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https://oarep.usim.edu.my/jspui/handle/123456789/2026
Title: | Customer loyalty assessment in Malaysian islamic banking using artificial intelligence | Authors: | Kishada, Zeyad M. Em. Wahab, Norailis Ab. Mustapha, Aouache |
Keywords: | Cross validation model;Customer loyalty;Malaysian Islamic banks | Issue Date: | 2016 | Publisher: | Asian Research Publishing Network | Journal: | Journal of Theoretical and Applied Information Technology | Abstract: | Banks are in the process of moving into a more competitive financial atmosphere with a wide variety of financial products and services. From the practical perspective, the prediction of customer loyalty will provide a better understanding of Islamic banking that relates to customer loyalty and offer a platform that helps the bank management to improve the customer loyalty. Therefore, the primary objective of this paper is the development of an artificial intelligence model for customers� loyalty assessment in Malaysian Islamic Banking. To achieve this, first a returned of 373 from total 500 samples was collected via self administered questionnaires distributed by hand to customers at various Islamic bank branches around Kuala Lumpur, Malaysia. Second, the data analysis of the returned samples and testing with several statistical tools and methods was examined using SPSS. The data used were customer satisfaction, customer service quality, customer perceived value and customer trust which are the factors affecting customer loyalty. Third, assessment model was proposed and developed using an artificial neural network (ANN) based on cross validation for modeling customer loyalty. The decision of changing the ANN architecture is essentially based on prediction results to obtain the best ANN model computation to quantify customer loyalty. A statistical performance was conducted includes, root mean square error (RMSE) and correlation coefficient (COE) between the measured and estimated customer loyalty by the ANN. Experimental results obtained based cross validation with COE (0.9867) indicates that the third ANNmodel has better accurate results with fold 4 and trainLM [4 10 1] compared to others structures. Simulations results yielded significant results in predicting customer loyalty. In conclusion, this research has achieved its stated goal of developing an ANN model that provide quantitative assessment to facilitate Islamic banks managers in their effort to develop and implement successful customer loyalty strategies. � 2005 - 2016 JATIT & LLS. All rights reserved. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84967334658&partnerID=40&md5=3aa329ae4c327f9eccc04c4d927dab2c | ISSN: | 19928645 |
Appears in Collections: | Scopus |
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Customer loyalty assessment in Malaysian islamic banking using artificial intelligence.pdf | 578.02 kB | Adobe PDF | View/Open |
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