ISLAMIC BANK CUSTOMERS’ ADOPTION OF DIGITAL BANKING SERVICES: EXTENDING DIFFUSION THEORY OF INNOVATION
Abstract
This paper examines the factors that drive non-users of digital banking services rendered by Pakistani Islamic banks to adopt digital banking using the Diffusion theory of Innovation (DOI). We gather data from 208 Islamic bank customers who do not use digital banking services. Findings of the study reveal that adoption of digital services offered by Islamic banks are largely decided by relative advantage, technology self-efficacy and complexity. All the factors above are influential in determining the digital banking adoption by non-users. The finding serves as an essential input to banks and policy makers in expanding the adoption of digital banking services of Islamic banks.
Acknowledgment
The authors would like to thank Bank Indonesia Institute, Bank Indonesia, for the funding that made this study possible.
References
Amin, H., Abdul-Rahman, A.-R., & Abdul-Razak, D. (2013). An integrative approach for understanding Islamic home financing adoption in Malaysia. International Journal of Bank Marketing, 31(7), 544-573.
Amin, H., Abdul-Rahman, A. R., & Abdul-Razak, D. (2016). Malaysian consumers’ willingness to choose Islamic mortgage products: An extension of the theory of interpersonal behaviour. International Journal of Bank Marketing, 34(6), 868-884.
Amin, H., Abdul-Rahman, A.-R., Ramayah, T., Supinah, R., & Mohd-Aris, M. (2014). Determinants of online waqf acceptance: An empirical investigation. The Electronic Journal of Information Systems in Developing Countries, 60(1), 1-18.
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall, Inc.
Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multi-trait multi-method matrix. Psychological Bulletin, 56(2), 81-105.
Carranza, R., Díaz, E., Sánchez-Camacho, C., & Martín-Consuegra, D. (2021). e-banking adoption: An opportunity for customer value co-creation. Frontiers in Psychology, 11, 621248. https://doi.org/10.3389/fpsyg.2020.621248
Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modelling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic mail emotion/ adoption study. Information Systems Research, 14(2), 189-217.
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211.
Dimitrova, I., Öhman, P., & Yazdanfar, D. (2022). Barriers to bank customers’ intention to fully adopt digital payment methods. International Journal of Quality and Service Sciences, 14(5), 16-36.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Gefen, D., Straub, D., & Boudreau, M. (2000). Structural equation modelling and regression: Guidelines for research practice. Communications of the Association for Information Systems, 4(7), 1-78. https://doi.org/10.17705/1CAIS.00407
Gu, J-C., Lee, S-C., & Suh, Y-H. (2009). Determinants of behavioral intention to mobile banking. Expert Systems with Applications, 36(9), 11605-11616.
Hair, J., Black, W., Babin, B., & Anderson, R. (2010). Multivariate data analysis. Upper Saddle River, N. J., London: Pearson Education.
Hair, J. F., Black, W., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (6th Edition). Upper Saddle River, NJ: Pearson Prentice Hall.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modelling. Journal of the Academy of Marketing Science, 43, 115-135. https://doi.org/10.1007/s11747-014-0403-8
Liu, Y., & Li, H. (2010). Mobile internet diffusion in China: An empirical study. Industrial Management & Data Systems, 110(3), 309-324.
Lowry, P. B., & Gaskin, J. (2014). Partial least squares (PLS) structural equation modelling (SEM) for building and testing behavioral causal theory: When to choose it and how to use it. IEEE Transactions on Professional Communication, 57(2), 123-146.
Marcoulides, G. A., & Saunders, C. (2006). PLS: A silver bullet?. A commentary on sample size issues in PLS modeling. MIS Quarterly, 30(2), 3-9.
Mathieu, J. (2007). A longitudinal cross-level model of leader and salesperson influences on sales force technology use and performance. Journal of Applied Psychology, 92(2), 528-537.
Mauro C., Hernandez, J., & Afonso Mazzon, J. (2007). Adoption of internet banking: Proposition and implementation of an integrated methodology approach. International Journal of Bank Marketing, 25(2), 72-88.
Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192-222.
Nunnaly, J. C. (1978). Psychometric theory (2nd edition). New York: McGraw-Hill, Inc.
OECD. (2020). Digital disruption in banking and its impact on competition http://www.oecd.org/daf/competition/digital-disruption-in-financial-markets.htm (Retrieved on June 1, 2021).
Rogers, E. M. (2003). Diffusion of innovations (4th edition). New York: The Free Press.
Rogers, E. M., & Shoemaker, F. (1983). Diffusion of innovation: A cross-cultural approach. New York, NY: The Free Press.
Shaikh, I. M., Bin Noordin, K., Arijo, S., Shaikh, F., & Alsharief, A. (2020). Predicting customers’ adoption towards family takaful scheme in Pakistan using diffusion theory of innovation. Journal of Islamic Marketing, 11(6), 1761-1776.
Shaikh, I. M., Qureshi, M. A., Noordin, K., Shaikh, J. M., Khan, A., & Shahbaz, M. S. (2020). Acceptance of Islamic financial technology (FinTech) banking services by Malaysian users: An extension of technology acceptance model. Foresight, 22(3), 367-383.
Shaikh, I. M., Shaikh, F. M., & Bin Noordin, K. (2022). Predicting customers’ acceptance towards Islamic home financing using DTPB theory. Journal of Islamic Marketing, 13(11), 2331-2346.
Shi, W., Shambare, N., & Wang, J. (2008). The adoption of internet banking: An institutional theory perspective. Journal of Financial Services Marketing, 12(4), 272-286.
Shih, Y., & Fang, K. (2004). The use of a decomposed theory of planned behavior to study Internet banking in Taiwan. Internet Research, 14(3), 213-223.
State Bank of Pakistan (SBP). (2019). Annual Report, State bank of Pakistan, Karachi.
State Bank of Pakistan (SBP). (2020). Annual Report, State bank of Pakistan, Karachi.
Sveriges Riksbank. (2019). Payments in Sweden, Sveriges Riksbank, Stockholm.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
Voorhees, C. M., Brady, M. K., Calantone, R., & Ramirez, E. (2016). Discriminant validity testing in marketing: An analysis, causes for concern, and proposed remedies. Journal of the Academy of Marketing Science, 44(1), 119-134.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Journal of Islamic Monetary Economics and Finance is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
