Evaluation Of Digital Banking Application Adoption Based On The Technology Acceptance Model (Tam)

  • Naelun Nihayah Department of Management, Faculty of Business and Economics Indonesian Islamic University, Sleman, Special Region of Yogyakarta, Indonesia
  • Nursya’bani Purnama Department of Management, Faculty of Business and Economics Indonesian Islamic University, Sleman, Special Region of Yogyakarta, Indonesia
Keywords: Digital Banking , Technology Acceptance Model (TAM), Perceived usefulness, Perceived ease of use and Intention to Use.

Abstract

In this digital era, digital banking has become an integral part of the banking sector. Users decisions to adopt and use digital banking services are significantly influenced by their perceptions and attitudes toward this technology. This research aims to analyze the factors that influence users' intention to use digital banking, utilizing the Technology Acceptance Model (TAM) as the theoretical framework. The study involves 100 respondents randomly selected through the method of random sampling. Data will be collected via an online questionnaire comprising TAM variables, including perceived usefulness and perceived ease of use. The data analysis will be conducted using the Partial Least Square Structural Equation Modeling (PLS-SEM) statistical method. The findings of this research are expected to provide a deeper insight into the factors affecting the adoption of digital banking and can serve as a guide for banks and financial service providers in enhancing the acceptance of digital banking technology among users.

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References

. Abadi, HRD, Ranjbarian, B., & Zade, F.K. (2012). Investigate the customers' behavioral intention to use mobile banking based on TPB, TAM and perceived risk (A case study in Meli Bank). International Journal of Academic Research in Business and Social Sciences , 2 (10), 312.

. Ahmad, M. (2018). Review of the technology acceptance model (TAM) in internet banking and mobile banking. International Journal of Information Communication Technology and Digital Convergence , 3 (1), 23-41.

. Aldammagh, Z., Abdeljawad, R., & Obaid, T. (2021). Predicting mobile banking adoption: An integration of TAM and TBP with trust and perceived risk. Financial Internet Quarterly , 17 (3), 35-46.

. Al-Sharafi, MA, Arshah, RA, Herzallah, FA, & Alajmi, Q. (2017). The effect of perceived ease of use and usefulness on customers' intention to use online banking services: the mediating role of perceived trust. International Journal of Innovative Computing , 7 (1).

. Davis, F. D. (1989). Perceived usefulness , perceived ease of use , and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008

. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurements error. Journal of marketing research , 18 (1), 39-50.

. Ghozali, I. (2006). Structural Equations Modelling Method Alternative with Partials Least Square. Semarang: University Diponegoro.

. Hair Jr, J.F., Matthews, L.M., Matthews, R.L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107-123.

. Hair Jr. J. F., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014). Partials least squares structural equations modeling (PLS-SEM) An emerging tools in business research. European business reviews, 26(2), 106-121.

. Hartono. (2008). SPSS 16.0 Statistical and Research Data Analysis. Yogyakarta: Student Library.

. Mowen, J. C., & Minor, M. (2002). Consumer behavior. Jakarta: Erlangga , 90 .

. Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw Hill.

. Rigopoulos, G., & Askounis, D. (2007). A TAM framework to evaluate users' perception towards online electronic payments. Journal of Internet Banking and Commerce , 12 (3), 1-6.

. Safeena, R., Date, H., Hundewale, N., & Kammani, A. (2013). Combination of TAM and TPB in internet banking adoption. International Journal of Computer Theory and Engineering , 5 (1), 146.

. Sekaran, U. and Bougie, R. (2016) Research Methods for Business: A Skill- Building Approach. 7th Edition, Wiley & Sons, West Sussex.

. Sugiyono. (2017). Quantitative, Qualitative, and R&D Research Methods. Bandung: Alphabet.

. Sugiyono. (2018). Method Study Quantitative. Bandung: Alphabet.

. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the TECHNOLOGY ACCEPTANCE MODEL : four longitudinal field studies. Management Science, 46(2), 186-204.

. https://doi.org/10.1287/mnsc.46.2.186.11926

. Wang, Y.S., Wang, Y.M., Lin, H.H., & Tang, T.I. (2003). Determinants of user acceptance of Internet banking: an empirical study. International journal of service industry management , 14 (5), 501-519.

. Yahyapour, Nima. 2008. Determining Factors Affecting Intention to Adopt Banking Recommender System, Case of Iran, Thesis, Lulea University of Technology Division of Industrial Marketing and Ecommerce

. Whitley, B. E. (2002). Principles of research in behavioral science (2nd edition).

. McGraw Hill.

Published
2024-03-29
How to Cite
Nihayah, N., & Purnama, N. (2024). Evaluation Of Digital Banking Application Adoption Based On The Technology Acceptance Model (Tam). International Journal of Science, Technology & Management, 5(2), 424-430. https://doi.org/10.46729/ijstm.v5i2.1083
Section
Articles