A bibliometric analysis of personalization effects on purchase intention in digital marketing
Main Article Content
Abstract
Purpose - This study examines the intellectual structure and thematic evolution of research on AI-driven personalization and consumer engagement to address the segments of literature.
Design/methodology/approach – A bibliometric analysis of 60 publications from 2022 to 2025 by using VOSviewer, keyword co-occurrence, overlay visualization, and bibliographic coupling techniques were applied to identify research clusters, temporal patterns, and influential contributions.
Findings - The findings reveal a chronological progression from early explorations and consumer trust toward personalization quality, cultural context, and AI-enabled marketing applications. The results underscore a dual trajectory: convergence around personalization quality and purchase intention, and divergence into domains psychology, culture, and ethics.
Originality/Value - The study offers theoretical contributions by mapping the evolution of personalization research and situating the influential authors for future research agenda.
Practical implications – the results highlight the need for consumer-centric, culturally adaptive, and ethically governed personalization strategies of policy makers and managers.
Social implications – Ethical AI governance and data protection are essential factors for consumer trust in digital ecosystem.
Keywords
AI-driven personalization; Bibliometric analysis; Consumer engagement; Digital marketing; Purchase intention.
Article Details
Field of Economic (JEL Codes)
M31 - Marketing - M37 - Advertising - Marketing and Advertising, O33 - Technological Change: Choices and Consequences • Diffusion Processes - Innovation • Research and Development • Technological Change • Intellectual Property Rights
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