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.

This study aims to identify the key destination-related factors associated with tourists’ revisit behavior in peri-urban rural areas within Chinese metropolitan regions in the context of short-video marketing, and to reveal the structural relationships and hierarchical characteristics among these factors. First, the LDA topic model was employed to conduct text mining on authentic tourist-generated comments posted on Douyin, through which the core factors related to revisit behavior were identified and conceptually standardized based on tourists’ expressions. Building on this process, 153 experts in relevant fields were invited to evaluate the direction and strength of the relationships among these factors. An integrated DEMATEL–ISM–MICMAC approach was then applied to analyze their causal attributes, hierarchical structure, and systemic roles. The results indicate that the identified factors do not operate independently but instead form a multilayered structure with clear hierarchical characteristics. Among them, rural visual imagery, escape-oriented experience, rural lifestyle experience, and rural industry integration occupy deeper structural levels and exert relatively strong structural influences on factors located at intermediate and surface levels. The findings further suggest that the sustained attractiveness of rural tourism destinations in metropolitan regions cannot rely solely on short-video exposure or isolated “internet-famous” attractions; rather, it requires coordinated alignment among digital communication content, rural industries, lifestyle experiences, and tourism supply. By integrating tourist-generated content, natural language processing, and expert-based structural assessment, this study extends research on short-video tourism marketing from a systems perspective and provides practical insights for peri-urban rural destinations in Chinese metropolitan regions seeking to optimize the structural configuration of tourism resources, products and services, and marketing communication.