How GenAI tools influence the purchase intention of green products through the mediating role of emotional connection: Evidence from China

In the field of green product consumption, consumers tend to seek detailed information to assess product efficacy. In recent years, the advent of Generative Artificial Intelligence (GenAI) tools has significantly streamlined consumers’ access to relevant information on green products. However, as emotional factors are decisive in purchase decision-making, existing studies that predominantly focus on rational decision-making frequently overlook this crucial emotional dimension. Addressing this gap, this study adopts the extended emotion heuristic theory to examine the impact of GenAI tools on green product purchase preferences. Using the partial least squares structural equation model, green product consumption data were collected from multiple regions including Chongqing, Guangdong, Hunan, Hubei, Shanghai, Beijing, and others, between January and March 2025. A total of 717 valid responses were analysed using SPSS 28, Amos 28, and Smart PLS 4.0. The results reveal that certain characteristics of GenAI-generated content—specifically, quality (content relevance, content accuracy), communication style (personalisation, anthropomorphism), and serendipity—positively influence purchase intention for green products. Furthermore, emotional connection plays a partial mediating role. These findings extend the application of emotion heuristic theory in the context of artificial intelligence and highlight the significant role of emotional factors in fostering consumption intentions via GenAI tools. The results offer insights for green product marketers and GenAI tool developers to enhance content quality, communication methods, and additional functions, while also informing regulatory policymaking related to GenAI tools.