Shopping in the algorithmic age: exploring the impact of AI-driven personalization, privacy concerns, and information control as moderator on purchase intentions through shoppable videos

Abstract

In the era of digital transformation, business operations are undergoing a profound shift, characterized by the ascent of personalization and AI-driven online transactions, leveraging real-time data to provide tailored recommendations. However, this evolution raises privacy concerns among consumers. This research endeavors to scrutinize the repercussions of AI-driven personalization on consumer purchasing intentions, specifically within the context of shoppable videos in Ho Chi Minh City. Despite antecedent inquiries into personalization and privacy concerns, the existing body of research on the influence of AI-driven personalization on purchase intention remains circumscribed, prompting the present study to address this lacuna. Methodologically, a combination of qualitative approaches, involving expert discussions, and quantitative methods, utilizing a survey encompassing 301 shoppers on platforms featuring shoppable videos, has been employed. The analytical framework encompasses statistical examinations of the sample structure, a reliability analysis of the measurement scale, and linear model testing through Structural Equation Modeling (SEM). The findings reveal that factors including AI-driven personalization, perceived personalization, perceived usefulness, privacy concerns, trust, and customer interaction exert notable influences on purchasing intentions. Moreover, perceived privacy and the willingness to share information regulate the relationship between perceived usefulness and privacy concerns. Furthermore, it is asserted that customer trust concerning privacy concerns can be fortified through the exercise of customer information control. This study proffers recommendations and implications for enterprises, presenting valuable insights to inform a more discerning and strategic business approach.