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AI-driven personalization and impulsive buying in e-commerce: a bibliometric analysis of research trends among
Alain Monica George1, Rupa R1, Shinta Sebastian1
1Research and PG Department of Commerce, Marian College Kuttikkanam Autonomous, Kuttikkanam, India.
Objectives:
The research is intended to chart the research space of artificial intelligence-based personalization and impulsive purchasing behavior in e-commerce, with a particular emphasis on Millennials and Generation Z. It aims to determine the trends of publications, the main themes, the sources of influence, the patterns of collaboration, as well as the new directions of the research.
Methods:
650 articles of Web of Science and 48 articles of Scopus were analyzed by Biblioshiny. Performance analysis, co-occurrence network analysis, thematic mapping, and source and authorship analysis were included in the analysis.
Findings:
The results indicate a definite increase in the number of publications over the past few years, which indicates growing interest among scholars in the AI and consumer behavior. In both data sets, the theme of artificial intelligence, technology adoption, and consumer behavior is predominant in the field, with trust, behavioral intention, and adoption proving to be key supporting concepts. The analysis of co-occurrence revealed the significant clusters with the focus on AI and technological improvement, consumer behavior, and engagement. Nonetheless, the direct correlation between AI-driven personalization and impulsive buying behavior is underrepresented, and the focus on Millennials and Generation Z has not been explicitly addressed yet.
Conclusion:
The study concludes that research in this area is currently increasing at an extremely fast rate, however, it remains in pieces and is still lacking a fully integrated conceptual framework. Though the literature covers AI and its impact on consumer behavior in a comprehensive manner, the behavioral consequence of impulsive buying by younger generations has been poorly covered in the literature.
Implications:
The results indicate that future research should address more directly how AI personalization processes relate to impulsive buying behaviors and should also investigate how generational differences influence the results. The research also provides valuable information to the researchers and practitioners with interest in the role of AI in digital commerce and consumer decision-making.
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