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Examining the Intersection of Artificial Intelligence and Influencer Marketing with Bibliometric Analysis

Year 2024, Volume: 5 Issue: 2, 83 - 104

Öznur Aktaş

https://doi.org/10.54439/gupayad.1505890

Abstract

Amaç: Bu çalışmanın temel amacı, bibliyometrik bir yaklaşımla yapay zekâ ve influencer kavramlarının birlikte ele alındığı mevcut araştırma eğilimlerini ve temel bulguları ortaya koyarak, gelecekte bu konuyla ilgili araştırma yapmak isteyen araştırmacılara yol göstermektir. Pazarlamacıların, yapay zekâyı pazarlama stratejilerinde giderek daha fazla kullanmaya başladıkları gözlemlenmiştir. Özellikle yapay zekâ ürünü olan yapay influencer kavramı, akademik dünyanın ilgisini çekmeye başlamıştır. Gereç ve Yöntem: 2008 yılından 4 Haziran 2024 tarihine kadar yayımlanan ve Scopus veri tabanında indekslenen, yapay zekâ (artificial intelligence) ve influencer konularını birlikte ele alan akademik yayınların bibliyometrik analizi yapılmıştır. Bu amaçla “R Studio” programının bibliyometrik paketi kullanılarak literatürdeki ana akımları ve ilişkileri ortaya çıkaracak birlikte oluşum ağ ve trend analizi yöntemleriyle analiz yapılmıştır. Bulgular: Elde edilen sonuçlar, yapay zekâ ile üretilen yapay influencer konusuna olan ilginin özellikle son yıllarda arttığını göstermektedir. Ayrıca, konu ile ilgili daha fazla yayına ihtiyaç olduğu tespit edilmiştir.

Keywords

Yapay Zekâ (AI) Influencer Bibliyometrik Analiz Bibliyometri Influencer Pazarlama

References

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  • Aktaş, Ö., & Gürbüz, A. (2022). Sosyal medya etkileyicilerinin genç tüketicilerinin kıyafet satın alma niyetleri üzerindeki etkisi. JOEEP: Journal of Emerging Economies And Policy, 7(2), 418-432.
  • Alboqami, H. (2023). Trust me, I'm an influencer! -Causal recipes for customer trust in artificial intelligence influencers in the retail industry. Journal Of Retailing And Consumer Services, 72, 103242. https://doi.org/10.1016/j.jretconser.2022.103242
  • Anayat, S., & Rasool, G. (2024). Artificial intelligence marketing (AIM): Connecting-the-dots using bibliometrics. Journal of Marketing Theory and Practice, 32(1), 114-135. https://doi.org/10.1080/10696679.2022.2103435
  • Akter, S., Varsha, P. S., Kumar, A., Gochhait, S., & Patagundi, B. (2021). The impact of artificial intelligence on branding: A bibliometric analysis (1982-2019). Journal of Global Information Management, 29(4), 221-246. https://doi:10.4018/jgım.20210701.oa10
  • Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-Tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007
  • Bailis, R. (2019). The state of influencer marketing: 10 influencer marketing statistics to inform where you invest. Bigcommerce. Retrieved From: https://www.bigcommerce.com/blog/influencer-marketing-statistics/#10-most-important-influencer-marketing-statisticsfor-2019 Retrieved date: 11/06/2024
  • Baklanov, N. (2019). The top instagram virtual influencers in 2019. Hype-Journal. Retrieved From: https:// hypeauditor.com/blog/the-top-instagram-virtual-influencers-in-2019/ Retrieved date: 11/06/2024
  • Bansal, R., Saini, S., Ngah, A. H., & Durga Prasad, T. (2024). Proselytizing the potential of influencer marketing via artificial intelligence: Mapping the research trends through bibliometric analysis. Cogent Business & Management, 11(1), 2372889. https://doi.org/10.1080/23311975.2024.2372889
  • Bellardo, T. (1980). The use of co-citations to study science. Library Research, 2(3), 231- 237.
  • Ben Jabeur, L., Tamine, L., & Boughanem, M. (2012, October). Active microbloggers: Identifying influencers, leaders and discussers in microblogging networks. In International Symposium on String Processing and Information Retrieval (pp. 111-117). Berlin, Heidelberg: Springer Berlin Heidelberg.
  • Biancone, P. P., Saiti, B., Petricean, D. & Chmet, F. (2020). The bibliometric analysis of Islamic banking and finance. Journal of Islamic Accounting and Business Research, 11(9), 2069-2086. https://doi.org/10.1108/JIABR-08-2020-0235
  • Borgman, C. L., & Furner, J. (2002). Scholarly communication and bibliometrics. Annual Review of İnformation Science And Technology, 36(1), 1-53. https://doi.org/10.1016/j.ijinfomgt.2020.102201
  • Bunker, D. (2020). Who do you trust? The digital destruction of shared situational awareness and the COVID-19 infodemic. International Journal of Information Management, 55, 102201. https://doi.org/10.1016/j.ijinfomgt.2020.102201
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  • Da Silva Oliveira, A. B., & Chimenti, P. (2021). Humanized robots: A proposition of categories to understand virtual ınfluencers. Australasian Journal of Information Systems, 25. https://doi.org/10.3127/ajis.v25i0.3223
  • Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48, 24-42.
  • De Veirman, M., Cauberghe, V., & Hudders, L. (2017). Marketing through Instagram influencers: The impact of number of followers and product divergence on brand attitude. International Journal of Advertising, 36(5), 798-828. https://doi.org/10.1080/02650487.2017.1348035
  • Di Guardo, M. C., & Harrigan, K. R. (2012). Mapping research on strategic alliances and innovation: A co-citation analysis. The Journal of Technology Transfer, 37, 789-811.
  • Donthu, N., Kumar, S., & Pattnaik, D. (2020). Forty-five years of Journal of Business Research: A bibliometric analysis. Journal of business research, 109, 1-14. https://doi.org/10.1016/j.jbusres.2019.10.039
  • Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285-296. https://doi.org/10.1016/j.jbusres.2021.04.070
  • Dumitriu, D., & Popescu, M. A. M. (2020). Artificial intelligence solutions for digital marketing. Procedia Manufacturing, 46, 630-636. https://doi.org/10.1016/j.promfg.2020.03.090
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Yapay Zekâ ve Influencer Pazarlamasının Kesişiminin Bibliyometrik Analiz ile İncelenmesi

Year 2024, Volume: 5 Issue: 2, 83 - 104

Öznur Aktaş

https://doi.org/10.54439/gupayad.1505890

Abstract

Amaç: Bu çalışmanın temel amacı, bibliyometrik bir yaklaşımla yapay zekâ ve influencer kavramlarının birlikte ele alındığı mevcut araştırma eğilimlerini ve temel bulguları ortaya koyarak, gelecekte bu konuyla ilgili araştırma yapmak isteyen araştırmacılara yol göstermektir. Pazarlamacıların, yapay zekâyı pazarlama stratejilerinde giderek daha fazla kullanmaya başladıkları gözlemlenmiştir. Özellikle yapay zekâ ürünü olan yapay influencer kavramı, akademik dünyanın ilgisini çekmeye başlamıştır. Gereç ve Yöntem: 2008 yılından 4 Haziran 2024 tarihine kadar yayımlanan ve Scopus veri tabanında indekslenen, yapay zekâ (artificial intelligence) ve influencer konularını birlikte ele alan akademik yayınların bibliyometrik analizi yapılmıştır. Bu amaçla “R Studio” programının bibliyometrik paketi kullanılarak literatürdeki ana akımları ve ilişkileri ortaya çıkaracak birlikte oluşum ağ ve trend analizi yöntemleriyle analiz yapılmıştır. Bulgular: Elde edilen sonuçlar, yapay zekâ ile üretilen yapay influencer konusuna olan ilginin özellikle son yıllarda arttığını göstermektedir. Ayrıca, konu ile ilgili daha fazla yayına ihtiyaç olduğu tespit edilmiştir.

Keywords

Yapay Zekâ (AI) Influencer Bibliyometrik Analiz Bibliyometri Influencer Pazarlama

Ethical Statement

Bu çalışma bilimsel araştırma ve yayın etiği izni gerektiren bir çalışma olmadığı için etik kurul onayı alınmamıştır.

References

  • Ahn, R. J., Cho, S. Y., & Sunny Tsai, W. (2022). Demystifying computer-generated imagery (CGI) influencers: The effect of perceived anthropomorphism and social presence on brand outcomes. Journal of interactive advertising, 22(3), 327-335. https://doi.org/10.1080/ 15252019.2022.2111242
  • Aktaş, Ö., & Gürbüz, A. (2022). Sosyal medya etkileyicilerinin genç tüketicilerinin kıyafet satın alma niyetleri üzerindeki etkisi. JOEEP: Journal of Emerging Economies And Policy, 7(2), 418-432.
  • Alboqami, H. (2023). Trust me, I'm an influencer! -Causal recipes for customer trust in artificial intelligence influencers in the retail industry. Journal Of Retailing And Consumer Services, 72, 103242. https://doi.org/10.1016/j.jretconser.2022.103242
  • Anayat, S., & Rasool, G. (2024). Artificial intelligence marketing (AIM): Connecting-the-dots using bibliometrics. Journal of Marketing Theory and Practice, 32(1), 114-135. https://doi.org/10.1080/10696679.2022.2103435
  • Akter, S., Varsha, P. S., Kumar, A., Gochhait, S., & Patagundi, B. (2021). The impact of artificial intelligence on branding: A bibliometric analysis (1982-2019). Journal of Global Information Management, 29(4), 221-246. https://doi:10.4018/jgım.20210701.oa10
  • Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-Tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007
  • Bailis, R. (2019). The state of influencer marketing: 10 influencer marketing statistics to inform where you invest. Bigcommerce. Retrieved From: https://www.bigcommerce.com/blog/influencer-marketing-statistics/#10-most-important-influencer-marketing-statisticsfor-2019 Retrieved date: 11/06/2024
  • Baklanov, N. (2019). The top instagram virtual influencers in 2019. Hype-Journal. Retrieved From: https:// hypeauditor.com/blog/the-top-instagram-virtual-influencers-in-2019/ Retrieved date: 11/06/2024
  • Bansal, R., Saini, S., Ngah, A. H., & Durga Prasad, T. (2024). Proselytizing the potential of influencer marketing via artificial intelligence: Mapping the research trends through bibliometric analysis. Cogent Business & Management, 11(1), 2372889. https://doi.org/10.1080/23311975.2024.2372889
  • Bellardo, T. (1980). The use of co-citations to study science. Library Research, 2(3), 231- 237.
  • Ben Jabeur, L., Tamine, L., & Boughanem, M. (2012, October). Active microbloggers: Identifying influencers, leaders and discussers in microblogging networks. In International Symposium on String Processing and Information Retrieval (pp. 111-117). Berlin, Heidelberg: Springer Berlin Heidelberg.
  • Biancone, P. P., Saiti, B., Petricean, D. & Chmet, F. (2020). The bibliometric analysis of Islamic banking and finance. Journal of Islamic Accounting and Business Research, 11(9), 2069-2086. https://doi.org/10.1108/JIABR-08-2020-0235
  • Borgman, C. L., & Furner, J. (2002). Scholarly communication and bibliometrics. Annual Review of İnformation Science And Technology, 36(1), 1-53. https://doi.org/10.1016/j.ijinfomgt.2020.102201
  • Bunker, D. (2020). Who do you trust? The digital destruction of shared situational awareness and the COVID-19 infodemic. International Journal of Information Management, 55, 102201. https://doi.org/10.1016/j.ijinfomgt.2020.102201
  • Byrne, M., Archibald‐Heeren, B., Hu, Y., Teh, A., Beserminji, R., Cai, E., ... & Aland, T. (2022). Varian ethos online adaptive radiotherapy for prostate cancer: Early results of contouring accuracy, treatment plan quality, and treatment time. Journal of Applied Clinical Medical Physics, 23(1), e13479. https://doi.org/10.1002/acm2.13479
  • Carter, D. (2016). Hustle and brand: The sociotechnical shaping of influence. Social Media+ Society, 2(3), 2056305116666305. https://doi.org/10.1177/2056305116666305
  • Chen, J., Ablanedo-Rosas, J. H., Frankwick, G. L., & Arévalo, F. R. J. (2021). The state of artificial intelligence in marketing with directions for future research. International Journal of Business Intelligence Research (IJBIR), 12(2), 1-26.
  • Da Silva Oliveira, A. B., & Chimenti, P. (2021). Humanized robots: A proposition of categories to understand virtual ınfluencers. Australasian Journal of Information Systems, 25. https://doi.org/10.3127/ajis.v25i0.3223
  • Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48, 24-42.
  • De Veirman, M., Cauberghe, V., & Hudders, L. (2017). Marketing through Instagram influencers: The impact of number of followers and product divergence on brand attitude. International Journal of Advertising, 36(5), 798-828. https://doi.org/10.1080/02650487.2017.1348035
  • Di Guardo, M. C., & Harrigan, K. R. (2012). Mapping research on strategic alliances and innovation: A co-citation analysis. The Journal of Technology Transfer, 37, 789-811.
  • Donthu, N., Kumar, S., & Pattnaik, D. (2020). Forty-five years of Journal of Business Research: A bibliometric analysis. Journal of business research, 109, 1-14. https://doi.org/10.1016/j.jbusres.2019.10.039
  • Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285-296. https://doi.org/10.1016/j.jbusres.2021.04.070
  • Dumitriu, D., & Popescu, M. A. M. (2020). Artificial intelligence solutions for digital marketing. Procedia Manufacturing, 46, 630-636. https://doi.org/10.1016/j.promfg.2020.03.090
  • Erkan, İ. (2020). Dijital pazarlamanın dünü, bugünü, geleceği: Bibliyometrik bir analiz. Akademik Hassasiyetler, 7(13), 149-168.
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Details

Primary Language Turkish
Subjects Artificial Intelligence (Other), Digital Marketing, Consumer Behaviour
Journal Section Research Articles
Authors

Öznur Aktaş

Early Pub Date November 18, 2024
Publication Date
Submission Date June 27, 2024
Acceptance Date October 28, 2024
Published in Issue Year 2024 Volume: 5 Issue: 2

Cite

APA Aktaş, Ö. (2024). Yapay Zekâ ve Influencer Pazarlamasının Kesişiminin Bibliyometrik Analiz ile İncelenmesi. Güncel Pazarlama Yaklaşımları Ve Araştırmaları Dergisi, 5(2), 83-104. https://doi.org/10.54439/gupayad.1505890
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