RESOLVING THE PERSONALIZATION-TRUST INCONSISTENCY IN DIGITAL ADVERTISING: THE MISSING AFFECTIVE LINK OF EMOTIONAL SUPPORT ON TIKTOK SHOP

Abstract

This study examines how perceived personalization in TikTok Shop ads influences trust through the mediating role of perceived emotional support, grounded in Affective Events Theory (AET). Despite the widespread adoption of AI-driven personalization, empirical findings on its influence on consumer trust remain inconsistent, as prior research has largely overlooked affective mechanisms, focusing instead on cognitive pathways such as relevance and usefulness. This study addresses this gap by proposing that perceived personalization functions as an affective event that triggers positive emotional reactions specifically perceived emotional support which subsequently builds consumer trust. A quantitative survey was conducted with 270 active TikTok Shop users in Indonesia who had been exposed to personalized advertisements, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results demonstrate that perceived personalization has a strong positive effect on perceived emotional support, which in turn significantly influences trust. Furthermore, perceived emotional support partially mediates the relationship between perceived personalization and trust, with a variance accounted for (VAF) of 44.6%, indicating that both affective and cognitive processes contribute to trust formation. Theoretically, this study extends AET into AI-based digital marketing and resolves the inconsistent personalization-trust findings by identifying emotional support as the missing affective link. Practically, the findings emphasize that marketers should prioritize creating emotional support through personalization strategies, as content that makes consumers feel understood and cared for is more effective in building trust. This study contributes to the growing literature on AI personalization in social commerce contexts, particularly in developing countries.