Research on the Impact Path of AI Personalized Recommendation's Relevance Experience on Consumer Online Shopping Click Intention

AI personalized recommendation technology has been deeply applied to online shopping, but there is a lack of research on consumer experience of using AI personalized recommendation with the online shopping click intention. This study focused on the impact path of consumer relevance experience in AI personalized recommendation on consumers' online click intention when shopping online. We used SPSS26.0 to analyze the consumer data from 1097 consumers’ questionnaires. We found that relevance experiences can positively promote online click intention through flow experiences. Privacy and security violations can regulate the impact of flow experience on online click intention. The stronger consumers' perception of privacy and security violations in AI personalized recommendations, the weaker the impact of flow experience on online click intention. This study provides the direction for improving AI personalized recommendation algorithms, which should promote consumers to obtain more relevant experiences, thereby promoting flow experiences, enhancing consumers' online click intention, and promoting the increase of sales on online shopping platforms.