Beyond Clicks and Carts: The Impact of Perceived Personalization via AI Product Recommendations on Purchase Intention in Social Commerce

This research paper investigates the impact of perceived personalization through AI-based product recommendations on consumers’ purchase intention within social commerce platforms. It explores how trust, performance expectancy, effort expectancy, social influence, and facilitating conditions mediate the relationship between personalization and behavioral intention. Data was collected via a survey of social commerce users and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings highlight that perceived personalization significantly boosts trust and behavioral intention, ultimately increasing purchase intention. These insights provide valuable implications for enhancing AI-driven recommendation strategies in the evolving landscape of social commerce.