With the rapid development of artificial intelligence technology, the depth and breadth of its application have been expanding. Especially in the field of marketing, companies have tried to introduce chatbots into e-commerce, and have launched AI shopping chatbots to provide consumers with product information. Compared with traditional search-based shopping, the AI shopping chatbot has the distinct advantage of offering accurate and appropriate product information based on consumers' needs, thereby significantly reducing the costs of screening and processing massive amounts of information and creating a more efficient and convenient shopping experience. Against this backdrop, this study investigates the interaction effect of product familiarity and product information appeals on the consumer purchase intention within the context of AI shopping chatbots. Grounded in Construal Level Theory, a 2 (product familiarity: high vs. low) × 2 (product information appeals: benefit vs. attribute) between-subjects experimental design was conducted to explore the underlying mechanisms. The findings reveal the following results: (1) The interaction between product familiarity and product information appeals effects on consumers' purchase intention. For low-familiarity products, the AI shopping chatbot provides product information with benefit-based appeals (vs. attribute appeals), which enhances consumers' purchase intention. For high-familiarity products, the AI shopping chatbot provides product information with attribute-based appeals (vs. benefit appeals), which increases consumers' purchase intention. (2) Mental simulation mediates this interaction effect. Specifically, product information with attribute appeals for high-familiarity products triggers process simulation, thereby increasing consumers' purchase intention, while product information with benefit-based appeals for low-familiarity products induces outcome simulation, thereby enhancing consumers' purchase intention. These results elucidate the influencing factors and mediation mechanisms of consumers' purchase intention in the context of artificial intelligence recommendations, offering actionable insights for enterprises to optimize intelligent recommendation strategies.

Construal Level Theory, Product Familiarity, Product Information Appeals, Mental Simulation, Consumer Purchase Intention