How Perceived Value Drives Usage Intention of AI Digital Human Advisors in Digital Finance
Yishu Tang, Hosung Son
Abstract
This study investigates how perceived value influences user satisfaction and usage intention toward AI Digital Human Advisors in digital finance, drawing on the Stimulus–Organism–Response (S–O–R) framework. Perceived value is conceptualized as comprising functional, cognitive, and emotional dimensions, reflecting users’ utilitarian, intellectual, and affective evaluations of AI advisors. To empirically test the proposed model, a structured questionnaire survey was conducted with 524 adult users of digital financial applications in mainland China, and the data were analyzed using structural equation modeling (SEM). The results reveal that cognitive and emotional value significantly enhance both satisfaction and usage intention, whereas functional value shows no significant effect. Satisfaction fully mediates the effect of cognitive value and partially mediates that of emotional value. Moreover, switching barriers negatively moderate the satisfaction–intention link, indicating that high friction weakens the behavioral impact of satisfaction. The findings extend perceived value theory to AI-mediated financial contexts by demonstrating that emotional and cognitive engagement—rather than functional efficiency—drives sustained behavioral intention. Practically, the study highlights the importance of designing emotionally intelligent and cognitively transparent AI advisors. As the data were collected from urban users in China, where digital finance is relatively advanced, future research should validate these findings in other cultural and institutional contexts.