A bibliometric approach to the evolution of artificial intelligence in digital marketing

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dc.contributor.authorNalbant, Kemal Gokhan
dc.contributor.authorAydin, Sevgi
dc.date.accessioned2025-03-09T10:48:51Z
dc.date.available2025-03-09T10:48:51Z
dc.date.issued2025
dc.departmentİstanbul Beykent Üniversitesi
dc.description.abstractPurpose-This research aims to examine the dynamic relationship between digital marketing and AI. This study used bibliometric analysis to investigate the significance of artificial intelligence in digital marketing research. The study was conducted using the WOS database, which includes word cloud analysis, keyword analysis, citation analysis, and publication analysis. Design/methodology/approach-The present inquiry utilized the Web of Science database to gather scholarly publications that were published between 2000 and 2023. A search was performed using the Boolean operator AND to retrieve pertinent publications that contain both the terms artificial intelligence and digital marketing in the first query. A total of 96 publications were found during the search. The search terms were expanded, and the content analysis was enhanced to include studies from 1993 to 2023, resulting in 521 studies for in-depth analysis in the second query. The acquired papers were subjected to bibliometric analysis using VOSviewer software (version 1.6.20). Findings-The phrase digital marketing had the highest frequency, with a cumulative link strength of 94. This keyword exhibited a strong association with the phrase artificial intelligence. The WOS database shows a steady increase in publications on digital marketing and AI since 2017 for the first query. In 2017, there were about two publications, which grew to around 26 by 2021. For the second query, the number of publications on digital marketing and AI also increased steadily. In 1993, there was one publication, rising to about 102 by 2022. Originality/value-The study conducts a comprehensive bibliometric analysis by examining publications that were released in the Web of Science database from 2000 to 2023 for the first query and from 1993 to 2023 for the second query. This research analyzes the progress and current status of corporate management and marketing techniques during the past twenty-four years. In addition, this approach enhances the originality of the second inquiry by providing a comprehensive analysis of studies spanning nearly 3 decades, offering unique insights into the evolution of the field. The research centers on the impact that AI has exerted on these sectors. Moreover, the results of this study emphasize the significance of the increasing number of scientific studies that intersect AI and digital marketing.
dc.identifier.doi10.1108/IMR-04-2024-0132
dc.identifier.issn0265-1335
dc.identifier.issn1758-6763
dc.identifier.scopus2-s2.0-85217867636
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1108/IMR-04-2024-0132
dc.identifier.urihttps://hdl.handle.net/20.500.12662/4674
dc.identifier.wosWOS:001421607900001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherEmerald Group Publishing Ltd
dc.relation.ispartofInternational Marketing Review
dc.relation.publicationcategoryDiğer
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250310
dc.subjectArtificial intelligence
dc.subjectDigital marketing
dc.subjectBibliometric analysis
dc.subjectWeb of science
dc.subjectVOSviewer
dc.titleA bibliometric approach to the evolution of artificial intelligence in digital marketing
dc.typeReview

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