Analysis of Key Determinants of Mobile Banking Usage: A Structural Equation Modeling (SEM) Approach Based on the Technology Acceptance Model (TAM)

  • Daffa Al Azhar Universitas Islam Indonesia, Yogyakarta, Indonesia
  • Dwi Martutiningrum Universitas Islam Indonesia, Yogyakarta, Indonesia
Keywords: Perceived Ease of Use, Perceived Usefulness, Attitude, Intention to Use, Mobile Banking Usage, Mobile Banking

Abstract

The financial services industry, particularly the banking sector, has experienced rapid growth in line with increasing consumer demands, competitive pressures, and technological advances. The innovations resulting from these dynamics play an important role in creating services that are easier to use and provide tangible benefits to users. These two perceptions are key to driving the wider and more sustainable adoption of digital banking services. This study aims to investigate the relationship between perceived ease of use, perceived usefulness, attitude, and intention to use regarding mobile banking usage. TAM is used as the primary theory in this study. The research methodology employs a quantitative approach with purposive sampling, yielding 250 samples. The research data was analyzed using Partial Least Squares-Structural Equation Modeling (PLS-SEM) with SmartPLS 4 software. The findings show that perceived ease of use significantly influences perceived usefulness, and both contribute positively to attitude. Furthermore, perceived usefulness was found to increase intention to use, which ultimately drives mobile banking usage in the use of mobile banking services. This study contributes to the marketing literature on the adoption of digital services by users, particularly in the context of mobile banking usage. Practically, this study emphasizes the importance of feature innovation, service quality improvement, and user experience optimization to enhance customer satisfaction, engagement, and loyalty amid the increasingly competitive digital banking services market. Practically, this research emphasizes the importance of developing user-friendly features that provide tangible benefits to users, to drive adoption and build customer loyalty in the face of increasingly competitive digital banking services.

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References

Abdennebi, H. Ben. (2023). M-banking adoption from the developing countries perspective: A mediated model. Digital Business, 3(2), 100065. https://doi.org/10.1016/j.digbus.2023.100065

Al Amin, M., Arefin, M. S., Alam, M. S., & Rasul, T. F. (2022). Understanding the Predictors of Rural Customers’ Continuance Intention toward Mobile Banking Services Applications during the COVID-19 Pandemic. Journal of Global Marketing, 35(4), 324–347. https://doi.org/10.1080/08911762.2021.2018750

Almaiah, M. A., Al-Otaibi, S., Shishakly, R., Hassan, L., Lutfi, A., Alrawad, M., Qatawneh, M., & Alghanam, O. A. (2023). Investigating the Role of Perceived Risk, Perceived Security and Perceived Trust on Smart m-Banking Application Using SEM. Sustainability, 15(13), 9908. https://doi.org/10.3390/su15139908

Apit, W., Alrajawy, I., Isaac, O., Yulianto, A., & Ameen, A. (2022). E XAMINING THE I NTENTION TO U SE M OBILE B ANKING DURING P ERIOD OF COVID-19 : T ECHNOLOGY A CCEPTANCE M ODEL WITH.

Ariffin, S. K., Abd Rahman, M. F. R., Muhammad, A. M., & Zhang, Q. (2021). Understanding the consumer’s intention to use the e-wallet services. Spanish Journal of Marketing - ESIC, 25(3), 446–461. https://doi.org/10.1108/SJME-07-2021-0138

Ayyub, S., Xuhui, W., Asif, M., & Ayyub, R. M. (2020). Determinants of intention to use Islamic banking. International Journal of Islamic and Middle Eastern Finance and Management, 13(1), 147–163. https://doi.org/10.1108/IMEFM-05-2017-0135

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(January), 1–10. https://doi.org/10.3389/fpsyg.2020.621248

Chua, H. W., & Yu, Z. (2024). A systematic literature review of the acceptability of the use of Metaverse in education over 16 years. In Journal of Computers in Education (Vol. 11, Issue 2). https://doi.org/10.1007/s40692-023-00273-z

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319–339. https://doi.org/10.2307/249008

Flavián, C., Guinaliu, M., & Lu, Y. (2020). Mobile payments adoption – introducing mindfulness to better understand consumer behavior. International Journal of Bank Marketing, 38(7), 1575–1599. https://doi.org/10.1108/IJBM-01-2020-0039

Hair, J. F., Balck, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate Data Analysis. In Cengage Learning EMEA (Eight, Vol. 19, Issue 3). Annabel Ainscow. https://doi.org/10.5117/2006.019.003.007

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8

Himel, M. T. A., Ashraf, S., Bappy, T. A., Abir, M. T., Morshed, M. K., & Hossain, M. N. (2021). Users’ attitude and intention to use mobile financial services in Bangladesh: an empirical study. South Asian Journal of Marketing, 2(1), 72–96. https://doi.org/10.1108/SAJM-02-2021-0015

Ho, J. C., Wu, C. G., Lee, C. S., & Pham, T. T. T. (2020). Factors affecting the behavioral intention to adopt mobile banking: An international comparison. Technology in Society, 63(December 2019), 101360. https://doi.org/10.1016/j.techsoc.2020.101360

Hooda, A., Gupta, P., Jeyaraj, A., Giannakis, M., & Dwivedi, Y. K. (2022). The effects of trust on behavioral intention and use behavior within e-government contexts. International Journal of Information Management, 67(May), 102553. https://doi.org/10.1016/j.ijinfomgt.2022.102553

Ibrahim, M. H., Khoirunnisa, A. N., & Salsabiil, U. Z. (2022). the Intention To Use Mobile Banking During the Covid-19 Pandemic: Modification of the Utaut Model. Airlangga International Journal of Islamic Economics and Finance, 5(01), 1–17. https://doi.org/10.20473/aijief.v5i01.31449

Irimia-Diéguez, A., Velicia-Martín, F., & Aguayo-Camacho, M. (2023). Predicting Fintech Innovation Adoption: the Mediator Role of Social Norms and Attitudes. Financial Innovation, 9(1), 36. https://doi.org/10.1186/s40854-022-00434-6

Jadil, Y., Rana, N. P., & Dwivedi, Y. K. (2021). A meta-analysis of the UTAUT model in the mobile banking literature: The moderating role of sample size and culture. Journal of Business Research, 132, 354–372. https://doi.org/10.1016/j.jbusres.2021.04.052

Jebarajakirthy, C., & Shankar, A. (2021). Impact of online convenience on mobile banking adoption intention: A moderated mediation approach. Journal of Retailing and Consumer Services, 58(October 2020), 102323. https://doi.org/10.1016/j.jretconser.2020.102323

Kelly, A. E., & Palaniappan, S. (2023). Using a technology acceptance model to determine factors influencing continued usage of mobile money service transactions in Ghana. Journal of Innovation and Entrepreneurship, 12(1), 34. https://doi.org/10.1186/s13731-023-00301-3

Kim, J., & Kim, M. (2022). Intention to Use Mobile Easy Payment Services: Focusing on the Risk Perception of COVID-19. Frontiers in Psychology, 13(May). https://doi.org/10.3389/fpsyg.2022.878514

Kumar, A., Dhingra, S., Batra, V., & Purohit, H. (2020). A Framework of Mobile Banking Adoption in India. Journal of Open Innovation: Technology, Market, and Complexity, 6(2), 40. https://doi.org/10.3390/JOITMC6020040

Liu, Y., Zhao, L., & Su, Y. S. (2022). Exploring Factors of Preschool Parents’ Behavioral Intention to Use Face Recognition Technology on Campus. Frontiers in Physics, 10(April), 1–10. https://doi.org/10.3389/fphy.2022.857751

Ly, B., & Ly, R. (2022). Internet banking adoption under Technology Acceptance Model—Evidence from Cambodian users. Computers in Human Behavior Reports, 7(July), 100224. https://doi.org/10.1016/j.chbr.2022.100224

Marangunić, N., & Granić, A. (2015). Technology acceptance model: a literature review from 1986 to 2013. Universal Access in the Information Society, 14(1), 81–95. https://doi.org/10.1007/s10209-014-0348-1

Mensah, I. K., & Khan, M. K. (2024). Unified Theory of Acceptance and Use of Technology (UTAUT) Model: Factors Influencing Mobile Banking Services’ Adoption in China. SAGE Open, 14(1), 1–18. https://doi.org/10.1177/21582440241234230

Mohamad, L., Osman, Z., Mohamad, R. K., Ismail, Z., & Mohd Din, M. I. (2023). The Perceived Attitude of Bank Customers towards the Intention to Use Digital Banking in Malaysia. International Journal of Academic Research in Business and Social Sciences, 13(1), 1308–1323. https://doi.org/10.6007/IJARBSS/v13-i1/15570

Nguyen, D. N., Nguyen, D. D., & Van Nguyen, D. (2020). Distribution information safety and factors affecting the intention to use digital banking in Vietnam. Journal of Distribution Science, 18(6), 83–91. https://doi.org/10.15722/jds.18.6.202006.83

Ong, H. B., & Chong, L. L. (2023). The effect of cashless payments on the internet and mobile banking. Journal of Financial Services Marketing, 28(1), 178–188. https://doi.org/10.1057/s41264-022-00145-0

Perumal, S., Qing, Y. R., & Jaganathan, M. (2022). Factors influencing attitudes and intentions towards smart retail technology. International Journal of Data and Network Science, 6(2), 595–602. https://doi.org/10.5267/j.ijdns.2021.11.005

Phan Chung, T., Nguyen Thi Ngoc, L., Nguyen Thi My, L., & Vu Xuan, A. (2023). The Effect of Word – of – Mouth on the Adoption Behavior of Mobile Banking in Vietnam. Advances in Economics, Business and Management Research, 1, 480–500. https://doi.org/10.2991/978-94-6463-150-0_31

Purohit, S., & Arora, R. (2023). Adoption of mobile banking at the bottom of the pyramid: an emerging market perspective. International Journal of Emerging Markets, 18(1), 200–222. https://doi.org/10.1108/IJOEM-07-2020-0821

Rawwash, H., Masa’d, F., Enaizan, O., Eanizan, B., Adaileh, M. J., Saleh, A. M., & Almestarihi, R. (2020). Factors affecting Jordanian electronic banking services. Management Science Letters, 10(4), 915–922. https://doi.org/10.5267/j.msl.2019.10.004

Riptiono, S., Susanti, D. N., Rhamdhani, I. M., Anggraeni, A. I., & Prasetyo, A. (2021). Parsing religiosity and intention to use Islamic mobile banking in Indonesia. Banks and Bank Systems, 16(4), 34–44. https://doi.org/10.21511/bbs.16(4).2021.04

Safari, K., Bisimwa, A., & Buzera Armel, M. (2022). Attitudes and intentions toward internet banking in an under developed financial sector. PSU Research Review, 6(1), 39–58. https://doi.org/10.1108/PRR-03-2020-0009

Shankar, A., Jebarajakirthy, C., & Ashaduzzaman, M. (2020). How do electronic word of mouth practices contribute to mobile banking adoption? Journal of Retailing and Consumer Services, 52(August 2019), 101920. https://doi.org/10.1016/j.jretconser.2019.101920

Sharma, M., Banerjee, S., & Paul, J. (2022). Role of social media on mobile banking adoption among consumers. Technological Forecasting and Social Change, 180(May), 121720. https://doi.org/10.1016/j.techfore.2022.121720

Siagian, H., Tarigan, Z. J. H., Basana, S. R., & Basuki, R. (2022). The effect of perceived security, perceived ease of use, and perceived usefulness on consumer behavioral intention through trust in digital payment platform. International Journal of Data and Network Science, 6(3), 861–874. https://doi.org/10.5267/j.ijdns.2022.2.010

Siyal, A. W., Donghong, D., Umrani, W. A., Siyal, S., & Bhand, S. (2019). Predicting Mobile Banking Acceptance and Loyalty in Chinese Bank Customers. Sage Open, 9(2), 1–21. https://doi.org/10.1177/2158244019844084

Songkram, N., Chootongchai, S., Osuwan, H., Chuppunnarat, Y., & Songkram, N. (2023). Students’ adoption towards behavioral intention of digital learning platform. Education and Information Technologies, 28(9), 11655–11677. https://doi.org/10.1007/s10639-023-11637-4

Sultana, N., Chowdhury, R. S., & Haque, A. (2023). Gravitating towards Fintech: A study on Undergraduates using extended UTAUT model. Heliyon, 9(10), e20731. https://doi.org/10.1016/j.heliyon.2023.e20731

Takács, R., Takács, S., T Kárász, J., Horváth, Z., & Oláh, A. (2021). Exploring Coping Strategies of Different Generations of Students Starting University. Frontiers in Psychology, 12(September), 1–10. https://doi.org/10.3389/fpsyg.2021.740569

Tariq, M., Maryam, S. Z., & Shaheen, W. A. (2024). Cognitive factors and actual usage of Fintech innovation: Exploring the UTAUT framework for digital banking. Heliyon, 10(15), e35582. https://doi.org/10.1016/j.heliyon.2024.e35582

Thanabordeekij, P., Sudtasan, T., & Tanamee, D. (2020). Integrating Trust Into the Technology Acceptance Model : the Case of Mobile Banking Adoption in Myanmar. Panyapiwat, 12(3), 107–119.

Ullah, S., Kiani, U. S., Raza, B., & Mustafa, A. (2022). Consumers’ Intention to Adopt m-payment/m-banking: The Role of Their Financial Skills and Digital Literacy. Frontiers in Psychology, 13(April), 1–12. https://doi.org/10.3389/fpsyg.2022.873708

Uyob, R., Ku Bahador, K. M., & Saad, R. A. J. (2023). Integrating technology acceptance model with diffusion of innovation theory: an empirical investigation of the usage behaviour of XBRL-based Malaysia business reporting system. Accounting Research Journal, 36(4/5), 453–470. https://doi.org/10.1108/ARJ-02-2023-0063

Yamin, M. A. Y., & Abdalatif, O. A. A. (2024). Examining consumer behavior towards adoption of quick response code mobile payment systems: transforming mobile payment in the fintech industry. Humanities and Social Sciences Communications, 11(1), 675. https://doi.org/10.1057/s41599-024-03189-w

Yin, L. X., & Lin, H. C. (2022). Predictors of customers’ continuance intention of mobile banking from the perspective of the interactivity theory. Economic Research-Ekonomska Istrazivanja , 35(1), 6820–6849. https://doi.org/10.1080/1331677X.2022.2053782

Yung-Chi, C., Uguumur, E., Chen-I, H., Wen-Ling, L., & Chi-Ming, H. (2020). Factors Affecting the Internet Banking Adoption. Jurnal Ekonomi Malaysia, 54(3), 117–131. https://doi.org/10.17576/JEM-2020-5403-

Published
2026-02-24
How to Cite
Azhar, D., & Martutiningrum, D. (2026). Analysis of Key Determinants of Mobile Banking Usage: A Structural Equation Modeling (SEM) Approach Based on the Technology Acceptance Model (TAM). Indonesian Interdisciplinary Journal of Sharia Economics (IIJSE), 9(1), 3363-3374. https://doi.org/10.31538/iijse.v9i1.8670