How technology paradoxes and self-efficacy affect the resistance of facial recognition technology in online microfinance platforms: evidence from China

Abstract

This study aims to figure out the antecedents of users' resistance behavior toward facial recognition technology (FRT) in the microfinance platforms of China. We proposed a theoretical model by combining the technology paradox framework and self-efficacy theory. There were 418 valid questionnaires collected via an online survey. This study demonstrates, using structural equation modeling (SEM), that self-efficacy significantly affects technology paradoxes, anxiety, and resistance. Moreover, it suggests that the relationship between technology paradoxes and anxiety varies, and users are more concerned about the dissatisfiers of technology paradoxes (inefficiency and public). Besides, a positive correlation was found between anxiety and resistance. Finally, the results of the mediating effects test show that self-efficacy can not only directly affect resistance, but also indirectly influence it through efficiency, public, and anxiety. This study provides a deeper insight into users' resistance behaviors toward FRT and has significant implications for managers, technology designers, and future researchers.