Explaining Behavioral Intention and Actual Use of Digital Payment Systems: A Structural Equation Modeling Approach Among University Students

Digital payment systems have become increasingly important in contemporary financial environments; however, understanding the factors that drive their adoption remains a significant research challenge. This study examines the determinants of behavioral intention and actual use of digital payments by applying an extended Technology Acceptance Model (TAM) that incorporates perceived risk and trust alongside the traditional TAM constructs. Data were collected through an online survey of 154 Slovenian and international students enrolled in finance-related programs at the University of Maribor, Slovenia, and analyzed using structural equation modeling (SEM) using WarpPLS (version: 8.0). The results indicate that perceived ease of use positively affects perceived usefulness and behavioral intention, while perceived usefulness significantly increases behavioral intention. Perceived risk negatively influences trust, whereas trust positively affects behavioral intention. Furthermore, behavioral intention is the strongest predictor of actual use. All hypothesized relationships were statistically significant. The findings confirm the suitability of the extended TAM for explaining digital payment adoption in the studied group of young people and highlight the importance of usability, perceived benefits, trust, and risk perceptions in shaping digital payment behavior.