Algorithm-driven personalization, content exposure, and live commerce: The roles of engagement and trust in Gen Z impulse buying on TikTok Shop

Type of the article: Research ArticleAbstractThis research aims to investigate the impact of algorithmic personalization, exposure to content, social interaction and live commerce experiences on impulse buying among Generation Z users of TikTok Shop in Indonesia with real-time engagement acting as a mediator and perceived trust acting as a moderator. This study relates directly to the increasing influence of recommendation algorithms and interactive live commerce on consumer behavior and specifically on Generation Z who are digital natives and very often make impulse purchases. A quantitative survey was conducted using purposive sampling to collect data from valid participants aged 17-27 living in Indonesia and actively using TikTok Shop between January and April 2025. Ethical principles were applied, including voluntary participation, informed consent, anonymity, and confidentiality in relation to the use of data. 576 data were analyzed using Structural Equation Modelling and Partial Least Squares (SEM-PLS). Findings reveal that algorithmic personalization (β = 0.069; p = 0.048); content exposure (β = 0.881; p lt; 0.001); and social interaction (β = 0.088; p = 0.017) have significant positive influence on impulse buying. All three of these relationships are mediated by real-time engagement with small but significant (β = 0.011; p = 0.037) effect size. The relationship between perceived trust and live commerce experience moderates the effects of live commerce experience and enhances the strength of the effect; however, the moderating effect of perceived trust on algorithmic personalization and social interaction was not as strong. The results of this research indicate that the main motivating factors of impulse buying in social commerce are based on algorithmic recommendations through personalization, social connection, and live commerce.