A MECHANISM-BASED PERSPECTIVE ON THE PERSONALIZATION-PRIVACY TRADE-OFF: THE ROLES OF PERCEIVED SURVEILLANCE AND TRUST IN AI-DRIVEN E-COMMERCE

Abstract

This study examines the personalization-privacy trade-off in AI-driven e-commerce by investigating how AI-driven personalization, privacy concern, and consumer trust jointly influence online purchase decisions among Generation Z consumers. Rather than treating personalization and privacy as opposing forces, this study proposes an integrated framework that explains consumers’ behavioral responses through trust formation. Using survey data collected from 635 Generation Z consumers in Vietnam and analyzed using Structural Equation Modeling (SEM), the findings indicate that AI-driven personalization significantly enhances consumer trust and directly influences purchase decisions. Trust also exerts a strong positive effect on purchase decisions, confirming its central role in AI-enabled e-commerce environments. In addition, privacy concern significantly affects trust, highlighting the importance of consumers’ privacy evaluations in shaping behavioral outcomes. These findings suggest that consumer responses to AI-driven personalization are governed by an interconnected psychological mechanism rather than by isolated direct effects. This study contributes to the literature by extending the personalization-privacy trade-off perspective and integrating trust as a key explanatory construct in AI-driven e-commerce. The findings also provide practical implications for e-commerce firms by emphasizing the need to develop transparent and trustworthy personalization strategies that balance personalization benefits with consumers’ privacy expectations.