This study investigates how the packaging image of agricultural products in livestreaming commerce influences consumers’ repurchase intentions and, on this basis, formulates effective packaging improvement strategies to enhance repurchase intention. Focusing on agricultural product packaging, we conducted an online survey of 392 consumers with livestream shopping experience and employed a combined approach of structural equation modeling (SEM) and artificial neural networks (ANNs) to analyze the effects of packaging image on repurchase intention. Starting from elements of packaging design—such as external appearance, cultural cues, imagery, and materials—we examined color schemes, typography, and illustration styles and further explored how these factors shape repurchase intention by elevating consumers’ perceived value. The findings indicate that the information-conveying functions of packaging—namely the communication of product culture, quality, and distinctive attributes—have a significant impact on repurchase intention. SEM results reveal that perceived value plays a pivotal mediating role between packaging image and repurchase intention. Complementarily, ANN analysis identifies visual appearance as the strongest predictor of repurchase intention among all packaging elements. Building on these insights, the study proposes concrete packaging design strategies, including optimizing visual appearance to highlight brand distinctiveness; distilling design symbols to narrate brand stories; and mining cultural connotations to strengthen cultural expression. This research not only verifies the importance of packaging design in boosting consumers’ repurchase intentions but also offers a practical strategic framework that can be extended to packaging design practices for other agricultural products. It provides new theoretical support and practical guidance for the field, offering a valuable reference for future research and practice.

AI-driven personalization has become an important mechanism in interactive digital marketing, yet its influence on consumers’ online purchase intention remains insufficiently understood. Situated within the institutional context of digital platform consumption and personal information protection in China, this study examines 309 consumers who have received formal legal education. Participants were recruited primarily through Chinese universities and professional legal networks. A theoretical model is developed to investigate how perceived AI-personalized recommendations and perceived AI-personalized content influence online purchase intention, with perceived value and platform trust examined as two independent mediating mechanisms and digital consumer legal literacy as a boundary condition. Structural equation modeling (SEM) and artificial neural network (ANN) analysis are jointly employed to provide both explanatory and predictive perspectives. The results show that perceived AI-personalized recommendations and perceived AI-personalized content are both positively associated with online purchase intention and are indirectly related to it through perceived value and platform trust. Digital consumer legal literacy further positively moderates the effects of perceived AI-personalized recommendation and perceived AI-personalized content on perceived value and platform trust, indicating that consumers’ understanding of digital rights, platform responsibilities, and relevant legal rules shapes how they evaluate the value and trustworthiness of algorithmic personalization. The ANN analysis further identifies the relative importance of the predictor variables and provides predictive evidence complementary to the SEM results. By integrating a dual-path mechanism of “utility evaluation–trust evaluation” with digital consumer legal literacy as an institutionally grounded boundary condition, this study advances the theoretical understanding of the relationship between AI-personalized marketing and online purchase intention within the Chinese legal and platform-governance context, while also offering practical implications for optimizing personalized services and strengthening consumer rights governance on digital platforms.