The Utilization of AI Technology and Personalization Algorithms on the Phenomenon of Research Shopping in Female Consumer Behavior in the Digital Era

Abstract

The rapid development of artificial intelligence (AI) technology and personalization algorithms has fundamentally transformed the landscape of e-commerce and digital retail, particularly influencing the shopping behavior of female consumers. This study examines the utilization of AI-driven personalization algorithms and their impact on the research shopping phenomenon among female consumers in the digital era. Research shopping, defined as the behavior of searching for product information online while making the final purchase decision offline or across multiple platforms, has become increasingly prevalent as digital touchpoints multiply. This research employs a quantitative approach with a survey method involving 250 female respondents aged 18–45 who actively use e-commerce platforms in Indonesia. Data were collected using structured questionnaires and analyzed using Structural Equation Modeling (SEM). The findings reveal that AI personalization algorithms significantly influence female consumer decision-making processes, fostering research shopping tendencies through targeted recommendations, dynamic pricing, and adaptive content delivery. Furthermore, the study identifies trust, perceived usefulness, and digital literacy as key mediating variables between AI technology utilization and research shopping behavior. These results contribute to the growing body of literature on AI-driven consumer behavior and offer practical implications for digital marketers and e-commerce platform developers seeking to optimize user experience for female consumers.