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Platform Quality and AI Recommendation Quality in Building Customer Loyalty: The Mediating Role of Customer Trust and the Moderating Effect of Digital Literacy Kurnia Asni; Isthafan Najmi; Rizal Ansari; Irwan Safwadi; Agusmadi
International Journal of Science and Environment (IJSE) Vol. 6 No. 2 (2026): May 2026
Publisher : CV. Inara in Colaboration with www.stie-sampit.ac.id

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51601/ijse.v6i2.747

Abstract

The rapid advancement of Artificial Intelligence (AI) has shifted e-commerce competition toward personalized and intelligent digital experiences. This study investigates the impact of AI-enabled Platform Quality and AI Recommendation Quality on Customer Loyalty, focusing on the mediating role of Customer Trust and the moderating effect of Digital Literacy. Utilizing a quantitative explanatory approach, data were collected through an online survey from 250 Lazada users residing in Aceh Province, Indonesia. The proposed research model was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The empirical findings reveal that both AI-enabled Platform Quality and AI Recommendation Quality significantly enhance Customer Trust. Furthermore, while general platform quality directly drives Customer Loyalty, AI recommendation features require the complete mediation of Customer Trust to successfully foster long-term customer retention. Consequently, Customer Trust acts as a crucial psychological mechanism, partially mediating the effect of platform quality and fully mediating the effect of recommendation quality on customer loyalty. Interestingly, the study discovered that Digital Literacy does not moderate the relationship between AI capabilities and trust. Instead, it serves as a significant direct predictor of Customer Trust, suggesting that for the predominantly Gen-Z and Millennial user base, digital literacy operates as a foundational baseline skill rather than a differentiating factor. These findings provide theoretical advancements to the Information Systems Success Model and offer actionable managerial insights for e-commerce platforms to prioritize trust-building alongside algorithmic improvements.