AI Shopping Assistant Traits and Purchase Intention in a Distinct Cultural Context: Dual Pathways of Cognition and Affect in China

Against the backdrop of artificial intelligence (AI) reshaping the global retail ecosystem, traditional retail models face numerous challenges, and AI-powered online shopping guidance has become pivotal for retailers’ digital transformation. This study aims to explore the impact of AI online shopping guide characteristics on consumer behavioral mechanisms. Grounded in the Theory of Reasoned Action (TRA) and the Theory of Planned Behavior (TPB), a theoretical model was constructed with professionalism of guidance, interaction style, and personalized recommendations as independent variables; consumer trust and satisfaction as mediating variables; and purchase intention as the dependent variable. Empirical validation was conducted through an analysis of 475 valid questionnaires from users of mainstream Chinese e-commerce platforms. The results indicate that the professionalism of AI guides, interaction style, and personalized recommendations are all positively correlated with purchase intention. Additionally, consumer trust and satisfaction play partial mediating roles between these variables and purchase intention. This research provides strategic insights for optimizing AI-guided systems on e-commerce platforms and extends the application of traditional behavioral theories to intelligent service scenarios.