Unpacking Trust in AI-Based E-Commerce: An Integrated Model of Cognitive and Psychological Drivers of Purchase Intention Among Gen Z Shopee Users

Abstract

This study investigates the cognitive and psychological factors influencing perceived trust and purchase intention in AI-powered e-commerce platforms, focusing on Shopee users from Generation Z in Indonesia. As AI technologies increasingly shape online shopping experiences, understanding how trust is developed becomes essential for driving consumer adoption. Drawing on trust theory and the Technology Readiness Index (TRI), this research proposes an integrated model incorporating cognitive variables (AI exposure, attitude toward AI, and AI accuracy perception) and psychological readiness dimensions (optimism, innovativeness, discomfort, and insecurity). Data were collected through a survey of 200 Gen Z Shopee users and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results confirm that AI exposure, attitude toward AI, AI accuracy perception, optimism, and innovativeness significantly enhance perceived trust, while discomfort and insecurity exert negative effects. Perceived trust also mediates the relationships between all cognitive and psychological predictors and purchase intention. These findings validate the central role of trust as a mechanism linking AI-based experiences with consumer behavioral intentions. Theoretically, this study contributes to AI and e-commerce literature by integrating multidimensional trust antecedents into a unified model. Practically, it offers insights for e-commerce platforms to enhance user trust by improving AI transparency, reducing user discomfort, and addressing security concerns. The results emphasize the importance of personalized, trustworthy AI-driven interactions to foster Gen Z consumer engagement and loyalty in competitive digital marketplaces.

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