A META-ANALYSIS OF PERSONALIZATION EFFECTS ON PURCHASE INTENTION IN DIGITAL MARKETING
Main Article Content
Abstract
This study examines the intellectual structure and thematic evolution of research on AI-driven personalization and consumer engagement through a bibliometric analysis of publications from 2022 to 2025. Using VOSviewer, keyword co-occurrence, overlay visualization, and bibliographic coupling techniques were applied to identify research clusters, temporal patterns, and influential contributions. The findings reveal a chronological progression from early explorations of digital personalization and consumer trust toward recent emphases on personalization quality, cultural context, and AI-enabled marketing applications. Bibliographic coupling highlights the central role of influential authors such as Guo (2023) and Lim (2024), with transitional figures like Prodanova (2024) bridging distinct intellectual clusters. The results underscore a dual trajectory in the literature: convergence around core constructs such as personalization quality and purchase intention, and divergence into interdisciplinary domains including psychology, culture, and ethics. The study offers theoretical contributions by mapping the evolution of personalization research and practical implications by highlighting the need for consumer-centric, culturally adaptive, and ethically governed personalization strategies. Limitations related to database coverage, reliance on citation metrics, and the dynamic nature of the field are acknowledged, and avenues for future research are proposed.
Keywords
AI-driven personalization; consumer engagement; digital marketing; meta-analysis; purchase intention
Article Details
Field of Economic (JEL Codes)
M31 - Marketing - Marketing and Advertising
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