THE IMPACT OF AI-DRIVEN FEATURES ON CUSTOMER SATISFACTION ON TIKTOK IN VIETNAM: EXPLORING THE MODERATING EFFECT OF PRIVACY CONCERNS

In the context of rapidly advancing technologies, this study delves into the intricate dynamics of AI-driven features, focusing on the balance between AI features and privacy concerns on TikTok in Vietnam. Grounded in Social Support Theory, the research develops a comprehensive framework to examine the impact of AI-driven features on customer satisfaction and experience, with privacy concerns as a moderating variable. Using a positivist research paradigm, crosssectional data were collected from 348 TikTok users in Vietnam through an online survey employing purposive-convenience sampling. Structural Equation Modeling (SEM) was applied to analyze the relationships among AI driven features, customer experience, and satisfaction. Results highlight the pivotal role of personalized algorithms in enhancing user satisfaction, while privacy concerns exert a nuanced but statistically insignificant moderating influence. Findings underscore the need to strike a balance between AI-driven features and privacy to foster trust and satisfaction in AI-powered platforms. The study concludes with implications for businesses and platform developers, suggesting further research to address contextual and methodological limitations for a deeper understanding of factors in AI-driven environments.