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Based on the cognitive appraisal theory, this study extends the AI device use acceptance (AIDUA) model to explain users’ continued usage intention of GAI. The extended AIDUA model integrates individual-technology fit and task-technology fit as predictors of users’ expected values of GAI. A total of 704 valid questionnaires were collected through the “Wenjuanxing” survey platform. Structural equation modeling (SEM) and artificial neural network (ANN) were used to explore the linear and nonlinear relationships among variables. Our study confirmed the positive influence mechanisms of social influence, anthropomorphism, hedonic motivation, individual-technology fit, and task-technology fit on performance expectancy and effort expectancy. We further explored users’ continued usage intention of GAI by constructing a dynamic transmission mechanism of “usage intention—usage behavior—continued usage intention,” suggesting the positive moderating role of flow experience between usage behavior and continued usage intention.
Wang et al. (Wed,) studied this question.