In the current era of digital transformation, a major challenge in e-commerce is mitigating the risk of fraud in online transactions, which can erode consumer trust. This study aims to evaluate the impact of AI-driven hyper-personalization and live streaming interactions on consumer purchase intention. A quantitative approach was employed using the Partial Least Squares-Structural Equation Modeling (PLS-SEM) method. Data were collected from online shopping platform users and analyzed using SmartPLS. The results indicate that AI-driven hyper-personalization has a positive and significant influence on purchase intention; this confirms that the effectiveness of algorithms in providing relevant recommendations enhances the technology's value as perceived by consumers. Furthermore, live streaming interactions exert a more dominant positive and significant influence on purchase intention, demonstrating that social presence and visual transparency facilitated by direct interaction are crucial elements in alleviating concerns regarding fraud risks. Overall, both variables demonstrate strong predictive power regarding purchase intention. The study concludes that while AI technology forms the foundation for intelligent personalization, the human touch provided through direct interaction remains a key factor in building trust and driving sales conversions within an increasingly competitive digital marketplace.
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