Research on the impact of green advertising information on green purchase behavior in social media: SEM-ANN approach

Purpose This study aims to explore the impact of green advertising information on social media on consumers’ green purchasing behavior. It utilizes the SOR model to investigate how detailed environmental protection and product performance attributes in advertisements influence consumer behavior. The study also examines the moderating role of attribution of responsibility in enhancing these effects. Design/methodology/approach Data were collected through an online questionnaire, resulting in 541 valid responses. The data were analyzed using a hybrid approach combining structural equation modeling (SEM) and artificial neural networks (ANN) via Amos 22.0 software. Findings The results show that advertisements containing detailed environmental and product performance information significantly enhance information quality, which in turn positively impacts green purchasing behavior. Furthermore, consumers’ awareness of the environmental crisis was positively related to their green purchasing behavior. The study also finds that attribution of responsibility amplifies the positive effects of information quality and environmental crisis awareness on consumers’ unconditional green purchases. Originality/value This study introduces a hybrid SEM-ANN approach, enhancing the model’s predictive power and providing deeper insights into the non-linear relationships between green advertising, consumer awareness, and purchasing behavior. By offering a more robust analysis of these complex interactions, it contributes original insights into how green advertising messages on social media can effectively influence consumer green purchasing behaviors. The study emphasizes the importance of information quality and environmental awareness, providing a framework for companies to tailor their advertising strategies to better engage consumers with green products.