Should I scan my face? The influence of perceived value and trust on Chinese users' intention to use facial recognition payment. (March 2023) - Hu, Bo; Liu, Yu-li; Yan, Wenjia
Highlights: We build a usage intention model of facial recognition payment from the perspectives of perceived value and trust. Perceived convenience has a positive impact while financial risk and privacy risk have a negative impact on perceived value. Influences of risk factors far outweigh those of benefit factors on trust toward FRP. Perceived sensitivity of facial information has a significant moderating effect on perceived value. Abstract: While China has seen the widespread adoption of facial recognition payment, concerns over the potential risks impede the further growth of user acceptance. Drawing on the perspectives of perceived value and trust, we developed a research model to explore how the Chinese users' trade-off between perceived benefits (perceived convenience and perceived novelty) and perceived risks (perceived privacy risk and perceived financial risk) influences their usage intention. Based on survey data from 1, 200 Chinese mobile payment users, this study uses structural equation modeling to examine the hypotheses. Our results show that perceived convenience positively influences perceived value, while privacy risk and financial risk negatively influence perceived value and trust. Although perceived novelty has no significant effect on perceived value and trust, perceived value positively influences trust, and both of them have a positive effect on the intention to use. Furthermore, our moderation analysis indicates that the influence of perceived value on the intention to use is stronger among users who consider facial information to be more sensitive. The theoretical implications for research as well as the practical implications for practitioners are also discussed.