Predicting efficiency in Malaysian Islamic banks: A two-stage TOPSIS and neural networks approach

被引:59
作者
Wanke, Peter [1 ]
Azad, Abul Kalam [2 ]
Barros, C. P. [3 ]
机构
[1] Univ Fed Rio de Janeiro, COPPEAD Grad Business Sch, Rua Paschoal Lemme 355, BR-21949900 Rio De Janeiro, Brazil
[2] Univ Malaya, Fac Econ & Adm, Dept Appl Stat, Kuala Lumpur 50603, Malaysia
[3] Univ Lisbon, Dept Econ, Rua Miguel Lupi 20, P-1248079 Lisbon, Portugal
关键词
Islamic banking; Malaysia; TOPSIS; Two-stage; Neural networks; Efficiency ranks; DISTRESS; RETURN;
D O I
10.1016/j.ribaf.2015.10.002
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
This paper presents an efficiency assessment of the Malaysian Islamic banks using TOPSIS. In this research, this technique is applied first in a two-stage approach to assess the relative efficiency of Malaysian Islamic banks using the most frequent indicators found in the banking literature. Besides, 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 cost structure have a prominent negative impact on efficiency levels, although some parsimony in equity leveraging derived from Islamic finance principles maybe helpful in achieving higher efficiency levels. Findings also indicate that the Malaysian Islamic banking market also imposes cultural and regulatory barriers to foreign banks, so that their efficiency levels are lower when compared to their national counterparts. Learning curves (trend impact) are relevant in predicting efficiency levels. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:485 / 498
页数:14
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