Technology-enabled Personalization for Mobile Banking Services Literature Review and Theoretical Framework
Main Article Content
Keywords
M-Banking, UTAUT, Technology-enabled Personalization, Mobile services, Literature Review
Abstract
New technologies are giving very interesting potential to the personalization of products and services, in particular of mobile services. The study of the literature shows that technology-based personalization is an important factor in the adoption of mobile services. However, previous researchers are not unanimous as to the nature of this role: some studies confirm the moderating or mediating effect of personalization on the relationship between the adoption factors stated in the Unified Technology Acceptance and Utilization Theory (UTAUT) and the intention to adopt technology-based services. Other researchers consider that personalization rather exerts a causal relationship on the adoption of technology-based services. This paper undertakes a literature review with the aim of clarifying the impact of new technologies, such as artificial intelligence, Big Data, Internet of Things and Block Chain, on the personalization of mobile banking services. Moreover, this study presents a synthesis of previous research examining the role of personalization in relation to the factors affecting adoption and the intention to adopt mobile banking. Finally, this research proposes a conceptual model that can serve as a basis for future empirical research in the context of mobile services. Results and discussion could guide future empirical research in this area.
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References
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Guo, X., Sun, Y., Yan, Z., & Wang, N. (2012). Privacy-personalization paradox in adoption of mobile health service: the mediating role of trust. https://aisel.aisnet.org/pacis2012/27
Hagen, L., Uetake, K., Yang, N., Bollinger, B., Chaney, A. J., Dzyabura, D., & Zhu, Y. (2020). How can machine learning aid behavioral marketing research? Marketing Letters, 31(4), 361–370. https://doi.org/10.1007/s11002-020-09535-7
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Hmoud, B. I., & Várallyai, L. (2020). Artificial Intelligence in Human Resources Information Systems: Investigating its Trust and Adoption Determinants. International Journal of Engineering and Management Sciences, 5(1), 749–765. https://doi.org/10.21791/IJEMS.2020.1.65
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Jun 10, 2022
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Khemiri, M., & Jallouli, R. (2022). Technology-enabled Personalization for Mobile Banking Services: Literature Review and Theoretical Framework. Journal of Telecommunications and the Digital Economy, 10(2), 173–194. https://doi.org/10.18080/jtde.v10n2.545
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