages12
JournalEuropean Journal of Operational Research
Volume249
Issue number1
Early online date17 Oct 2015
DOIs
Publication statusPublished - 16 Feb 2016

Bibliographical note

© 2015, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

Keywords

  • banking efficiency
  • bootstrapped regression
  • data envelopment analysis
  • fuzzy-DEA
  • Mozambique

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