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Cited by 757

The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.

Artificial intelligence in marketing: Systematic review and future research direction

Open access
Verma, Sanjeev, Sharma, Rohit, Deb, Subhamay, Maitra, Debojit·2021·International Journal of Information Management Data Insights
DOI 10.1016/j.jjimei.2020.100002
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Abstract

Disruptive technologies such as the internet of things, big data analytics, blockchain, and artificial intelligence have changed the ways businesses operate. Of all the disruptive technologies, artificial intelligence (AI) is the latest technological disruptor and holds immense marketing transformation potential. Practitioners worldwide are trying to figure out the best fit AI solutions for their marketing functions. However, a systematic literature review can highlight the importance of artificial intelligence (AI) in marketing and chart future research directions. The present study aims to offer a comprehensive review of AI in marketing using bibliometric, conceptual and intellectual network analysis of extant literature published between 1982 and 2020. A comprehensive review of one thousand five hundred and eighty papers helped to identify the scientific actors' performance like most relevant authors and most relevant sources. Furthermore, co-citation and co-occurrence analysis offered the conceptual and intellectual network. Data clustering using the Louvain algorithm helped identify research sub-themes and future research directions to expand AI in marketing.

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Show all 13 references

Research works printed but not linked: 34

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Cited by

Metadata

Authors
Verma, S., Sharma, R., Deb, S., & Maitra, D.
Venue
International Journal of Information Management Data Insights
Publisher
Elsevier BV
Published
2021-04
Volume
1
Issue
1
Pages
100002
ISSN
2667-0968 (ISSN-L)
DOI
10.1016/j.jjimei.2020.100002
OpenAlex
W3128384299
Cited by
757
References
13
FWCI
12.12
Type
journal article
Language
en
Open access
gold
Licence

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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.