Artificial Intelligence Agents and Consumer Behavior: A Bibliometric Analysis of an Emerging Research Field

Recent dynamic advances in AI technologies have brought about profound transformations in the marketing paradigm and in consumer behavior and interactions. At the heart of this transformation, the relationship between AI agents and consumer behavior stands out as a timely area calling for in-depth investigation in the literature. This study constitutes a bibliometric analysis undertaken to reveal the intellectual accumulation of knowledge in this conceptual domain and to examine the evolution of the literature systematically. To this end, 438 articles indexed in the Web of Science (WoS) database between 2020 and 2026 were subjected to a comprehensive examination. The research first conducted a performance analysis to resolve the quantitative structure of the field, mapping annual publication distributions, the most prolific authors, the most highly cited studies, leading countries, and institutional collaborations. It then carried out citation, co-citation, and co-occurence analyses using science mapping techniques in order to structure the intellectual framework of the field. The findings show that the AI agent literature emerging in the context of consumer behavior is following a growth trend that is gaining momentum in both quantitative and qualitative terms. Thematically, the literature was found to concentrate on the transparency and interpretability of AI algorithms, the implications of these algorithms for consumer attitudes and behavior, the strengthening of human-AI interaction through anthropomorphic design elements, the dark side encompassing ethics, privacy, and trust, and sectoral reflections in the service industry.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-15
DOI
https://doi.org/10.5281/zenodo.23373210
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
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article

Artificial Intelligence Agents and Consumer Behavior: A Bibliometric Analysis of an Emerging Research Field

Nilay SAYAN, Ramazan KAYHAN, Busra BILGISEVEN
Zenodo (CERN European Organization for Nuclear Research)
AI in Service Interactions
article

Artificial Intelligence Agents and Consumer Behavior: A Bibliometric Analysis of an Emerging Research Field

Nilay SAYAN, Ramazan KAYHAN, Busra BILGISEVEN
article en

Abstract

Recent dynamic advances in AI technologies have brought about profound transformations in the marketing paradigm and in consumer behavior and interactions. At the heart of this transformation, the relationship between AI agents and consumer behavior stands out as a timely area calling for in-depth investigation in the literature. This study constitutes a bibliometric analysis undertaken to reveal the intellectual accumulation of knowledge in this conceptual domain and to examine the evolution of the literature systematically. To this end, 438 articles indexed in the Web of Science (WoS) database between 2020 and 2026 were subjected to a comprehensive examination. The research first conducted a performance analysis to resolve the quantitative structure of the field, mapping annual publication distributions, the most prolific authors, the most highly cited studies, leading countries, and institutional collaborations. It then carried out citation, co-citation, and co-occurence analyses using science mapping techniques in order to structure the intellectual framework of the field. The findings show that the AI agent literature emerging in the context of consumer behavior is following a growth trend that is gaining momentum in both quantitative and qualitative terms. Thematically, the literature was found to concentrate on the transparency and interpretability of AI algorithms, the implications of these algorithms for consumer attitudes and behavior, the strengthening of human-AI interaction through anthropomorphic design elements, the dark side encompassing ethics, privacy, and trust, and sectoral reflections in the service industry.

Zenodo (CERN European Organization for Nuclear Research)
Istanbul Commerce University (TR)
Openalex Percentile: Top 13%
AI in Service Interactions
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