Perceived Risk and Interaction of Generative AI User Experience on Continuance Intention: The Mediating Effect of Flow

초록

With the rapid diffusion of Generative Artificial Intelligence driven by advances in information and communication technology, this study empirically examines the effects of perceived risk and interaction in the generative AI user experience on continuous use intention, focusing on the mediating role of flow. Survey data were collected from university students who frequently use ChatGPT, and structural equation modeling (SEM) was applied. The results show that perceived risk has a significant negative effect on flow, while its direct effect on continuous use intention is not significant; instead, an indirect effect through flow was confirmed. Interaction has significant positive effects on both flow and continuous use intention, and flow positively influences continuous use intention, confirming its mediating role. These findings provide practical implications for the effective utilization of generative AI services and for developing user-centered strategies and policies. Furthermore, this study theoretically contributes to the existing literature by identifying the black box mechanism of how cognitive absorption bridges the gap between potential risks and actual retention. Ultimately, these insights establish a solid foundation for future research to investigate diverse user demographics and evolving functional updates in generative AI ecosystems.

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