Keywords: Baby-Boomer, Digital banks, Fintechs, Gen Z, Technology Acceptance Model, UTAUT2


In 2023, global banking and investment services IT spending surged to $652.1 billion, marking an 8.1% increase from 2022. Mobile banking, constituting over half of transactions, emerged as the predominant channel. Despite substantial technological investments, understanding the reasons behind mobile app usage remains crucial, particularly among the different generations. Thus, this study analyzes the perception of "baby boomer" and "Z" generations regarding the adoption of banking apps. Twenty individuals across generations with varying app familiarity participated in qualitative interviews. The data was analyzed using the Content Analysis technique. Our findings suggest that users value the convenience of app-based transactions, reducing reliance on physical banks. Generation Z favors digital banks, while baby boomers trust traditional ones, citing concerns like connectivity issues, tech knowledge limitations, and cost-benefit considerations. Non-using Generation Z individuals cite age, maturity, security concerns, and lack of social influence as reasons. Apprehensions about using other apps prevail among baby boomer users, echoing non-users' fears, emphasizing the significant role of fear in decision-making, possibly linked to reported digital data theft and virtual scams.

Author Biographies

Danielle Rocha Teodoro, Centro Universitário do Sul de Minas - UNISMG

Bachelor's degree in Information Systems from Centro Universiário do Sul de Minas - UNISMG.

Rodrigo Franklin Frogeri, Centro Universitário do Sul de Minas - UNISMG

Doctor in Information Systems and Knowledge Management. 


Addy, M. N., Addo, E. T., Kwofie, T. E., & Yartey, J. E. (n.d.). Predicting the adoption of e-procurement in construction project delivery in Sub-Saharan Africa: an application of UTAUT2. CONSTRUCTION INNOVATION-ENGLAND.

Alves-Mazzotti, A. J., & Gewandsznajder, F. (2004). O método nas ciências naturais e sociais: pesquisas quantitativas e qualitativas (2nd ed.). PIONEIRA Thompson Learning.

BACEN. (2021). Fintechs. Banco Central Do Brasil.

Bardin, L. (2013). L’analyse de contenu. PUF.

Chauhan, S., Akhtar, A., & Gupta, A. (2022). Customer experience in digital banking: a review and future research directions. International Journal of Quality and Service Sciences, 14(2), 311–348.

Creswell, J. W. (2010). Projeto de Pesquisa: Métodos Qualitativo, Quantitativo e Misto. Artmed.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989a). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 27(3), 319–340.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989b). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), 982–1003.

Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019). Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a Revised Theoretical Model. Information Systems Frontiers, 21(3), 719–734.

FEBRABAN. (2019). Aplicativos de bancos evoluem e ganham novas funções. FEBRABAN Tech.

FEBRABAN. (2023). Brasileiro aumenta em 30% suas transações bancárias em 2022, e oito em cada dez operações são digitais. FEBRABAN Tech.

Feliciano, A. D. P., & Frogeri, R. F. (2018). A Dinâmica de Uso dos Aplicativos Móveis Bancários: uma análise sob a perspectiva da população idosa. Revista de Sistemas e Computação, 8(2), 1–14.

Feliciano, A. D. P., Frogeri, R. F., & Prado, L. Á. (2018). A ACEITAÇÃO DOS APLICATIVOS MÓVEIS BANCÁRIOS NO BRASIL: uma análise da utilidade percebida e facilidade de uso. INTERAÇÃO, 20(1), 206–231.

Gama Junior, F. da C., Frogeri, R. F., Piurcosky, F. P., & Carvalho, E. G. (2024). ACCEPTANCE OF INFORMATION SYSTEMS DURING COVID-19: A COMPARATIVE STUDY BETWEEN FEDERAL AND PRIVATE EDUCATIONAL INSTITUTIONS. Mythos (Interdisciplinary), 21(1), 1–17.

Gartner. (2023). Gartner Forecasts Worldwide Banking and Investment Services IT Spending to Reach $652 Billion in 2023. Current Economic Uncertainty Driving Organizations to Invest in Agile IT Infrastructure.

Grani, A., & Maranguni, N. (2019). Technology acceptance model in educational context: A systematic literature review. British Journal of Educational Technology, 50(5), 2572–2593.

Hameed, S., & Nigam, A. (2023). Exploring India’s Generation Z perspective on AI enabled internet banking services. Foresight, 25(2), 287–302.

Holden, R. J., & Karsh, B. T. (2010). The Technology Acceptance Model: Its past and its future in health care. Journal of Biomedical Informatics, 43(1), 159–172.

Karim, M. W., Ulfy, M. A., & Huda, M. N. (2020). Determining intention to use smartphone banking application among millennial cohort in Malaysia. International Journal of Management and Sustainability, 9(1), 43–53.

King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information and Management, 43(6), 740–755.

Kitsios, F., Giatsidis, I., & Kamariotou, M. (2021). Digital transformation and strategy in the banking sector: Evaluating the acceptance rate of e-services. Journal of Open Innovation: Technology, Market, and Complexity, 7(3), 204.

Koenaite, M., Maziriri, E., & Chuchu, T. (2021). Attitudes Towards Utilising Mobile Banking Applications Among Generation Z Consumers in South Africa. Journal of Business and Management Review, 2(6), 417–438.

Kopplin, C. S., Gantert, T. M., & Maier, J. V. (2022). Acceptance of matchmaking tools in coworking spaces: an extended perspective. Review of Managerial Science, 16(6), 1911–1943.

Lisana, L. (2024). Understanding the key drivers in using mobile payment among Generation Z. Journal of Science and Technology Policy Management, 15(1), 122–141.

Ma, Q., & Liu, L. (2004). The Technology Acceptance Model: A Meta-Analysis of Empirical Findings. Journal of Organizational and End User Computing (JOEUC), 16(1), 59–72.

Maria, H. D. S., Frogeri, R. F., Piurcosky, F. P., & Prado, L. Á. (2021). Remotely Piloted Aircraft?: Analysis of the Deployment in Aeronautical Accident Investigation Bureau. Journal of Aerospace Technology and Management (JATM), 13(e0121), 1–21.

Matar, A., & Alkhawaldeh, A. M. (2022). Adoption of electronic cards using Wi-Fi platform services by clients of banking sector during COVID-19 pandemic. International Journal of Engineering Business Management, 14.

Melnyk, V. (2023). Transforming the nature of trust between banks and young clients: from traditional to digital banking. Qualitative Research in Financial Markets.

Minayo, M. C. de S. (2012). Análise qualitativa: teoria, passos e fidedignidade. Ciência & Saúde Coletiva, 17(3), 621–626.

Myers, M. D. (2013). Qualitative research in business and management. SAGE Publications Ltd.

Myers, M. D., & Newman, M. (2007). The qualitative interview in IS research: Examining the craft. Information and Organization, 17(1), 2–26.

Rodrigues, L. F., Oliveira, A., & Rodrigues, H. (2023). e-Banking Usage by Generations X, Y, and Z. Application OfEmerging Technologies, 115, 234–246.

Schomakers, E.-M., Lidynia, C., Vervier, L. S., Valdez, A. C., & Ziefle, M. (2022). Applying an Extended UTAUT2 Model to Explain User Acceptance of Lifestyle and Therapy Mobile Health Apps: Survey Study. JMIR MHealth and UHealth, 10(1).

Srivastava, S., Mohta, A., & Shunmugasundaram, V. (2024). Adoption of digital payment FinTech service by Gen Y and Gen Z users: evidence from India. Digital Policy, Regulation and Governance , 26(1), 95–117.

Suo, W. J., Goi, C. L., Goi, M. T., & Sim, A. K. S. (2022). Factors Influencing Behavioural Intention to Adopt the QR-Code Payment: Extending UTAUT2 Model. INTERNATIONAL JOURNAL OF ASIAN BUSINESS AND INFORMATION MANAGEMENT, 13(2).

Szajna, B. (1996). Empirical Evaluation of the Revised Technology Acceptance Model. Management Science, 42(1), 85–92.

Turner, M., Kitchenham, B., Brereton, P., Charters, S., & Budgen, D. (2010). Does the technology acceptance model predict actual use? A systematic literature review. Information and Software Technology, 52(5), 463–479.

Urquhart, C. (2012). Grounded Theory for Qualitative Research: A Practical Quide. Sage.

Venkatesh, V., & Davis, F. D. (2000). 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., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly: Management Information Systems, 27(3), 425–478.

Venkatesh, V., Thong, J., & Xu, X. (2012). Consumer acceptance and user of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178.

Wewege, L., Lee, J., & C. Thomsett, M. (2020). Disruptions and Digital Banking Trends. Journal of Applied Finance & Banking, 10(6), 15–56.


Windasari, N. A., Kusumawati, N., Larasati, N., & Amelia, R. P. (2022). Digital-only banking experience: Insights from gen Y and gen Z. Journal of Innovation and Knowledge, 7(2), 100170.

Zmoginski, F. (2019). A geração que desafia os bancos. FEBRABAN.

How to Cite
Teodoro , D. R., & Frogeri, R. F. (2024). BRIDGING THE GENERATION GAP. Revista Mythos, 21(1), 48-70.
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