Volume 52, Number 1, January–March 2018
Fuzzy Data Envelopment Analysis: Recent Developments and Applications
|Page(s)||285 - 303|
|Published online||30 May 2018|
A comparison between stochastic DEA and fuzzy DEA approaches: revisiting efficiency in Angolan banks
Center for Studies in Logistics, Infrastructure and Management, COPPEAD Graduate Business School, Federal University of Rio de Janeiro, Rua Paschoal Lemme,
Rio de Janeiro, Brazil
2 ISEG – Lisbon School of Economics and Management, ULisboa and CEsA – Research Centre on African, Asian and Latin American Studies, Rua Miguel Lupi, 20. 1249-078 Lisboa, Portugal
3 Aston Business School, Aston University, Birmingham, B4 7ET, UK
* Corresponding author: email@example.com
Accepted: 21 September 2016
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 compare Stochastic-DEA and Fuzzy-DEA models to assess, respectively, how the underlying randomness and fuzziness impact efficiency levels. The proposed models have been demonstrated using an application in Angolan banks. Findings reveal that conclusions with respect to the ranking of DMUs may vary substantially depending upon the type of the model chosen, although efficiency scores are similar to some extent when compared within the ambits of Stochastic-DEA and Fuzzy-DEA models. Additionally, modeling choices on fuzziness, rather than on randomness, appears to be the most critical source for variations in efficiency rankings. Managerial implications for Angolan banks are also explored.
Mathematics Subject Classification: 90C05 / 62F40 / 62U20 / 03B52
Key words: Data envelopment analysis / Angola Fuzzy-DEA / Stochastic-DEA / KL-Divergence
© EDP Sciences, ROADEF, SMAI 2018
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