Data-Driven Governance of Digital Consumption: Behavioral Analytics of Generation Z TikTok Users

In the era of Smart Society, social commerce platforms utilize aggressive algorithmic stimuli like flash sales to drive digital consumption. However, the governance of these intelligent ecosystems requires a deep understanding of how such stimuli interact with consumer psychology to ensure long-term sustainability. This study aims to provide behavioral insights into the impact of flash sales on the impulsive buying behavior of Generation Z, while examining the moderating roles of Fear of Missing Out (FoMO) and self-control. Utilizing a quantitative data-driven approach, data were collected from 100 TikTok Shop users in Greater Jakarta. The research framework applies the Stimulus-Organism-Response (S-O-R) theory, analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM) as a governance analytics tool. The findings reveal that flash sales, FoMO, and self-control do not significantly influence impulsive buying, indicating a state of promotion fatigue and consumer habituation. Despite the lack of significant paths, the model demonstrates substantial predictive relevance (R2 = 0.808$; Q2 = 0.699$). These results contribute to evidence-based policymaking by highlighting the "novelty of insignificance" in mature digital markets. The study underscores the necessity for smart governance to transition from urgency-based tactics toward transparent marketing strategies that align with SDG 12 (Responsible Consumption and Production). These behavioral insights are vital for developing adaptive policy frameworks that support sustainable human behavior within the evolving digital economy.