Investigating Critical Resemblances of Islamic Banking with Conventional: Binary Matrices as Solution Methodology

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1. Journal of Business and Social Review in Emerging Economies Vol . 6, No 1, March 2020 Volume and Issues Obtainable at Center for Sustainability Research and Consultancy Journal of Business and Social Review in Emerging Economies ISSN: 2519-089X (E): 2519-0326 Volume 6: No. 1, March 2020 Journal homepage: www.publishing.globalcsrc.org/jbsee Investigating Critical Resemblances of Islamic Banking with Conventional: Binary Matrices as Solution Methodology 1 Abdul Aziz Khan Niazi, 2 Tehmina Fiaz Qazi, 3 Abdul Basit 1 Institute of Business and Management, University of Engineering and Technology, Lahore, Pakistan azizniazi@uet.edu.pk 2 Institute of Business and Management, University of Engineering and Technology, Lahore, Pakistan tehmina.qazi@gmail.com 3 Lahore Institute of Science and Technology, Lahore, Pakistan. abasit_shahbaz@yahoo.com ARTICLE DETAILS History Revised format: February 2020 Available Online: March 2020 Keywords Resemblance, Islamic banking, Conventional, ISM, MICMAC JEL Classification: G29 ABSTRACT Identifying, ranking, exhuming and classifying the relations among the critical resemblances between Islamic and conventional banking is aim of this study. It also discusses the structure of these resemblances and devises valuable guidelines for discerners. It follows qualitative paradigm of research philosophy and overall design consists of review of literature, data collection and analysis. Literature review is used to prepare a list of resemblances, Interpretive Structural Modelling (ISM) is employed for ranking, exhuming and modeling the relationships among resemblances, whereas, cross impact matrix multiplication applied to classification (MICMAC) for substantiating the results of ISM by classifying factors into independent, dependent, linkage and autonomous clusters. Through the discourse of literature review a list of eighteen critical resemblances has been prepared. Results of ISM show that resemblance in rating system and resemblance in public perception occupy highest rank therefore are least critical, whereas, resemblance in settlement of cost of funds and similar employee qualification occupy bottom of the model therefore are the most critical. MICMAC analysis validates the results of ISM. This study is helpful to discerners who want to understand differences and similarities between two paradigms of banking. It is equally useful for regulators, management, employees, customers, researchers, religious scholars and society at large being an original attempt by the authors substantiated by real time survey data collected from experts on the issue. © 2020 The authors, under a Creative Commons AttributionNonCommercial 4.0 Corresponding author’s email address: azizniazi@uet.edu.pk Recommended citation: Niazi, A.A.K., Qazi, T.F., Basit. A. (2020). Investigating Critical Resemblances of Islamic Banking with Conventional: Binary Matrices as Solution Methodology. Journal of Business and Social Review in Emerging Economies, 6(1), 351-366 DOI: 10.26710/jafee.v6i1.1045 351
2. Journal of Business and Social Review in Emerging Economies Vol . 6, No 1, March 2020 1. Introduction Much effort of theorists and researchers has been devoted to refine differences and resemblances between Islamic and conventional banking. It is a hot topic in the area of banking particularly when both co-exist in many countries. Conventional banks dominate banking business whereas advocates of Islamic banks expect gradual paradigm shift in clientele. There are many reasons for believing them similar or different that may be religious or non-religious, but to date discerners are confused and are unable to separate the two on immaculate basis. Theoretical clarifications, given to date, do not seem to be plausible. It is indispensable to study similarities and dissimilarities of Islamic and conventional banking in order to corroborate the contemporary findings. Ahmad and Haron (2002) asserted that the products of Islamic banking are not whole heartedly accepted because they cannot be clearly distinguished from that of conventional. Khan and Mirakhor (1994) concluded that there is no such true profit and loss sharing system. Beck et al. (2011) bolstered that Islamic banks’ business model is not too different from that of conventional. It also represented that it is difficult for the discerners to clearly distinguish between the two paradigms of banking. Zeitun and Benjelloun (2012) argued that Islamic banks offer many products having high degree of resemblance with that of conventional banks. Samad (2004) also concluded that there is no material difference as such between financial performance of two categories of banks. Ahmad et al. (2010) emphasized that Muslims still patronize conventional banks for their faster and efficient services. In fact, there is resemblance between Islamic and conventional banks on many counts that have not been scientifically studied. There is lack of researches investigating the phenomenon in holistic, comprehensive and integrative way to make position rather clearer. It is important to investigate the issue of resemblance of Islamic banking with conventional because stakeholders are confused on the issue. Hence the objectives of this study are: i) to identify and rank the resemblances between Islamic and conventional banking, ii) to exhume interactions among the factors, iii) to enlighten upon that how structural model is helpful to distinguish between two paradigms of banking, iv) to deliberate theoretical and practical implications by way of classification of factors and v) to propose framework for future research. To achieve these objectives, the study considered different methodological choices. In order to ascertain critical resemblances, it considered ten different methods viz: literature review (Dhochak & Sharma, 2016; Li et al., 2019; Song et al., 2017), expert opinion (Dhochak & Sharma, 2016), case study (Li et al., 2019; Valmohammadi & Dashti, 2016), Delphi method (Bhosale & Kant, 2016; Zhang & Wei, 2010), exploratory factor analysis (Li & Yang, 2014), meta-analysis (Lohaus & Habermann, 2019), presuming by authors (Lohaus & Habermann, 2019), idea engineering and brainstorming session (Kumar et al., 2013), interview content analysis (Xiao, 2018) and anecdotal evidences (Azevedo et al., 2013). In this study the method of literature review coupled with expert opinion has been considered as appropriate. It is the most commonly used methods for these types of studies. For structuring of the issue grounded theory, thematic content analysis, structural equation modelling and interpretive structural modelling have been considered. Interpretive structural modelling has been found best to commensurate to objectives of the study (Warfield, 1973 & 1974; Sushil, 2017). In order to confirm the results of structural modelling another technique namely MICMAC has been employed to substantiate results of ISM. Rest of the paper is arranged as literature review, solution methodology, results, discussion and conclusion. 2. Literature Review Before embarking on analysis, the study accounted for reasonable amount of literature apropos to the issue. Out of thorough literature survey some germane studies are being reported here to set out the outset of the study. Lee and Isa (2017) bolstered that Islamic and conventional banks have similarities with slight differences. Salman and Nawaz (2018) carried a study in order to identify difference among Islamic and conventional banking concerning efficiency, liquidity and profitability. It signifies that customer trust in Islamic banking is more influenced by return on asset than in conventional banking. Amin et al. (2013) asserted that customer satisfaction with regards to trust, customer loyalty and image in Islamic and conventional banks are significantly interrelated; while differences exist in terms of Muslim and non352
3. Journal of Business and Social Review in Emerging Economies Vol . 6, No 1, March 2020 Muslim customers. Karim et al. (2014) argued that high requirements of capital influences deposit and lending actions of Islamic and conventional banks in similar manner. Rizvi and Arshad (2014) established that derivatives and proximate alternatives in Islamic finance are, in fact, not in compliance with the values and framework of Shariah rather they resemble with that of conventional, however, a more recent literature suggests some tools complying with Shariah for mitigating risks of Islamic finance. Rhanoui and Belkhoutout (2018) focused on how Islamic and conventional banks perceive operational risks objectifying to determine the extent to which operational risk is similar and different and found that most of the operational risks are similar. Barnett and Iqbal (2013) highlighted similarities between Islamic finance and Socially Responsible Investing (SRI). During the last two decades, Islamic finance has witnessed a much impressive growth rate, yet the Islamic fixed income market is lagging behind which also has resemblance with that of conventional banking. Al-Mamun et al. (2014) concluded that there are plenty of differences among interest-based conventional banking system and interest-free (Islamic) banking system. Islamic banking system adopts moral, social and ethical ways of creating wealth and gives second priority to economic benefits; whereas conventional believes in creating wealth through pure economic i.e. almost ignoring ethical, moral and social means. Hanif (2014) delineated that Islamic banks have gained customers’ trust and obtained deposits on the basis of profit and loss sharing yet the options of financing and investment available for Islamic banks are still similar to and minimal than conventional banks. Ibrahim and Ismail (2015) identified differences between both banking areas in terms of foundation law, economic functions and business organization. Ariff and Lewis (2014) proclaimed that there are few similarities between Shariah and common law but major differences exist among them by which it can be concluded that there are more differences among both laws than the similarities. Islamic banking is deflecting from its primary path of considering moral and social aspects by embracing operational practices of conventional banking. There is minor difference among them concerning financial risks and deposit rates but there is no significant difference in monthly average rates of lending (Ahmed et al., 2014; Azmat et al., 2017; Jawadi et al., 2016). Saidu (2014) found that there is a difference between principles for Islamic banking and its actual working. Khan (2010) argued that regulatory reforms are required instead of introducing a separate law for Islamic banking. Sr. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Resemblances Resemblance in Settlement of Cost of Funds Resemblance in Determination of Rates of Profits Resemblance in Sanction Procedures Resemblance in Repayment Annuities Resemblance in Documentation Processes Resemblance in Working Styles Resemblance in Interbank Clearings Resemblance in Borrowing Patterns Resemblance in Accounting Practices Same Banking Laws/Rules/Regulations Resemblance in Rating System Resemblance in Public Perception Resemblance in Client Assessment Procedure Resemblance in Banker’s Behavior Resemblance in Recovery Procedures Similar Employee Qualification Resemblance in HRM Practices Similar Marketing Tactics Author(s) (Lee & Isa, 2017) (Haron & Ahmad, 2000) (Lee & Isa, 2017) (Lee & Isa, 2017) (Lee & Isa, 2017) (Ahmad & Hassan, 2006) (Ismath Bacha, 2008) (Lee & Isa, 2017) (Karim, 2001) (Ariff & Lewis, 2014) (Hadriche, 2015) (Hanif et al., 2012) (Hanif et al., 2012) (Zainol et al., 2009) (Ahmed et al., 2006) (Bashir et at., 2011) (Bowra et al., 2012) (Saeed & Baig, 2013) Table 1: List of Resemblances in Islamic and Conventional Banking 353
4. Journal of Business and Social Review in Emerging Economies Vol . 6, No 1, March 2020 The practices of modern Islamic banking and financial institutions are violating the real Islamic principles and thus have failed in their claim to be a thorough alternative of conventional banking. Zarrouk et al. (2016) revealed that Islamic banking positively influences profitability in Middle East and North Africa (MENA) region yet many profitability antecedents of Islamic and conventional banks are same. It is also argued that changing the perspective of non-Muslims is major obstacle in evolving Islamic banking in its true letter and spirit. Non-Muslims view Islamic banking merely as a religious system that should only be used by Muslims (Badruddin, 2015; Omercic, 2016). However, some conventional banks are converting from conventional to Islamic that due to continuous demand for Islamic products and compliance with Shariah principles (Asif et al., 2017). With the support of aforementioned representation of literature total eighteen resemblances have been identified (Table 1) which were ratified by experts. Same have been used for data collection and analyses. 3. Solution Methodology This study follows qualitative approach. Overall design consists of selective literature review, survey for data collection and data analysis. It is a cross sectional experimental study using primary type of data elicited directly from stakeholders viz: Shariah scholars, Islamic bankers, conventional bankers, customers of Islamic banking, customers of conventional banking, regulators and researchers. Literature discourse is used to set the outset of the study and factor identification, ISM has been employed for imposing structure on the elements (resemblances here in this study) of the issue and MICMAC analysis for classification based on driving and dependence power. ISM and MICMAC analyses are mathematical techniques that used theory of binary matrices in combination with elementary concepts of set theory. The methodologies follow principle of Boolean Algebra for basic mathematical operations. Interpretive Structural Modeling (ISM): ISM is a well-defined methodology for construction of model using multiplication properties of binary matrices. It is visible modeling approach using reachability and transitive inferences through matrix transformation. ISM applies when there is no priory theoretical framework and the situation is conundrum like that of we have in hand. ISM uses the data collected from experts on the issue. Panel of Experts in ISM: Panel of experts means the persons conversant with issue. In this case panel have been recruited from within the stakeholders aforementioned. This type of sampling is useful when data are not-existing, expensive, limited, unreliable and confusing (Ranjbar et al., 2012). In this case opinion of experts is considered to be valid. The expert opinions outperform as compare to statistical archival data (Clayton, 1997). Experts have been recruited on the criteria of their theoretical knowledge, practical experience (minimum 10 years), expert knowledge and organization in which they are working admitting the fact that quality is more important than quantity of experts. The panel is comprised of sixteen experts (Clayton, 1997; Khan & Khan, 2013) having expertise on different aspects of the issue. We have developed rapport with experts as piloting. We approached more than thirty experts, only twenty-one agreed but actually participated sixteen. Experts first have been briefed on the issue in their office setting. Two to three discussion sessions were held with experts to persuade them to participate in the study and those who were agreeable were approached face-to-face one-on-one basis (Li & Yang, 2014). Many visits were paid to experts for completing survey. A matrix type questionnaire suitable to ISM was used to elicit the data using factor i leads to factor j. It took more than two months to approach experts and collect data. Standard symbols (i.e. V,A,O,X) have been used to record data. Data was consolidated using the principle “minority gives way to majority” (Abdullah & Siraj 2014; Cai & Xia 2018; Dhochak & Sharma, 2016; Li et al., 2019; Sushil 2012). The panel of experts was engaged at three different levels i.e. first for the judgement as to whether the factors are reasonable and representative of phenomenon, second for determination of contextual relationships and third for reviewing the model qua reality. We proceeded to ISM stepwise (Attri et al., 2013; Thakkar et al., 2008; Warfield, 1973) as follows: 354
5. Journal of Business and Social Review in Emerging Economies Vol . 6, No 1, March 2020 Step 1 Identification of factors Step 2 Development of Structural Self-Interaction Matrix (SSIM) Step 3 Establishing the contextual relationships among elements Step 4 Development of the final reachability matrix Step 5 Partitioning the reachability Step 6 Development of conical matrix Step 7 Development of digraph Step 1 Identification of factors: Already performed in section of literature review. Step 2 Development of Structural Self-Interaction Matrix (SSIM): The data collected on matrix type questionnaire has been converted into SSIM using principle of majority. SSIM contains data in i-j part in form of VAXO that follows the rules as given below: Figure 1: Rules of construction of SSIM and Initial Reachability Matrix Table 2: Structural Self-Interaction Matrix 3 Resemblances Resemblance in Settlement of Cost of Funds Resemblance in Determination of Rates of Profits Resemblance in Sanction Procedures 4 5 Resemblance in Repayment Annuities Resemblance in Documentation Processes 6 Resemblance in Working Styles 7 Resemblance in Interbank Clearings 8 Resemblance in Borrowing Patterns 9 10 Resemblance in Accounting Practices Same Banking Laws/Rules/Regulations 11 Resemblance in Rating System 12 16 17 Resemblance in Public Perception Resemblance in Client Assessment Procedure Resemblance in Banker’s Behavior Resemblance in Recovery Procedures Similar Employee Qualification Resemblance in HRM Practices 18 Similar Marketing Tactics 1 2 13 14 15 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 V O O O O A V O A O V O O O O O O O V O O A O X A O V O O O O V O X X X O O V A O V X O V A V A V O X O O V X A V O A V O O V O A V V O V O O O O X O O O A A O V V A V A X V A V A V V O O O O O O V V V A V O V O O O A V V V V O V O V O V A O V V O V V A O O O O O A A A A A A X X O O O V A A O O O O V V O Step 3 Establishing the contextual relationship among elements: For establishing the contextual relationships initial reachability matrix has been prepared using the rules as enumerated in Figure 1. 355
6. Journal of Business and Social Review in Emerging Economies Vol . 6, No 1, March 2020 Table 3: Initial Reachability Matrix 2 1 3 0 4 0 5 0 6 0 7 0 8 1 9 0 10 0 11 0 12 1 13 0 14 0 15 0 16 0 17 0 18 0 Driving 1 1 1 2 0 1 0 1 0 0 0 0 1 0 0 1 0 0 0 0 1 0 5 3 0 0 1 1 1 1 0 0 1 0 0 1 1 0 1 0 1 0 9 4 0 0 1 1 1 0 0 1 0 0 1 0 0 1 0 0 0 1 7 5 0 0 1 0 1 1 0 1 1 0 0 1 0 1 1 0 0 0 8 6 0 0 1 0 1 1 0 0 0 0 0 1 1 0 1 0 1 1 8 7 1 1 0 0 0 0 1 0 1 0 1 1 0 0 0 0 0 0 6 8 0 0 0 0 1 0 1 1 1 1 1 0 1 0 1 0 0 0 8 9 0 1 0 1 0 1 0 0 1 0 1 1 0 0 0 0 1 0 7 10 1 1 1 0 1 1 1 0 1 1 1 1 1 1 1 0 1 1 15 11 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 2 12 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 2 13 0 0 1 0 1 0 0 0 0 0 1 1 1 1 1 0 0 0 7 14 0 0 0 0 0 1 0 0 0 0 0 1 1 1 1 0 0 0 5 15 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 3 16 0 0 1 0 0 1 0 0 1 0 0 1 0 1 0 1 1 1 8 17 0 0 0 0 0 1 0 0 0 0 0 1 0 1 0 0 1 0 4 18 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 1 3 3 5 7 5 7 8 3 5 8 2 7 16 7 7 8 1 7 5 Dependence 4 Step 4 Development of the final reachability matrix: Initial reachability matrix has been converted into final reachability by removing transitivity as per norms of ISM (Table 4). 356 1 2 3 4 5 6 7 1 1 0 0 0 0 0 1 2 3 4 1 0 1* 1 1* 1 1* 1 1 0 1 1 1* 1 1* 0 1 1* 1 0 1* 8 1* 1* 1* 1* 9 10 11 0 1 0 12 Table 4: Final Reachability Matrix 5 6 7 8 9 10 11 12 13 1* 0 1* 1 1* 1* 1* 1 1* 1* 1* 0 1* 1 0 1* 1 0 1 1 0 1* 1 0 1* 1 1 1 1* 1* 1 1* 1* 1 1* 1* 1 1 1* 1 1 1* 1* 1 1* 1 1 1* 1* 1* 0 1* 1 1 0 1* 1 1* 1 0 1 1 0 14 15 16 17 18 Driving 13 0 1* 0 1* 0 1* 0 0 1 1* 12 14 1* 1 0 1 1* 15 1 1* 0 1* 1 16 1 1 0 1* 1* 14 1* 1 0 1 1 10 0 0 0 1* 0 16 1* 1 0 1* 0 1 1* 1 1 1 1 1 1* 1 1 1 0 1* 1 1* 1 1* 1 0 0 0 1 1 0 0 1 0 0 1* 1* 1 1 0 1* 1 0 1 1 1 1 1 1 1* 1* 1* 1 1 1 0 0 0 0 0 0 1 1 0 1* 1 0 0 0 0 0 1* 0 1* 1 0 1* 1* 1 1* 0 1* 0 0 0 13 0 0 1 1* 1 1* 0 1* 1* 0 1 1 1 1 1 0 1* 0 14 0 0 1* 0 1* 1 0 1* 0 0 1* 1 1 1 1 0 0 0 12 9 15 16 0 0 0 0 1* 0 1* 1 1* 1* 0 1 0 0 1* 1* 0 1 0 0 1* 0 1 1 1 0 1* 1 1 1* 0 1 0 1 0 1 8 12 14 17 3 8
7. Journal of Business and Social Review in Emerging Economies 17 18 Dependence 0 0 4 0 0 8 1 * 0 1* 1 1* 1 1* 0 14 13 16 13 0 0 8 1* 0 1* 0 17 12 0 0 7 Vol. 6, No 1, March 2020 0 1 1* 1 1* 1* 1 0 1* 0 16 18 13 14 14 0 0 1 10 8 1 1* 0 1 13 10 Step 5 Partitioning the reachability matrix: Binary matrix given as Table 4 has been partitioned (Table 5 – 13) using the elementary concepts of set theory according to Warfeild (1973). Table 5: Iteration I Sr Reachability Set Antecedent Set Intersection Set 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 1,2,4,5,7,8,9,10,11,12,13,15,17 2,3,4,5,6,8,9,11,12,14,17,18 2,3,4,5,6,8,9,11,12,13,14,15,17,18 3,4,5,6,7,8,9,10,11,12,13,14,15,17,18 2,3,4,5,6,7,8,9,10,11,12,13,14,15,17,18 3,4,5,6,7,8,9,11,12,13,14,15,17,18 1,2,4,6,7,8,9,11,12,17 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,17 2,3,4,5,6,9,10,11,12,13,14,15,17,18 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,17,18 8,11,12 5,7,8,10,11,12,13,15 3,4,5,6,8,9,11,12,13,14,15,17 3,5,6,8,11,12,13,14,15 3,5,8,11,12,13,14,15 3,4,5,6,8,9,12,14,15,16,17,18 3,5,6,8,12,13,14,15,17,18, 3,4,5,8,11,12,14,18 1,7,8,10 1,2,3,5,7,8,9,10 2,3,4,5,6,8,9,10,13,14,15,16,17,18 1,2,3,4,5,6,7,8,9,10,13,16,18 1,2,3,4,5,6,8,9,10,12,13,14,15,16,17,18 2,3,4,5,6,7,8,9,10,13,14,16,17 1,4,5,6,7,10,12 1,2,3,4,5,6,7,8,10,11,12,13,14,15,16,17,18 1,2,3,4,5,6,7,8,9,10,13,16 1,4,5,9,10,12 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,18 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18 1,3,4,5,6,8,9,10,12,13,14,15,17 2,3,4,5,6,8,9,10,13,14,15,16,17,18 1,3,4,5,6,8,9,10,12,13,14,15,16,17 16 1,2,3,4,5,6,7,8,9,10,13,16,17 2,3,4,5,6,9,10,16,18 1,7,8,10 2,3,5,8,9 2,3,4,5,6,8,9,13,14,15,17,18 3,4,5,6,7,8,9,10,13,18 2,3,4,5,6,8,9,10,12,13,14,15,17,18 3,4,5,6,7,8,9,13,14,17 1,4,6,7,12 1,2,3,4,5,6,7,8,10,11,12,13,14,15 2,3,4,5,6,9,10,13 1,4,5,9,10,12 8,11,12 5,7,8,10,11,12,13,15 3,4,5,6,8,9,12,13,14,15,17 3,5,6,8,13,14,15 3,5,8,12,13,14,15 16 3,5,6,8,13,17 3,4,5,18 Level I I Table 6: Iteration II Sr . 1 2 3 4 5 Reachability Set 1,2,4,5,7,8,9,10, 13,15,17 2,3,4,5,6,8,9, 14,17,18 2,3,4,5,6,8,9,13,14,15,17,18 3,4,5,6,7,8,9,10, 13,14,15,17,18 2,3,4,5,6,7,8,9,10,13,14,15,17,18 6 7 8 3,4,5,6,7,8,9,13,14,15,17,18 1,2,4,6,7,8,9,17 1,2,3,4,5,6,7,8,9,10,13,14,15,17 9 10 2,3,4,5,6,9,10,13,14,15,17,18 1,2,3,4,5,6,7,8,9,10,13,14,15,17, 18 3,4,5,6,8,9,13,14,15,17 3,5,6,8,13,14,15 3,5,8,13,14,15 3,4,5,6,8,9,14,15,16,17,18 3,5,6,8,13,14,15,17,18, 3,4,5,8,14,18 13 14 15 16 17 18 Antecedent Set Intersection Set 1,7,8,10 1,2,3,5,7,8,9,10 2,3,4,5,6,8,9,10,13,14,15,16,17,18 1,2,3,4,5,6,7,8,9,10,13,16,18 1,2,3,4,5,6,8,9,10, 13,14,15,16,17,18 2,3,4,5,6,7,8,9,10,13,14,16,17 1,4,5,6,7,10, 1,2,3,4,5,6,7,8,10,13,14,15,16,17, 18 1,2,3,4,5,6,7,8,9,10,13,16 1,4,5,9,10 1,7,8,10 2,3,5,8,9 2,3,4,5,6,8,9,13,14,15,17,18 3,4,5,6,7,8,9,10,13,18 2,3,4,5,6,8,9,10,13,14,15,17, 18 3,4,5,6,7,8,9,13,14,17 1,4,6,7 1,2,3,4,5,6,7,8,10,13,14,15 1,3,4,5,6,8,9,10,13,14,15,17 2,3,4,5,6,8,9,10,13,14,15,16,17,18 1,3,4,5,6,8,9,10,13,14,15,16,17 16 1,2,3,4,5,6,7,8,9,10,13,16,17 2,3,4,5,6,9,10,16,18 3,4,5,6,8,9,13,14,15,17 3,5,6,8,13,14,15 3,5,8, 13,14,15 16 3,5,6,8,13,17 3,4,5,18 Leve l 2,3,4,5,6,9,10,13 1,4,5,9,10 II II II 357
8. Journal of Business and Social Review in Emerging Economies Vol . 6, No 1, March 2020 Table 7: Iteration III Sr. Reachability Set Antecedent Set Intersection Set Level 1,2,4,5,7,8,9,10, 17 1,7,8,10 1,7,8,10 1 2,3,4,5,6,8,9,17,18 1,2,3,5,7,8,9,10 2,3,5,8,9 2 2,3,4,5,6,8,9,17,18 2,3,4,5,6,8,9,10,16,17,18 2,3,4,5,6,8,9,17,18 III 3 3,4,5,6,7,8,9,10,18 1,2,3,4,5,6,7,8,9,10,16,18 3,4,5,6,7,8,9,10,18 III 4 2,3,4,5,6,7,8,9,10,17,18 1,2,3,4,5,6,8,9,10,16,17,18 2,3,4,5,6,8,9,10,17,18 5 3,4,5,6,7,8,9,17,18 2,3,4,5,6,7,8,9,10,16,17 3,4,5,6,7,8,9,17 6 1,2,4,6,7,8,9,17 1,4,5,6,7,10, 1,4,6,7 7 1,2,3,4,5,6,7,8,9,10,17 1,2,3,4,5,6,7,8,10,16,17,18 1,2,3,4,5,6,7,8,10 8 2,3,4,5,6,9,10,17,18 1,2,3,4,5,6,7,8,9,10,16 2,3,4,5,6,9,10 9 1,4,5,9,10 1,4,5,9,10 10 1,2,3,4,5,6,7,8,9,10,17,18 3,4,5,6,8,9,16,17,18 16 16 16 3,5,6,8,17,18, 1,2,3,4,5,6,7,8,9,10,16,17 3,5,6,8,17 17 3,4,5,8,18 2,3,4,5,6,9,10,16,18 3,4,5,18 III 18 Table 8: Iteration IV Sr. Reachability Set Antecedent Set Intersection Set Level 1,2,5,7,8,9,10, 17 1,7,8,10 1,7,8,10 1 2,5,6,8,9,17 1,2,5,7,8,9,10 2,5,8,9 2 2,5,6,7,8,9,10,17 1,2,5,6,8,9,10,16,17 2,5,6,8,9,10,17 5 5,6,7,8,9,17 2,5,6,7,8,9,10,16,17 5,6,7,8,9,17 IV 6 1,2,6,7,8,9,17 1,5,6,7,10, 1,6,7 7 1,2,5,6,7,8,10,16,17 1,2,5,6,7,8,10 8 1,2,5,6,7,8,9,10,17 2,5,6,9,10,17 1,2,5,6,7,8,9,10,16 2,5,6,9,10 9 1,5,9,10 1,5,9,10 10 1,2,5,6,7,8,9,10,17 5,6,8,9,16,17 16 16 16 5,6,8,17 1,2,3,4,5,6,7,8,9,10,16,17 3,5,6,8,17 IV 17 Table 9: Iteration V Sr. Reachability Set Antecedent Set Intersection Set Level 1,2,5,7,8,9,10 1,7,8,10 1,7,8,10 1 2,5,8,9 1,2,5,7,8,9,10 2,5,8,9 V 2 2,5,7,8,9,10 1,2,5,8,9,10,16,17 2,5,8,9,10 5 1,2,7,8,9 1,5,6,7,10, 1,7 7 1,2,5,7,8,9,10, 1,2,5,7,8,10,16 1,2,5,7,8,10 8 2,5,9,10 1,2,5,7,8,9,10,16 2,5,9,10 V 9 1,2,5,7,8,9,10 1,5,9,10 1,5,9,10 10 5,8,9,16 16 16 16 Table 10: Iteration VI Sr. Reachability Set Antecedent Set Intersection Set Level 1,5,7,8,10 1,7,8,10 1,7,8,10 1 5,7,8,10 1,5,8,10,16 5,8,10 5 1,7,8 1,5,6,7,10 1,7 7 1,5,7,8,10 1,5,7,8,10,16 1,5,7,8,10 VI 8 1,5,7,8,10 1,5,10 1,5,10 10 5,8,16 16 16 16 Table 11: Iteration VII Sr. Reachability Set Antecedent Set Intersection Set Level 1,5,7,10 1,7,10 1,7,10 1 5,7,10 1,5,10,16 5,10 5 1,7 1,5,6,7,10 1,7 VII 7 1,5,7,10 1,5,10 1,5,10 10 358
9. Journal of Business and Social Review in Emerging Economies 5 ,16 16 Vol. 6, No 1, March 2020 16 16 Table 12: Iteration VIII Sr. Reachability Set Antecedent Set Intersection Set Level 1,5,10 1,10 1,10 1 5,10 1,10,16 5,10 VIII 5 1,5,10 1,5,10 1,5,10 VIII 10 5,16 16 16 16 Table 13: Iteration IX Sr. Reachability Set Antecedent Set Intersection Set Level 1 1 1 IX 1 16 16 16 IX 16 Step 6 Development of conical matrix: Conical matrix has been constructed by swapping column jn with jn and swapping column in with in according to Warfield (1973). Table 14: Conical Matrix 11 12 13 14 15 3 4 18 6 17 2 9 8 7 5 10 1 16 Driving 11 1 1 0 0 0 0 0 0 0 0 0 0 1* 0 0 0 0 0 3 12 1* 1 1* 0 1* 0 0 0 0 0 0 0 1 1* 1* 1* 0 0 8 13 1 1 1 1 1 1 1* 0 1* 1* 0 1* 1* 0 1 0 0 0 12 14 1* 1 1 1 1 1* 0 0 1 0 0 0 1* 0 1* 0 0 0 9 15 1* 1 1 1* 1 1* 0 0 0 0 0 0 1* 0 1* 0 0 0 8 3 1* 1 1 1* 1 1 1 1* 1 1 1* 1 1* 0 1 0 0 0 14 4 1 1* 1* 1 1* 1 1 1 1* 1* 0 1* 1 1* 1 1* 0 0 15 18 1* 1 0 1* 0 1* 1 1 0 0 0 0 1* 0 1* 0 0 0 8 6 1* 1 1 1* 1 1 1* 1 1 1 0 1* 1* 1* 1 0 0 0 14 17 0 1 1* 1 1* 1* 0 1* 1 1 0 0 1* 0 1* 0 0 0 10 2 1* 1 0 1* 0 1* 1 1* 1* 1 1 1 1* 0 1* 0 0 0 12 9 1 1 1* 1* 1* 1* 1 1* 1 1 1 1 0 0 1* 1* 0 0 14 8 1 1* 1 1* 1 1* 1* 0 1* 1* 1* 1 1 1 1 1 1* 0 16 7 1 1 0 0 0 0 1* 0 1* 1* 1 1 1* 1 0 0 1 0 10 5 1* 1 1* 1 1 1 1* 1* 1 1* 1* 1 1 1* 1 1* 0 0 16 10 1 1 1 1 1 1 1* 1 1 1 1 1 1* 1 1 1 1 0 17 1 1* 1 1* 0 1* 0 1* 0 0 1* 1 1* 1 1* 1* 1* 1 0 13 16 0 1 0 1 1* 1 1* 1 1 1 0 1 1* 0 1* 0 0 1 12 Dependence 16 18 13 14 14 14 13 10 13 13 8 12 17 8 16 7 4 1 Step 7 Development of digraph: The level determined through iterations aforementioned and arrangement of the level by way of swapping rows and columns of final reachability matrix and a model appeared on diagonal. It has been presented in form of a directed graph Figure 2. 359
10. Journal of Business and Social Review in Emerging Economies Vol . 6, No 1, March 2020 12 11 Level I 13 14 15 Level II 18 3 4 Level III 6 17 Level IV 2 9 Level V 8 Level VI 7 5 Level VII 10 Level VIII 1 16 Level IX Figure 2: ISM Model There are total nine levels where factor 11 and 12 occupy top level (Level I); 13, 14 and 15 (Level II); 3, 4 and 18 (Level III); 6 and 17 (Level IV); 2 and 9 (Level V); 8 (Level VI); 7 (Level VII); 5 and 10 (Level VIII) and 1 and 16 occupy bottom (Level IX). It can be observed that at levels 11, 12; 5, 10; 1, 16 are not linked, but 13, 14, 15; 3, 4, 18; 6, 17; 2, 9 are two way related. MICMAC Analysis: It is a structural methodology that analyzes the underlying structure of factors (Godet, 1986). Objective of MICMAC is to identify key factors. This methodology has ability to supplement ISM by classifying the factors into four clusters namely independent, autonomous, linkage and dependent. 360
11. Journal of Business and Social Review in Emerging Economies Vol . 6, No 1, March 2020 Figure 3: Driving-Dependence Diagram Independent Custer: It contains factor having high driving power but low dependence power. Factors listed at 1, 2, 7, 10 and 16 are in independent cluster. These are key factors and high care is needed to handle them. Practitioners must therefore give priority to understanding these factors. Autonomous Cluster: This cluster contains the factors which have weak driving and weak dependence. They are separated from model have few but powerful links and don’t have much impact on system. There is no such factor in this study in autonomous cluster. Non-existence of autonomous mean all factors play important role. Dependent Cluster: It contains factors that have weak driving but strong dependence power. In this study factors listed at 11, 12, 14, 15 and 18 are dependent factors. Dependent factors resultantly depend on others and they need extra care. Linkage Cluster: It contains factors that have strong driving and strong dependence power. In this study factors listed at 4, 5, 6, 8, 9, 13 and 17 are linking factors. They are considered as unbalanced because any action on them affects others and has feedback effect on themselves. 361
12. Journal of Business and Social Review in Emerging Economies Vol . 6, No 1, March 2020 4. Results There are three parts of the study i.e. literature review, ISM and MICMAC. Results of literature review revealed that the total eighteen critical resemblances between two paradigms of banking. Results of ISM show that there is nine level structure underlying the phenomenon. Resemblance in rating system (11) and resemblance in public perception (12) occupy highest level therefore is less critical, whereas resemblance in settlement of cost of funds (1) and similar employee qualification (16) occupy bottom level and are the most critical. All remaining factors constitute middle part of the model having moderate low and moderate high severity depending on the level they occupy. Results of MICMAC show that 1, 2, 7, 10 and 16 are independent; 4, 5, 6, 8, 9, 13 and 17 are linking and 11, 12, 14, 15 and 18 are dependent. Result of Literature Review No. Barrier Resemblance in Settlement 1 of Cost of Funds Resemblance in Determination of Rates of 2 Profits Resemblance in Sanction 3 Procedures Resemblance in Repayment 4 Annuities Resemblance in 5 Documentation Processes Resemblance in Working 6 Styles Resemblance in Interbank 7 Clearings Resemblance in Borrowing 8 Patterns Resemblance in Accounting 9 Practices Same Banking 10 Laws/Rules/Regulations Resemblance in Rating 11 System Resemblance in Public 12 Perception Resemblance in Client 13 Assessment Procedure Resemblance in Banker’s 14 Behavior Resemblance in Recovery 15 Procedures Similar Employee 16 Qualification Resemblance in HRM 17 Practices 18 Similar Marketing Tactics Driving 13 Results of MICMAC Analysis Dependence Effectiveness Cluster ISM Results Level Comments Key Factor 4 9 Independent IX 8 4 Independent V 14 0 Linkage III 13 1 Linkage III 16 0 Linkage VIII 13 1 Linkage IV 8 2 Independent VII 17 −1 Linkage VI 12 2 Linkage V 7 10 Independent VIII 16 −13 Dependent I Dependent I 12 14 15 16 14 10 16 14 17 3 8 12 9 8 12 10 8 −10 18 13 −1 Linkage II 14 −5 Dependent II 14 −6 Dependent II 1 11 Independent IX 13 −2 Linkage IV 10 −2 Dependent III Key Factor Table 15: Summary of Results There is no autonomous factor. Summary of the results is presented as Table 15. Resemblance in settlement of cost of funds (1) and similar employee qualification (16) are the key factors that create high degree of resemblance in Islamic and conventional banks. 5. Discussion Main objective of the study is to identify, rank, exhume the relations and classify the critical resemblances between Islamic and conventional banking. The problem of resemblance of banking paradigms is concern of all stakeholders for different reasons vital to them. This research has identified the confusing factors and ranked them on the basis of their criticalness. It pointed out the key factors that are source of confusion and established the contextual relationships among them. It is an original attempt by the authors substantiated by real time survey data collected from experts on the issue. It is a seminal study that 362
13. Journal of Business and Social Review in Emerging Economies Vol . 6, No 1, March 2020 analyzed differently the phenomenon from traditional methods. This finding is consistent with the result of previous studies (Table 16). Table 16: Comparison of Present Study with Prior Studies Sr Study Focus 1 Current Study Resemblances 2 Sukmana & Ibrahim, 2017 Rates of return 3 Lee & Isa, 2017 Determinants of bank margins 4 Khan et al., 2017 Comparative performance Wan Ibrahim & Ismail, 2015 Al-Mamun et al., 2014 Similarities and differences Comparison 5 6 Country Factors Methodology Result Pakistan Eighteen ISM and MICMAC Resemblance in settlement of cost of funds and similar employee qualification are key factors. Malaysia 1,3,6,9 and 12 months rates nonlinear ARDL (NARDL) Rates of return do not rigidly peg to each other. Malaysia Fifteen Pakistan Return to Risk Ratio Two-step generalized method of moments (GMM) technique ARMA-GARCH-inMean model Malaysia - Literature review Malaysia Seven Financial Ratios There are significant similarities No difference in the performance. Similarity is prevalent in supervisory roles. No major difference. The authors found five different studies as listed above in Table 16 that are comparable with the study in hand. This comparison revealed that in general present studies is aligned with the contemporary literature but is different on the counts of factors under study, methodological approach, context of the study, respondents from which the data have been collected, scope of the study and results. 6. Conclusion This research has identified the confusing factors and ranked them on the basis of their criticalness because resemblance between the two paradigms of banking is hot issue. The study pointed out the key factors that are source of confusion and established the contextual relationships among them. It is envisaged on literature review for identification of factors, employed ISM for ranking, prioritizing and modelling coupled with MICMAC for classification of the factors into independent, linkage, autonomous and dependent. Total eighteen factors were identified and sixteen experts were recruited from which the data was collected regarding the issue. Results of ISM show that there is nine level structure underlying the phenomenon. Resemblance in rating system (11) and resemblance in public perception (12) occupy highest level therefore is less critical, whereas resemblance in settlement of cost of funds (1) and similar employee qualification (16) occupy bottom level and are the most critical. All remaining factors constitute middle part of the model having moderate low and moderate high severity depending on the level they occupy. Results of MICMAC show that 1, 2, 7, 10 and 16 are independent; 4, 5, 6, 8, 9, 13, 17 are linking and 11, 12, 14, 15 and 18 are dependent. There is no autonomous factor. The study has valuable theoretical contribution by way of identification of factors, ISM model and driving-dependence diagram. Further it provides more supplementary information regarding the phenomena that gives greater understanding to stakeholders. The factors are generic and the results are fairly generalizable. ISM model and driving-dependence diagram offers practitioners and policy makers a framework for resolving practical issues. This study is helpful in building awareness in customers and society at large. It makes easy for researchers to develop further frameworks on the bases of classification. It is equally useful for regulators, management, employees, customers, researchers, religious scholars and society at large. It is an original attempt by the authors substantiated by real time survey data collected from experts on the issue. The study also has certain limitations. Firstly, ISM method only identifies but does not quantify the relationships therefore some other weighing method SEM, PCA, AHP, ANP, TOPSIS, GRA etc. may be used to quantify the relationships. Secondly, key factors have only been identified from limited number of published articles there might be some factors which might have been overlooked therefore future studies should be rather rigorous. Thirdly, the study was conducted in Pakistan since there are varying cultural, social, technological and political systems therefore future studies must be conducted in different countries. Fourthly, data has been collected from few stakeholders therefore it is recommended that extensive research should be conducted taking inputs from more stakeholders. 363
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