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

Yıl 2024, Cilt: 9 Sayı: 1, 75 - 90, 30.06.2024

Mehmet Gökerik , Öznur Aktaş

Öz

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.

Anahtar Kelimeler

Yapay Zeka, Dijital Pazarlama, Bibliyometrik Analiz, Bibliometrix

Digital Marketing Trends Reshaped by Artificial Intelligence: A Bibliometric Approach

Öz

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.

Anahtar Kelimeler

Artificial Intelligence, Digital Marketing, Bibliometric Analysis, Bibliometrix

Kaynakça

• Ali Abbasi, G., Abdul Rahim, N. F., Wu, H., Iranmanesh, M., & Keong, B. N. C. (2022). Determinants of SME’s social media marketing adoption: competitive industry as a moderator. Sage Open, 12(1), https://doi.org/10.1177/21582440211067220
• 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
• Coelho, M. P., & Mendes, J. Z. (2019). Digital music and the “death of the long tail”. Journal of Business Research, 101, 454-460. https://doi.org/10.1016/j.jbusres.2019.01.015
• Darmody, A., & Zwick, D. (2020). Manipulate to empower: Hyper-relevance and the contradictions of marketing in the age of surveillance capitalism. Big Data & Society, 7(1), 2053951720904112. https://doi.org/10.1177/2053951720904112
• Dellaert, B. G. C. (2018). The consumer production journey: Marketing to consumers as co-producers in the sharing economy. Journal of the Academy of Marketing Science, 47, 238-254.https://doi.org/10.1007/s11747-018-0607-4
• Dellaert, B. G., Shu, S. B., Arentze, T. A., Baker, T., Diehl, K., Donkers, B., ... & Steffel, M. (2020). Consumer decisions with artificially intelligent voice assistants. Marketing Letters, 31, 335-347. https://doi.org/10.1007/s11002-020-09537-5
• Di Guardo, M. C. ve Harrigan, K. R. (2012). Mapping research on strategic alliances and innovation: a cocitation analysis. The Journal of Technology Transfer, 37(6), 789–811. https://doi 10.1007/s10961-011-9239-2
• 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
• Drummond, C., O'Toole, T., & McGrath, H. (2020). Digital engagement strategies and tactics in social media marketing. European Journal of Marketing, 54, 1247-1280. https://doi.org/10.1108/EJM-02-2019-0183
• Ducange, P., Fazzolari, M., Petrocchi, M., & Vecchio, M. (2019). An effective Decision Support System for social media listening based on cross-source sentiment analysis models. Engineering Applications of Artificial Intelligence, 78, 71-85. https://doi.org/10.1016/j.engappai.2018.10.014
• 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
• Dwivedi, Y. K., Ismagilova, E., Hughes, D. L., Carlson, J., Filieri, R., Jacobson, J., ... & Wang, Y. (2021). Setting the future of digital and social media marketing research: Perspectives and research propositions. International Journal of Information Management, 59, 102168. https://doi.org/10.1016/j.ijinfomgt.2020.102168
• Erkan, İ. (2020). Dijital Pazarlamanın Dünü, Bugünü, Geleceği: Bibliyometrik Bir Analiz. Akademik Hassasiyetler, 7(13), 149-168.
• Garfield, E. (1990). KeyWords Plus-ISI's breakthrough retrieval method. 1. Expanding your searching power on current-contents on diskette. Current contents, 32, 5-9.
• Gielens, K., & Steenkamp, J. B. E. (2019). Branding in the era of digital (dis) intermediation. International Journal of Research in Marketing, 36(3), 367-384. https://doi.org/10.1016/j.ijresmar.2019.01.005
• Gill, K. S. (2024). Eliza! A reckoning with Cartesian magic. Ai & Society, 1-3. https://doi.org/10.1007/s00146-024-01868-5
• Glaum, M., & Street, D. L. (2003). Compliance with the disclosure requirements of Germany's new market: IAS versus US GAAP. Journal of International Financial Management & Accounting, 14(1), 64-100. https://doi.org/10.1111/1467-646X.00090
• Gold, S., Trautrims, A., & Trodd, Z. (2015). Modern slavery challenges to supply chain management. Supply chain management: an international journal, 20(5), 485-494. https://doi.org/10.1108/scm-02-2015-0046
• Grossberg, K. A. (2016). The new marketing solutions that will drive strategy implementation. Strategy & leadership, 44(3), 20-26. https://doi.org/10.1108/SL-04-2016-0018
• Güler, S. (2023). Dijital Liderlik Araştırmaları Üzerine Bibliyometrik Bir Analiz. Yönetim & Organizasyon Alanında Seçme Yazılar, 71. https://doi.org/10.58830/ozgur.pub258.c1301
• Han, R., Lam, H. K., Zhan, Y., Wang, Y., Dwivedi, Y. K., & Tan, K. H. (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. https://doi.org/10.1108/IMDS-05-2021-0300
• Hanna, R., Rohm, A., & Crittenden, V. L. (2011). We’re all connected: The power of the social media ecosystem. Business horizons, 54(3), 265-273. https://doi.org/10.1016/j.bushor.2011.01.007
• He, W. (2022). Research Hotspot and Prospect of Artificial Intelligence in Marketing in China - Visual Analysis Based on CiteSpace. https://doi.org/10.54691/bcpbm.v20i.1021
• Joshi, Y., Lim, W. M., Jagani, K., & Kumar, S. (2023). Social media influencer marketing: foundations, trends, and ways forward. Electronic Commerce Research, 1-55. https://doi.org/10.1007/s10660-023-09719-z
• Kannan, P. K. (2017). Digital marketing: A framework, review and research agenda. International journal of research in marketing, 34(1), 22-45. https://doi.org/10.1016/j.ijresmar.2016.11.006
• Khatri, M. (2021). How digital marketing along with artificial intelligence is transforming consumer behaviour. International Journal for Research in Applied Science and Engineering Technology, 9(VII), 523-527. https://doi.org/10.22214/ijraset.2021.36287
• Knechel, W. R., & Willekens, M. (2006). The role of risk management and governance in determining audit demand. Journal of Business Finance & Accounting, 33(9‐10), 1344-1367. https://doi.org/10.1111/j.1468-5957.2006.01238.x
• Kocic, M., & Radaković, K. (2018). The importance of digital marketing in the customer relationship management process. Marketing Science, 49, 44-51. https://doi.org/10.5937/markt1801044k
• Kotane, I., Znotina, D., & Hushko, S. (2019). Assessment of trends in the application of digital marketing. Scientific Journal of Polonia University, 33(2), 28-35. https://doi.org/10.23856/3303
• Koulaouzidis, G., Jadczyk, T., Iakovidis, D. K., Koulaouzidis, A., Bisnaire, M., & Charisopoulou, D. (2022). Artificial intelligence in cardiology—a narrative review of current status. Journal of Clinical Medicine, 11(13), 3910. https://doi.org/10.3390/jcm11133910
• Kull, A. J., Romero, M., & Monahan, L. (2021). How may I help you? Driving brand engagement through the warmth of an initial chatbot message. Journal of business research, 135, 840-850. https://doi.org/10.1016/j.jbusres.2021.03.005
• Kumar, V., Dixit, A., Javalgi, R. G., & Dass, M. (2016). Research framework, strategies, and applications of intelligent agent technologies (IATs) in marketing. Journal of the Academy of Marketing Science, 44, 24-45. 10.1007/s11747-015-0426-9
• Leung, K. H., Luk, C. C., Choy, K. L., Lam, H. Y., & Lee, C. K. (2019). A B2B flexible pricing decision support system for managing the request for quotation process under e-commerce business environment. International Journal of Production Research, 57(20), 6528-6551. https://doi.org/10.1080/00207543.2019.1566674
• Li, S., Vlassis, N., Kawale, J., & Fu, Y. (2016). Matching via Dimensionality Reduction for Estimation of Treatment Effects in Digital Marketing Campaigns. In IJCAI (pp. 3768-3774). https://dl.acm.org/doi/abs/10.5555/3061053.3061146
• Liebenlito, M., Inayah, N., Choerunnisa, E., Sutanto, T. E., & Inna, S. (2024). Active learning on Indonesian Twitter sentiment analysis using uncertainty sampling. Journal of Applied Data Sciences, 5(1), 114-121. https://doi.org/10.47738/jads.v5i1.144
• Low, S., Ullah, F., Shirowzhan, S., Sepasgozar, S. M., & Lin Lee, C. (2020). Smart digital marketing capabilities for sustainable property development: A case of Malaysia. Sustainability, 12(13), 5402. https://doi.org/10.3390/su12135402
• Ma, L., & Sun, B. (2020). Machine learning and AI in marketing–Connecting computing power to human insights. International Journal of Research in Marketing, 37(3), 481-504. https://doi.org/10.1016/j.ijresmar.2020.04.005
• Miklosik, A., Kuchta, M., Evans, N., & Zak, S. (2019). Towards the adoption of machine learning-based analytical tools in digital marketing. Ieee Access, 7, 85705-85718. https://doi.org/10.1109/access.2019.2924425
• Mogaji, E., Soetan, T. O., & Kieu, T. A. (2020). The implications of artificial intelligence on the digital marketing of financial services to vulnerable customers. Australasian Marketing Journal, j-ausmj. https://doi.org/10.1016/j.ausmj.2020.05.003
• Montgomery, K. C., Chester, J., & Milosevic, T. (2017). Children’s privacy in the big data era: Research opportunities. Pediatrics, 140(Supplement_2), S117-S121. https://doi.org/10.1542/peds.2016-1758O
• Nazar, M., Alam, M. M., Yafi, E., & Su’ud, M. M. (2021). A systematic review of human–computer interaction and explainable artificial intelligence in healthcare with artificial intelligence techniques. IEEE Access, 9, 153316-153348. https://doi.org/10.1109/access.2021.3127881
• Önal, G. F. (2017). Bildirilerin Bibliyometrik Profili: IX. Ulusal Müzik Eğitimi Sempozyumu. Ahi Evran Üniversitesi Kırşehir Eğitim Fakültesi Dergisi, 18(3), 1079-1097.
• Peters, U. (2024). Science Based on Artificial Intelligence Need not Pose a Social Epistemological Problem.
• Pritchard, A. (1969). Statistical bibliography or bibliometrics. Journal of Documentation, 25(4), ss.348-349.
• Radesky, J., Chassiakos, Y. L. R., Ameenuddin, N., & Navsaria, D. (2020). Digital advertising to children. Pediatrics, 146(1). https://doi.org/10.1542/peds.2020-1681
• Richardson, G. (2006). Determinants of tax evasion: A cross-country investigation. Journal of international Accounting, Auditing and taxation, 15(2), 150-169. https://doi.org/10.1016/j.intaccaudtax.2006.08.005
• Ruiz-Real, J. L., Uribe-Toril, J., Torres, J. A., & De Pablo, J. (2021). Artificial intelligence in business and economics research: Trends and future. Journal of Business Economics and Management, 22(1), 98-117. https://doi.org/10.3846/jbem.2020.13641
• Sanz, E. (2014). On the symbolic production of digital markets for cultural goods. Journal of Cultural Economy, 7, 131-144. https://doi.org/10.1080/17530350.2013.851028
• Saura, J. R., Ribeiro-Soriano, D., & Palacios-Marqués, D. (2021). Setting B2B digital marketing in artificial intelligence-based CRMs: A review and directions for future research. Industrial Marketing Management, 98, 161-178. https://doi.org/10.1016/j.indmarman.2021.08.006
• Smith, A. N., Fischer, E., & Yongjian, C. (2012). How does brand-related user-generated content differ across YouTube, Facebook, and Twitter?. Journal of interactive marketing, 26(2), 102-113. https://doi.org/10.1016/j.intmar.2012.01.002
• Sprong, N., Driessen, P. H., Hillebrand, B., & Molner, S. (2021). Market innovation: A literature review and new research directions. Journal of Business Research, 123, 450-462. https://doi.org/10.1016/j.jbusres.2020.09.057
• Statista. (2023). Artificial intelligence in marketing industry value prediction for 2028. Access address: https://www.statista.com/topics/5017/ai-use-in-marketing/ Access date: 08.01.2023
• Sunarya, P. A., Rahardja, U., Chen, S. C., Lic, Y. M., & Hardini, M. (2024). Deciphering Digital Social Dynamics: A Comparative Study of Logistic Regression and Random Forest in Predicting E-Commerce Customer Behavior. Journal of Applied Data Sciences, 5(1), 100-113. https://doi.org/10.47738/jads.v5i1.155
• Tiautrakul, J., & Jindakul, J. (2019). The Artificial Intelligence (AI) with the Future of Digital Marketing. Available at SSRN 3405184. https://doi.org/10.2139/ssrn.3405184
• Toader, D. C., Boca, G., Toader, R., Măcelaru, M., Toader, C., Ighian, D., & Rădulescu, A. T. (2019). The effect of social presence and chatbot errors on trust. Sustainability, 12(1), 256. https://doi.org/10.3390/su12010256
• Turker, D., & Altuntas, C. (2014). Sustainable supply chain management in the fast fashion industry: An analysis of corporate reports. European Management Journal, 32(5), 837-849. https://doi.org/10.1016/j.emj.2014.02.001
• Vollrath, M., & Villegas, S. G. (2021). Avoiding digital marketing analytics myopia: revisiting the customer decision journey as a strategic marketing framework. Journal of Marketing Analytics, 10, 106-113. https://doi.org/10.1057/s41270-020-00098-0
• Wirth, N. (2018). Hello marketing, what can artificial intelligence help you with?. International Journal of Market Research, 60(5), 435-438. https://doi.org/10.1177/1470785318776841
• Zaveri, B., & Amin, P. (2019). Augmented and virtual reality: Future of marketing trends. Manthan: Journal of Commerce and Management, 16-25. https://doi.org/10.17492/manthan.v6I1.182679