Conventional versus Islamic bank efficiency: A dynamic network data-envelopment-analysis approach

Abstract

This study compares the efficiency of conventional and Islamic banks in Malaysia by engaging in a dynamic three-step (production, intermediation, and profitability) network data envelopment analysis (DEA). The inputs and outputs for the DEA model are selected based on the CAMELS rating. The major contributions of this study are threefold. First, this study investigates the efficiency of Malaysian banks using a novel dynamic network DEA model. Second, the Malaysian banking industry is found to be efficient in creating earning assets rather than in creating loans or profit. The results reveal that only a few banks in Malaysia have been efficient in converting deposits and equities into profit. Third, Islamic banks, in general, have been performing efficiently in the production and profitability approaches. Conventional banks, in contrast, are found to have been efficient in the intermediation approach. Policy implications are derived from the main conclusions.

Landscape of Research on the Efficiency Profiles of Islamic Banks using DEA: Survey, Classification and Critical Analysis of the Literature

“…The mixed efficiency findings with respect to different types of efficiencies (i.e., OTE, PTE, SE, CE, PE, RE and AE) fall into several categories depending on the feature or characteristic under consideration (i.e., bank type: Islamic vs Conventional; and ownership type: foreign vs domestic) and could be summarised as follows: (a) Islamic banks are more efficient than Conventional banks; (b) Islamic banks are less efficient than Conventional banks; (c) there is no significant difference in efficiency between Islamic banks and their Conventional counterparts; (d) domestic Islamic banks are more efficient than foreign Islamic banks; and (e) domestic Islamic banks are less efficient than foreign Islamic banks. As an illustration of these conflicting results, Ahmad and Luo (2010), Shawtari et al (2015), Yilmaz and Güneş (2015), Batir et al (2017), Erfani and Vasigh (2018), Prima Sakti and Mohamad (2018), Musa et al (2020) and Azad et al (2021) revealed that Islamic banks are more overall technically efficient than Conventional banks, whilst Mokhtar et al (2007Mokhtar et al ( , 2008, Ahmad and Abdul Rahman (2012), Mobarek and Kalonov (2014), Abbas et al (2016), Majeed and Zanib (2016), Abdul-Wahab and Haron (2017), Doumpos et al (2017), Shah and Masood (2017), Kaffash et al (2018), Khan et al (2018), Haque et al (2020), Alsharif (2021) and Azad et al (2021) came to the opposite conclusion. Other studies found a non-significant association (Grigorian andManole, 2005, Shahid et al, 2010;Yahya et al, 2012;Asmild et al, 2019;Shahwan and Habib, 2021).…”

“…The different groups of banks that have been compared were chosen based on (1) the type of bank; i.e., Islamic vs. Conventional banks (e.g., Grigorian and Manole, 2005;Kaffash et al, 2018;Wanke et al, 2019;Azad et al, 2021), (2) the type of operating structure (modus operandi) of the bank; i.e., fully-fledged Islamic banks vs. Islamic windows (e.g., Mokhtar et al, 2007;Salami and Adeyemi, 2015), where Islamic windows refer to Conventional banks offering Islamic banking products and services, and (3) the geographic location or countries they operate in, which could be divided into four main categories: (a) the first category consists of single country-focused studies (e.g., Mokhtar et al, 2007;Yilmaz and Güneş, 2015;Abdul-Wahab and Haron, 2017), (b) the second category consists of multi-country focused studies (e.g., Grigorian and Manole, 2005;Noor and Ahmad, 2012a;Wanke et al, 2019), (c) the third category consists of regional focused studies (e.g., Al-Muharrami, 2008;Alqahtani et al, 2017;Zeineb and Mensi, 2018), and (d) the fourth and last category consists of multi-region focused studies comparing the efficiency scores of Islamic banks in different regions (e.g., Yudistira, 2004;.…”

“…As to the heterogeneity of Islamic banks due to their characteristics or features, metafrontier analyses are most appropriate for addressing this type of heterogeneity; however, only one study by Johnes et al (2014) As to the type of DEA models, static black-box models (i.e., CCR, BCC) were predominantly used. In their study, Azad et al (2021) opened the black-box by using a static network SBM model to compute the efficiency scores of Malaysian Islamic and Conventional banks, whereas Wanke et al (2019) took account of both the internal structure of banks and the time dynamics by using a dynamic-network SBM model to estimate the efficiency scores of banks. To the best of our knowledge, no efficiency study of Islamic banks used an actual dynamic black-box model to estimate the efficiency scores of banks except for Shawtari et al (2015Shawtari et al ( , 2018 who used black-box window analysis to unveil time dynamics of efficiency.…”

“…The general banking literature classifies the efficiency evaluation perspectives or approaches into six https://doi.org/10.55802/IJB.028(3).004 categories; namely, the intermediation approach or IA for short (e.g., Ferrier and Lovell, 1990;Favero and Papi, 1995;Berger and Humphrey, 1997;Berger and Mester, 2003;Drake et al, 2006), the asset approach or AA for short (e.g., Favero and Papi, 1995), the production approach or PA for short (e.g., Ferrier and Lovell, 1990;Berger and Humphrey, 1997), the profit-oriented approach or POA for short (e.g., Berger and Mester, 2003), the value-added approach or VAA for short (e.g., Pastor et al, 1997), and the usercost approach or UCA for short (e.g., Hancock, 1985). However, to the best of our knowledge, in the Islamic banking literature only four types of approaches were adopted; namely, IA (e.g., Yudistira, 2004;Hassan, 2006;Johnes et al, 2014;Kaffash et al, 2018), PA (e.g., Mostafa, 2011;Musa et al, 2020), AA (Shah and Masood, 2017), and a hybrid approach (HA) consisting of a combination of PA, IA and POA modelled as divisions of a network (Azad et al, 2021). We refer the reader to Table 2 for a summary description of each approach including its conceptual model and typical inputs and outputs used by researchers for their implementations of the conceptual models.…”

A New Resource Allocation Multiple Criteria Decision-Making Method in a Two-Stage Inverse Data Envelopment Analysis Framework for the Sustainable Development of Chinese Commercial Banks

“…However, most of the research has the following limitations: First, the internal structure of decision-making units (DMUs) is often overlooked; second, undesirable outputs often cannot be considered. Wang et al (2014) claimed that the Chinese commercial banking system has a two-stage internal structure [21]; Azad et al (2021) [22], Tan et al (2021) [23], and Yang et al (2023) [24] all emphasized that it is necessary to consider the internal system structure of banks when evaluating their efficiency; otherwise, the accuracy of commercial bank efficiency evaluation would be affected. Safiullah and Shamsuddin (2022) [25], Shah et al (2022) [26], and Wanke et al (2023) [27] all claimed that nonperforming loans should be considered undesirable outputs in the efficiency evaluation of commercial banking because they represent the risks of commercial banking and hinder its sustainable development.…”