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Yapay Zekâ ile Yeniden Şekillenen Dijital Pazarlama Trendleri: Bibliyometrik Bir Yaklaşım

Year 2024, Volume: 9 Issue: 1, 75 - 90

Abstract

Bu çalışma, yapay zekâ teknolojilerinin dijital pazarlama trendlerini nasıl dönüştürdüğünü inceleyerek, 2010-2024 yılları arasındaki scopus indeksinde taranmış akademik yayınlara odaklanmaktadır. Yapay zekanın pazarlama alanındaki yükselişi ile, pazarlama stratejilerini optimize etme ve veri analizi kapasitelerini artırmada önemli bir etki oluşturmuştur. Çalışmanın amacı, yapay zekâ ve dijital pazarlama kesişimindeki mevcut araştırma eğilimlerini, temel bulguları ve gelecekteki potansiyel alanları bibliyometrik bir yaklaşımla değerlendirmektir. Çalışmanın analizi "R" programının bibliometrix eklentisi kullanılarak yapılmıştır. Scopus veri tabanlarından elde edilen makaleler, belirlenen anahtar kelimelerle filtrelenip, sıklık, alıntı sayısı, yazarlar, kaynaklar ve konuları temel alarak değerlendirilmiştir. Ayrıca, eş-ortaklık analizi, ağ analizi ve trend analizi gibi yöntemler kullanılarak, literatürdeki ana akımlar ve ilişkiler ortaya konuşmuştur. Bulunan sonuçlar, yapay zekânın dijital pazarlama alanında giderek artan bir etkiye sahip olduğunu göstermektedir.

References

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Digital Marketing Trends Reshaped by Artificial Intelligence: A Bibliometric Approach

Year 2024, Volume: 9 Issue: 1, 75 - 90

Abstract

This study examines how artificial intelligence technologies have transformed digital marketing trends, focusing on academic publications indexed in Scopus from 2010 to 2024. The rise of artificial intelligence in marketing has significantly impacted optimizing marketing strategies and enhancing data analysis capabilities. The aim is to assess current research trends, key findings, and future potential areas at artificial intelligence and digital marketing intersections through a bibliometric approach. The analysis was conducted using the "R" program's bibliometrix package, evaluating articles from Scopus databases based on selected keywords, frequency, citation counts, authors, sources, and subjects. Additionally, co-occurrence, network, and trend analysis methods were employed to reveal the main currents and relationships in the literature. The results indicate an increasingly significant impact of artificial intelligence on the field of digital marketing.

References

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  • Almeida, D., Naudé, W., & Sequeira, T. N. (2024). Artificial Intelligence and the Discovery of New Ideas: Is an Economic Growth Explosion Imminent? (No. 16766). Institute of Labor Economics (IZA).
  • Alyoshina, I. V. (2020). Artificial Intelligence for University Marketing. Biruta Svagzdiene, Arturas Simanavicius, Edmundas Jasinskas, Vilius Vasilius, 17. https://doi.org/10.17747/teds-2020-17-21
  • Anoir, L., Khaldi, M., & Erradi, M. (2024). Symbiotic Evolution: The Inextricable Relation between the Web and E-Learning. DIROSAT: Journal of Education, Social Sciences & Humanities, 2(1), 10-18. https://doi.org/10.58355/dirosat.v2i1.65
  • Appio, F. P., Cesaroni, F., & Di Minin, A. (2014). Visualizing the structure and bridges of the intellectual property management and strategy literature: A document cocitation analysis. Scientometrics, 101(1), 623–661. https://doi.org/10.1007/s11192-014-1329-0
  • 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
  • Ashworth, L., & Free, C. (2006). Marketing dataveillance and digital privacy: Using theories of justice to understand consumers’ online privacy concerns. Journal of Business Ethics, 67, 107-123. https://doi.org/10.1007/s10551-006-9007-7
  • Batra, S., Saini, M., Yadav, M., & Aggarwal, V. (2022). Mapping the intellectual structure and demystifying the research trend of cross listing: a bibliometric analysis. Managerial Finance, 49(6), 992-1016. https://doi.org/10.1108/MF-07-2022-0330.
  • Bhatt, V. K. (2021). Assessing the significance and impact of artificial intelligence and machine learning in placement of advertisements. In 2021 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD) (pp. 1-6). IEEE. https://doi.org/10.1109/ICTMOD52902.2021.9739228
  • Biancone, PP, Saiti, B., Petricean, D., & Chmet, F. (2020). Bibliometric analysis of Islamic banking and finance. Journal of Muslim Accounting and Business Research, 11(9), 2069–2086. https://doi.org/10.1108/JIABR-08-2020-0235
  • Bischoff, J., Berezan, O., & Scardicchio, L. (2019). The digital self and customer loyalty: from theory to virtual reality. Journal of Marketing Analytics, 7, 220-233. https://doi.org/10.1057/s41270-019-00065-4
  • Borgman, C. L., & Furner, J. (2002). Scholarly communication and bibliometrics. Annual review of information science and technology, 36(1), 1-53.
  • Bruce, E., Zhao, S., Du, Y., Meng, Y., Amoah, J. K., & Egala, S. B. (2023). The effect of digital marketing adoption on SMEs sustainable growth: Empirical evidence from Ghana. Sustainability, 15(6), 4760. https://doi.org/10.3390/su15064760
  • Busca, L., & Bertrandias, L. (2020). A framework for digital marketing research: Investigating the four cultural eras of digital marketing. Journal of Interactive Marketing, 49, 1-19. https://doi.org/10.1016/j.intmar.2019.08.00
  • Business Solution. (2023). 67 AI Marketing Statistics 2023 [Adoption, Use Cases, Market Size]. Access address: https://businessolution.org/ai-marketing-statistics/ Access date: 08.01.2023
  • Buttle, F., & Maklan, S. (2019). Customer relationship management: concepts and technologies. Routledge. https://doi.org/10.4324/9781351016551
  • Chaffey, D., & Ellis-Chadwick, F. (2019). Digital marketing. Pearson uk. https://doi.org/10.1016/j.bushor.2011.01.007
  • Cham, T. H., Cheah, J. H., Memon, M. A., Fam, K. S., & László, J. (2022). Digitalization and its impact on contemporary marketing strategies and practices. Journal of Marketing Analytics, 10(2), 103-105. https://doi.org/10.1057/s41270-022-00167-6
  • Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. Ieee Access, 8, 75264-75278. https://doi.org/10.1109/access.2020.2988510
  • Chintalapati, S., & Pandey, S. K. (2022). Artificial intelligence in marketing: A systematic literature review. International Journal of Market Research, 64(1), 38-68. https://doi.org/10.1177/14707853211018428
  • Chylinski, M., Heller, J., Hilken, T., Keeling, D., Mahr, D., & de Ruyter, K. (2020). Augmented reality marketing: A technology-enabled approach to situated customer experience. Australasian Marketing Journal, 28, 374-384.https://doi.org/10.1016/j.ausmj.2020.04.004
  • Clarke, C., Knights, D., & Jarvis, C. (2012). A labour of love? Academics in business schools. Scandinavian Journal of Management, 28(1), 5-15. https://doi.org/10.1016/j.scaman.2011.12.003
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There are 79 citations in total.

Details

Primary Language English
Subjects Business Administration, Digital Marketing
Journal Section Research Article
Authors

Mehmet Gökerik 0000-0002-0827-5805

Öznur Aktaş 0000-0002-0904-0653

Early Pub Date May 4, 2024
Publication Date
Submission Date January 9, 2024
Acceptance Date March 4, 2024
Published in Issue Year 2024 Volume: 9 Issue: 1

Cite

APA Gökerik, M., & Aktaş, Ö. (2024). Digital Marketing Trends Reshaped by Artificial Intelligence: A Bibliometric Approach. JOEEP: Journal of Emerging Economies and Policy, 9(1), 75-90.

JOEEP is published as two issues per year June and December and all publication policies and processes are conducted according to the international standards. JOEEP accepts and publishes the research articles in the fields of economics, political economy, fiscal economics, applied economics, business economics, labour economics and econometrics. JOEEP, without depending on any institution or organization, is a non-profit journal that has an International Editorial Board specialist on their fields. All “Publication Process” and “Writing Guidelines” are explained in the related title and it is expected from authors to Show a complete match to the rules. JOEEP is an open Access journal.