The introduction of mobile banking is essential in today’s financial sector, where technological innovation plays a critical role. To remain competitive in the current market, businesses must analyze client attitudes and perspectives, as these influence long-term demand and overall profitability. While previous studies have explored general adoption behaviors, limited research has examined how individual factors such as social influence, lifestyle compatibility, financial technology self-efficacy, and perceived usage cost affect mobile banking adoption among specific generational cohorts. This study addresses that gap by offering insights into these variables, contributing to the growing literature on mobile banking adoption, and presenting actionable recommendations for financial institutions targeting younger market segments. Using a structured questionnaire survey, data were collected from both users and non-users of mobile banking among the Gen Z population in the United States. The regression model significantly predicts mobile banking adoption, with an intercept of −0.548 (p < 0.001). Among the independent variables, perceived cost of usage has the strongest positive effect on adoption (B=0.857, β=0.722, p < 0.001), suggesting that adoption increases when mobile banking is perceived as more affordable. Social influence also has a significant positive impact (B=0.642, β=0.643, p < 0.001), indicating that peer influence is a central driver of adoption decisions. However, self-efficacy shows a significant negative relationship (B=−0.343, β=−0.339, p < 0.001), and lifestyle compatibility was found to be statistically insignificant (p=0.615). These findings suggest that reducing perceived costs, through lower fees, data bundling, or clearer communication about affordability, can directly enhance adoption among Gen Z consumers. Furthermore, leveraging peer influence via referral rewards, Partnerships with influencers, and in-app social features can increase user adoption. Since digital self-efficacy presents a barrier for some, banks should prioritize simplifying user interfaces and offering guided assistance, such as tutorials or chat-based support. Future research may employ longitudinal designs or analyze real-life transaction data for a more objective understanding of behavior. Additional variables like trust, perceived risk, and regulatory policies, not included in this study, should be integrated into future models to offer a more comprehensive analysis.
Santosh Reddy Addula (Fri,) studied this question.