Can generative AI features increase users' continued use intention?: The mediating role of user perceived value and user satisfaction

The emergence of generative AI has become a hot topic in academia and industry. Generative AI is also gradually becoming an interaction mode between enterprises and customers, improving customer experience and influencing their continued use intention. However, there is still uncertainty as to whether users are willing to use generative AI-driven products and services for a long time. Previous studies have mostly been based on traditional industries. How to enhance users’ continued use intention from the perspective of AI has become a widely concerned issue in academia and industry.Based on the Technology Acceptance Model (TAM) and Expectation Confirmation Theory (ECT), this study explores the impact of generative AI features on users’ continued use intention by improving the two paths of user perceived value and user satisfaction. 306 valid questionnaires were used, and SPSS 27.0 and SEM were used for data analysis and hypothesis testing. The results show that (1) generative AI features have a significant positive impact on users’ continued use intention; (2) user perceived value and user satisfaction play a mediating role in the relationship between generative AI features and users’ continued use intention. This finding improves users’ continued use intention of generative AI features, which is of great significance for understanding the marketing layout of generative AI for enterprises.