Abstract
This study examines the effects of the AI Recommendation System (ARS) on users’ loyalty on e-commerce platforms in Ho Chi Minh City. Integrating the S-O-R framework and Technology Acceptance Model (TAM), the study evaluates how characteristics of ARS, including personalization, accuracy, and transparency, affect trust and satisfaction. Data from 400 Gen Z consumers were analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM). Results showed ARS significantly boosted trust and satisfaction, serving as key intermediates for long-term loyalty. This finding offers practical implications for businesses to optimize AI strategy and build sustainable customer relationships in the digital era.
Recommended Citation
Nguyen, Thanh Liem; Duong, Trung Hieu; Nguyen, Linh Thuy Trang; Nguyen, Le Van Khanh; Le, Hoai An; and Bui, Xuan Huy, "The Impacts of AI Recommendation Systems on User Loyalty in E-Commerce Platforms: Evidence from Gen Z Consumers in Ho Chi Minh City" (2026). ICEB 2026 Proceedings (Beijing, China). 108.
https://aisel.aisnet.org/iceb2026/108