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The evolving role of artificial intelligence in marketing: A review and research agenda

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Vlačić, Božidar, Corbo, Leonardo, Costa e Silva, Susana, Dabić, Marina·2021·Journal of Business Research
DOI 10.1016/j.jbusres.2021.01.055
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Abstract

Abstract An increasing amount of research on Intelligent Systems/Artificial Intelligence (AI) in marketing has shown that AI is capable of mimicking humans and performing activities in an ‘intelligent’ manner. Considering the growing interest in AI among marketing researchers and practitioners, this review seeks to provide an overview of the trajectory of marketing and AI research fields. Building upon the review of 164 articles published in Web of Science and Scopus indexed journals, this article develops a context-specific research agenda. Our study of selected articles by means of Multiple Correspondence Analysis (MCA) procedure outlines several research avenues related to the adoption, use, and acceptance of AI technology in marketing, the role of data protection and ethics, the role of institutional support for marketing AI, as well as the revolution of the labor market and marketers’ competencies.

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Cited by

Metadata

Authors
Vlačić, B., Corbo, L., Costa e Silva, S., & Dabić, M.
Venue
Journal of Business Research
Publisher
Elsevier BV
Published
2021-05
Volume
128
Pages
187-203
ISSN
0148-2963 (ISSN-L)
DOI
10.1016/j.jbusres.2021.01.055
OpenAlex
W3133185045
Cited by
552
References
38
FWCI
30.17
Type
journal article
Language
en
Open access
green
Licence
Funders
European Commission

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.