<![CDATA[Purpose – This study examines how human–AI collaborative, AI interaction transparency, and perceived personalization influence sustainable purchase intention through customer trust and perceived message relevance in AI-enabled e-commerce. Design/methodology/approach – This study employs a quantitative explanatory approach using Partial Least Squares Structural Equation Modeling (PLS-SEM). Data were collected from 180 e-commerce consumers in Bali, Indonesia, using purposive sampling. A structured questionnaire was administered, and the data were analyzed using SmartPLS. Finding/Results – The findings reveal that human–AI collaborative and AI interaction transparency enhance customer trust, whereas perceived personalization does not. Perceived personalization significantly improves perceived message relevance, which, together with customer trust, strengthens sustainable purchase intention. Further analysis shows that AI interaction transparency also has a direct effect on sustainable purchase intention, while human–AI collaborative and perceived personalization do not. The mediation results identify two mechanisms: a trust pathway involving human–AI collaborative and AI interaction transparency, and a relevance pathway involving perceived personalization. Originality/Value – This study refines the application of the Stimulus–Organism–Response (S–O–R) framework by identifying two psychological pathways underlying sustainable purchase intention in AI-enabled e-commerce: a trust pathway driven by human–AI collaborative and AI interaction transparency, and a relevance pathway driven by perceived personalization. The findings highlight the importance of trustworthy interactions and personally relevant information in AI-enabled sustainable marketing.]]>
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