Bibliometric Analysis of Publications in Artificial Intelligence and Marketing

Year 2023, Volume: 31 Issue: 56, 369 - 388, 28.04.2023

Gül Ekinci , Fatma Gül Bilginer Özsaatcı

https://doi.org/10.17233/sosyoekonomi.2023.02.17

Cited By: 2

Abstract

This study examines the research made in artificial intelligence and marketing with the bibliometric analysis method. In the Scopus database between 1984 and 2022, the studies with the phrase “artificial intelligence*, marketing*” were searched, and 447 studies were found in the marketing field. The total number of references of the studies published in 236 different sources is 24436, the total number of authors is 1092, and the collaboration index is 2.84. The USA has the most studies, citations, and cooperation. It has been determined that business intelligence and information management come to the fore.

Keywords

Artificial Intelligence, Marketing, Bibliometric Analysis, Systematic Literature Review, Scopus

Yapay Zekâ ve Pazarlama Alanındaki Yayınların Bibliyometrik Analizi

Abstract

Bu çalışmanın amacı yapay zekâ ve pazarlama alanında yapılmış araştırmaları bibliyometrik analiz yöntemi ile incelemektir. Scopus veri tabanında 1984-2022 yılları arasındaki yayınlarda “artificial intelligence*, marketing*” ifadeleri geçen çalışmalar taratılmış ve 447 adet çalışma bulunmuştur. 236 farklı kaynakta yayınlanan çalışmaların toplam referans sayısı 24436, toplam yazar sayısı 1092ve iş birliği endeksi 2.84’tür. En fazla çalışma yapan, atıf alan, iş birliği yapan ülke ABD’dir. İş zekâsı ve bilgi yönetimi konularının ön plana çıktığı tespit edilmiştir.

Keywords

Yapay Zekâ, Pazarlama, Bibliyometrik Analiz, Sistematik Literatür Taraması, Scopus

References

• Andrés, A. (2009), Measuring Academic Research: How to Undertake a Bibliometric Study, Elsevier.
• Broadus, R.N. (1987), “Toward a definition of “bibliometrics”, Scientometrics, 12(5-6), 373-379.
• Donthu, N. et al. (2021), “How to conduct a bibliometric analysis: An overview and guidelines”, Journal of Business Research, 133, 286-296.
• Elia, G. et al. (2019), “Digital entrepreneurship ecosystem: How digital technologies and collective intelligence are reshaping the entrepreneurial process”, Technological Forecasting and Social Change, 150, 119791.
• Håkansson, H. (1982), International marketing and purchasing of industrial goods, An Interaction Approach, IMP Project Group, John Wiley & Sons.
• Håkansson, H. et al. (2009), Business in Networks, Wiley, Glasgow.
• Han, R. et al. (2021), “Artificial intelligence in business-to-business marketing: a bibliometric analysis of current research status, development and future directions”, Industrial Management & Data Systems, 121(12), 2467-2497.
• Hood, W.W. & C.S. Wilson (2001), “The literature of bibliometrics, scientometrics, and informetrics”, Scientometrics, 52(2), 291-314.
• Huang, M.H. & R.T. Rust (2018), “Artificial Intelligence in Service”, Journal of Service Research, 21(2), 155-172.
• Jarek, K. & G. Mazurek (2019), “Marketing and Artificial Intelligence”, Central European Business Review, 8(2), 46-55.
• Kot, M.T. & G. Leszczynski (2020), “The concept of intelligent agent in business interactions: is virtual assistant an actor or a boundary object?”, Journal of Business and Industrial Marketing, 35(7), 1155-1164.
• Kumar, B. et al. (2020), “Digital mediation in business-to-business marketing: a bibliometric analysis”, Industrial Marketing Management, (85), 126-140.
• LaPlaca, P.J. & A. Lindgreen (2016), “Letter from the Editors”, Industrial Marketing Management, (53), 1-2.
• Lee, J. et al. (2019), “Emerging Technology and Business Model Innovation: The Case of Artificial Intelligence”, Journal of Open Innovation: Technology, Market, and Complexity, 5(3), 44.
• Lee, J.H. (2021), “Changes in marketing brought by AI”, Proceedings - 2021 21st ACIS International Semi-Virtual Winter Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD-Winter, 257-259.
• McCarthy, J. et al. (1955), A proposal for the Dartmouth summer research project on artificial intelligence, <http://www-formal.stanford.edu/jmc/history/dartmouth/dartmouth.html?dom=pscau&src=syn>, 02.03.2022.
• McCorduck, P. (1982), Machines Who Think: A Personal Inquiry into the History and Prospects of Artificial Intelligence, AK Peters/CRC Press: Boca Raton, FL, USA.
• Mustak, M. et al. (2021), “Artificial Intelligence in Marketing: Topic Modeling, Scientometric Analysis, and Research Agenda”, Journal of Business Research, (124), 389-404.
• Rowlands, I. (2005, February), “Emerald authorship data, Lotka's law and research productivity”, in: Aslib Proceedings, Emerald Group Publishing Limited.
• Russell, S. & P. Norvig (2011), “Artificial Intelligence: A Modern Approach”, Artificial Intelligence, (175), 935-937.
• Synder, H. (2019), “Literature review as a research methodology: An overview and guidelines”, Journal of Business Research, (104), 333-339.
• Üsdiken, B. & Y. Pasadeos (1992), “Türkiye’de yayınlanan yönetimle ilgili veri temelli makalelerde yöntem”, ODTÜ Gelişme Dergisi, 19(2), 249-266.
• Van Esch, P. & J. Stewart Black (2021), “Artificial Intelligence (AI): Revolutionizing Digital Marketing”, Australasian Marketing Journal, 29(3), 199-203.
• Wirtz, J. (2021), “Artificial Intelligence in Marketing: Bibliometric Analysis, Topic Modeling and Research Agenda”, Journal of Business Research, (124), 389-404.
• Yılmaz, M. (2006), “Lotka yasası ve Türkiye’de kütüphane ve bilgi bilimi literatürü”, Türk Kütüphaneciliği, 16(1), 61-69.