The paradox of technology quality and ethical concerns in building trust and behavioral intention in the AI-enabled face recognition payment

Artificial intelligence (AI) characterizes a new generation of global payment solutions, while the challenge lies in understanding how to effectively influence users’ behavioral intention toward AI-enabled face recognition payment within the business ethics domain. Drawing upon trust theory and trust transfer lens, our study introduces a model aimed at examining the counteracting influences of technology quality and ethical concerns on user behavioral intention through the mediating effect of trust. Specifically, we delineate two distinct forms of trust: trust in AI-enabled face recognition technology and trust in AI-enabled face recognition payment. An empirical survey was conducted, gathering 348 valid questionnaires from users of AI-enabled face recognition payment. The empirical results demonstrate a noteworthy interaction effect between technology quality and ethical concerns on trust and behavioral intention toward AI-enabled face recognition payment, indicating a conspicuous paradox of these two factors. Our findings also reveal a trust transfer mechanism between the two trust targets in the context of AI-enabled face recognition payment, which in turn affects users’ behavioral intention. The findings of this paper make a valuable contribution to the extant mobile payment literature and enhance our understanding regarding the dual role of AI technology in shaping trust and behavioral intentions in AI-enabled face recognition payment.