Demystifying how emotional and cognitive resonance to AI-driven content consistency sparks customer engagement and impulse buying in short-video E-commerce

This study is the first to integrate the association of three dimensions of AI-based content recommendation's consistency (information, image and presence) and customer engagement including learning, sharing, socializing, advocacy and co-developing in short-video platforms. Drawing on Cue Consistency Theory, Resonance Theory, and SOR model, the study investigates how these consistency factors influence customer engagement and impulse buying through emotional and cognitive resonance, with the focus on the moderating roles of perceived serendipity and platform stickiness. A total of 679 responses were collected in Vietnam, and the data were analyzed using PLS-SEM. The results reveal that presence consistency positively influences emotional resonance, while information and image consistency positively impact cognitive resonance. Moreover, cognitive resonance is positively associated with impulse buying, and platform stickiness moderates the relationship between emotional resonance and customer engagement. Theoretically, this study extends cue consistency theory to AI-based recommendation contexts by incorporating emotional and cognitive resonance into a unified model. Managerially, the findings offer actionable insights for platform developers, marketers, content creators, and e-commerce sellers to fine-tune recommendation algorithm, improve their content strategies and ultimately foster stronger user experience and enhance conversion rate in an increasingly competitive digital market.