Determinants of using digital banking services:an analysis of user satisfaction through TAM and UTAUT models with PLS-SEM


The paper we proposed has as its main objective to analyze the impact on consumer habits of the phenomenon of digital transformation in the world of banking and financial services. The future of finance has a digital DNA: old and new players have started FinTech systems, that has genetically modified the financial world. The present work is mainly research carried out using statistical methods. The goal of our research is to build a model that, through an extended application and reinterpretation of the Unified Theory of Acceptance and Use of Technology (UTAUT), helps us to measure the factors affecting consumer satisfaction, retention levels towards digital banking and financial services and to investigate how these new services can impact on consumption. The study was carried out by administrating a survey and testing hypotheses with a structural equation model with PLS-PM.

DOI Code: 10.1285/i20705948v16n1p97



Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2):179–211.

Al-Msallam, S. and Alhaddad, A. (2016). Customer satisfaction and loyalty in the hotel industry: The mediating role of relationship marketing (pls approach). Journal of Research in Business and Management, 4(5):32–42.

Anderson, R. E. and Swaminathan, S. (2011). Customer satisfaction and loyalty in e-markets: A pls path modeling approach. Journal of Marketing Theory and Practice, 19(2):221–234.

Aria, M., Capaldo, G., Iorio, C., Orefice, C. I., Riccardi, M., and Siciliano, R. (2018). PLS path modeling for causal detection of project management skills: a research field in national research council in italy. Electronic Journal of Applied Statistical Analysis,


Azjen, I. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs.

Boari, G. and Nai Ruscone, M. (2015). A procedure simulating likert scale item responses. Electronic journal of applied statistical analysis, 8(3):288–297.

Cellini, P. (2015). Economia digitale: l’industria ei mercati di internet e dei nuovi media. LUISS University Press.

Chin, W. W. et al. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2):295–336.

Ciavolino, E. (2012). General distress as second order latent variable estimated through pls-pm approach. Electronic Journal of Applied Statistical Analysis, 5(3):458–464.

Ciavolino, E. and Dahlgaard, J. J. (2007). Ecsi–customer satisfaction modelling and analysis: a case study. Total Quality Management, 18(5):545–554.

Ciavolino, E. and Dahlgaard, J. J. (2009). Simultaneous equation model based on the generalized maximum entropy for studying the effect of management factors on enterprise performance. Journal of applied statistics, 36(7):801–815.

Cody-Allen, E. and Kishore, R. (2006). An extension of the utaut model with e-quality, trust, and satisfaction constructs. In Proceedings of the 2006 ACM SIGMIS CPR 21 conference on computer personnel research: Forty four years of computer personnel

research: achievements, challenges & the future, pages 82–89.

Davis, F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13:319–.

Davis, F. D., Marangunic, A., and Granic, A. (2020). TECHNOLOGY ACCEPTANCE MODEL: 30 Years of Tam. Springer.

Dijkstra, T. and Henseler, J. (2015). Consistent partial least squares path modeling. MIS Quarterly, 39.

Hair, J. F., Sarstedt, M., Pieper, T. M., and Ringle, C. M. (2012). The use of partial least squares structural equation modeling in strategic management research: a review of past practices and recommendations for future applications. Long range planning,


Henseler, J., Ringle, C. M., and 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.

Indriati, F. and Agustina, P. (2018). The influence of utaut factors on e-retention with e-satisfaction as mediating variable in e-learning. Hasanuddin Economics and Business Review, 2(1):19–33.

Leguina, A. (2015). A primer on partial least squares structural equation modeling (pls-sem). International Journal of Research & Method in Education, 38(2):220–221.

Liberati, C. and Mariani, P. (2018). Dynamic profiling through repeated surveys: a customer satisfaction study. Electronic Journal of Applied Statistical Analysis, 11(1):1–20.

Mateos-Aparicio, G. (2011). Partial least squares (pls) methods: Origins, evolution, and application to social sciences. Communications in Statistics-Theory and Methods, 40(13):2305–2317.

Merhi, M., Hone, K., and Tarhini, A. (2019). A cross-cultural study of the intention to use mobile banking between lebanese and british consumers: Extending utaut2 with

security, privacy and trust. Technology in Society, 59:101151.

Nasution, M. I., Fahmi, M., Prayogi, M. A., et al. (2020). The quality of small and medium enterprises performance using the structural equation model-part least square (sem-pls). In Journal of Physics: Conference Series, volume 1477, page 052052. IOP


Nitzl, C. (2016). The use of partial least squares structural equation modelling (pls-sem) in management accounting research: Directions for future theory development. Journal of Accounting Literature, 37:19–35.

Pelagatti, M. M., Fattore, M., and Vittadini, G. (2012). Inconsistencies of the pls-pm approach to structural equation models with formative-reflective schemes. Electronic Journal of Applied Statistical Analysis, 5(3):333–338.

R Core Team (2020). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.

Ravand, H. and Baghaei, P. (2016). Partial least squares structural equation modeling with r. Practical Assessment, Research, and Evaluation, 21(1):11.

Rogers, E. M. (2010). Diffusion of innovations. Simon and Schuster.

Venkatesh, V. and Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2):186–204.

Venkatesh, V., Morris, M. G., Davis, G. B., and Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, pages 425–478.

Venkatesh, V., Thong, J. Y., and Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, pages 157–178.

Villani, F. and Giudici, G. (2021). Fintech Expert: Contro il logorio della banca moderna. FrancoAngeli.

Wan, L., Xie, S., and Shu, A. (2020). Toward an understanding of university students’ continued intention to use moocs: When utaut model meets ttf model. SAGE Open, 10(3):2158244020941858.

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