THE IMPACT OF PRIVACY CALCULUS AND TRUST ON USER INFORMATION PARTICIPATION BEHAVIOR IN AI-BASED MEDICAL CONSULTATION-THE MODERATING ROLE OF GENDER

Artificial intelligence (AI)-based medical consultation, an emerging health service delivered on digital platforms, has been widely applied on major medical platforms. How to encourage users' information participation is a key issue for AI-based medical consultation platforms to succeed. A research framework is developed which applies the privacy calculus theory and trust and includes gender differences to the prediction of information participation behavior in the medical consultation context. The suggested hypotheses are confirmed using a structural equation modeling approach and a multi-group investigation employing empirical data from 470 users. The empirical results indicate that there are significant positive relationships between perceived information control and perceived benefits, between perceived benefits and trust, and between trust and information participation behavior, while negative relationships are found between perceived information control and perceived risks, between perceived risks and perceived benefits/trust. Further, the relationships between privacy calculus and trust are contingent on gender. Specifically, females are more sensitive to perceived risks, whereas males pay more attention to perceived benefits. Theoretical, practical implications and limitations are also discussed.