HRMARS - This study investigates the factors influencing Chinese users’ continuance intention toward facial recognition payment (FRP) by integrating the Expectation Confirmation Model (ECM) and the Antecedents–Privacy Concerns–Outcomes (APCO) framework. A quantitative research design was adopted, and data were collected from 369 valid respondents using an online survey. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to test the proposed hypotheses. The results indicate that satisfaction is the strongest predictor of continuance intention, followed by privacy concerns, which exert a significant but weaker negative effect. Expectation confirmation significantly influences both perceived usefulness and satisfaction, while perceived usefulness further enhances satisfaction. Privacy experience increases privacy concerns, whereas privacy awareness unexpectedly reduces them. In addition, privacy concerns negatively affect both satisfaction and continuance intention. The findings reveal that users do not simply ignore privacy risks; rather, they engage in a trade-off process in which perceived benefits outweigh perceived risks. This study contributes to the literature by integrating ECM and APCO to explain post-adoption behavior and by providing empirical evidence of the privacy paradox in the context of facial recognition payment. Practical implications are offered for service providers and policymakers to balance technological convenience and privacy protection.
Fei et al. (Thu,) studied this question.