Predicting Efficiency in Islamic Banks: An Integrated Multicriteria Decision Making (MCDM) Approach
Journal of International Financial Markets, Institutions & Money (2016)
32 Pages Posted: 1 Nov 2018
Date Written: October 9, 2018
This paper presents an efficiency assessment of 114 Islamic banks from 24 countries using the “Technique for Order Preference by Similarity to the Ideal Solution” (TOPSIS). TOPSIS is a multicriteria decision making technique similar to Data Envelopment Analysis (DEA), which ranks a finite set of units based on the minimization of distance from an ideal point and the maximization of distance from an anti-ideal point. In this research, TOPSIS is used first in a two-stage approach to assess the relative efficiency of Islamic banks using the most frequent indicators adopted by the literature. Then, in the second stage, neural networks are combined with TOPSIS results as part of an attempt to produce a model for banking performance with effective predictive ability. The results reveal that variables related to both country origin and cost structure have a prominent impact on efficiency. Findings also indicate that the Islamic banking market would benefit from a higher level of competition between institutions.
Keywords: Islamic banks, TOPSIS, two-stage, neural networks, efficiency
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