TRENDS IN ARTIFICIAL INTELLIGENCE MARKETING: A BIBLIOMETRIC ANALYSIS

Yıl 2023, Cilt: 3 Sayı: 2, 56 - 73, 20.10.2023

İbrahim Halil Efendioğlu

Öz

This study aims to examine artificial intelligence marketing research through bibliometric analysis and thoroughly examine publications related to artificial intelligence marketing. In line with this objective, 350 studies containing the terms "artificial intelligence market*" or "AI market*" in their keywords, titles, or abstracts were analyzed from the Web of Science (WoS). The data were analyzed using the R programming language, R Studio, and Bibliometrix package. The examined studies span the years 1983 to 2023. The analyses indicate that artificial intelligence marketing studies gained significance in 2015 and experienced a more rapid increase after 2018. The most prominent keywords in the literature include artificial intelligence, technology, future, information, management, performance, and big data concepts. The countries with the most significant volume of research in artificial intelligence marketing are China and USA. In addition, the journals with the most significant number of publications, authors, and countries that collaborated are shown in the study. In addition, the publications' conceptual, social, and intellectual structure was examined. Finally, various suggestions have been made to researchers who want to work in artificial intelligence marketing.

Anahtar Kelimeler

Artificial Intelligence Marketing, Bibliometric Analysis, Web of Science

YAPAY ZEKA PAZARLAMASINDA TRENDLER: BİBLİYOMETRİK BİR ANALİZ

Öz

Bu çalışma, yapay zeka pazarlama araştırmalarını bibliyometrik analiz yoluyla incelemeyi ve yapay zeka pazarlamayla ilgili çalışmaların kapsamlı bir genel bakışını sunmayı amaçlamaktadır. Bu amaç doğrultusunda, anahtar kelimelerinde, başlıklarında veya özetlerinde "artificial intelligence market*" ve "AI market*" ifadesini içeren 350 çalışma, Web of Science (WoS) veritabanından analiz edilmiştir. Elde edilen veri seti R programlama dili, R Studio ve Bibliometrix paketi kullanılarak bibliyometrik analiz yöntemi esas alınarak analiz edilmiştir. İncelenen çalışmalar 1983 – 2023 yıllarını kapsamaktadır. Analizler, yapay zeka pazarlama çalışmalarının 2015 yılından itibaren önem kazandığı ve 2018 yılından sonra daha hızlı bir şekilde arttığını göstermektedir. Literatürde en fazla öne çıkan anahtar kelimeler; yapay zeka, teknoloji, gelecek, bilgi, yönetim, performans ve büyük veri kavramlarıdır. Yapay zeka pazarlama konusunda en fazla çalışma yapan ülkeler; Çin ve ABD’dir. Ayrıca araştırmada en fazla çalışma yayımlanan dergiler, yazarlar ve birlikte çalışma yapan ülkeler gösterilmiştir. Bunun yanında literatürün, kavramsal, entelektüel ve sosyal,yapısı incelenmiştir. Son olarak yapay zeka pazarlamasında çalışma yapmak isteyen araştırmacılara çeşitli önerilerde bulunulmuştur.

Anahtar Kelimeler

Yapay Zeka Pazarlaması, Bibliyometrik Analiz, Web of Science

Kaynakça

• Agrawal, A., Gans, J. S., & Goldfarb, A. (2019). Artificial intelligence: the ambiguous labor market impact of automating prediction. Journal of Economic Perspectives, 33(2), 31-50. https://doi.org/10.1257/jep.33.2.31
• Alyoshina, I. V. (2019). Artificial intelligence in an age of digital globalization. In International Conference Technology & Entrepreneurship in Digital Society. 26-30.
• 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
• Arsenijevic, U. ve Jovic, M. (2019). Artificial ıntelligence marketing: chatbots. International Conference on Artificial Intelligence: Applications and Innovations, Crete, Greece, 19 22.
• Bayuk, M. N. ve Demir, B. N. (2019). Endüstri 4.0 kapsamında yapay zeka ve pazarlamanın geleceği. Journal of Social, Humanities and Administrative Sciences, 5(19), 781-799
• Capatina, A., Kachour, M., Lichy, J., Micu, A., Micu, A. E., & Codignola, F. (2020). Matching the future capabilities of an artificial intelligence-based software for social media marketing with potential users’ expectations. Technological Forecasting and Social Change, 151, 119794. https://doi.org/10.1016/j.techfore.2019.119794
• Chatterjee, S., Chaudhuri, R., Vrontis, D., Thrassou, A., & Ghosh, S. K. (2021). Adoption of artificial intelligence-integrated CRM systems in agile organizations in India. Technological Forecasting and Social Change, 168, 120783. https://doi.org/10.1016/j.techfore.2021.120783
• Cobo, M. J., López‐Herrera, A. G., Herrera‐Viedma, E., ve Herrera, F. (2011). Science mapping software tools: Review, analysis, and cooperative study among tools. Journal of the American Society for Information Science and Technology, 62(7), 1382 1402. https://doi.org/10.1002/asi.21525
• 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. https://doi.org/10.1007/s11747-019-00696-0
• Donthu, N., Kumar, S., Pattnaik, D., & Lim, W. M. (2021). A bibliometric retrospection of marketing from the lens of psychology: Insights from Psychology & Marketing. Psychology & Marketing, 38(5), 834-865. https://doi.org/10.1002/mar.21472
• Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., ... & Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002
• Ekinci, G., & Özsaatci Bilginer, F. G. (2023). Yapay Zekâ ve Pazarlama Alanındaki Yayınların Bibliyometrik Analizi. Sosyoekonomi, 31(56), 369-388. https://doi.org/10.17233/sosyoekonomi.2023.02.17
• Ercan, F. (2020). Turizm pazarlamasında yapay zekâ teknolojilerinin kullanımı ve uygulama örnekleri. Ankara Hacı Bayram Veli Üniversitesi Turizm Fakültesi Dergisi, 23(2), 394 410.
• Eren, A., & Eren, D. (2020). Pazarlama literatüründe elektronik ağızdan ağıza iletişimin bibliyometrik analizi. Journal of Business Research-Turk, 12(3), 2515-2530 https://doi.org/10.20491/isarder.2020.990
• Feng, C. M., Park, A., Pitt, L., Kietzmann, J., & Northey, G. (2021). Artificial intelligence in marketing: A bibliographic perspective. Australasian Marketing Journal, 29(3), 252 263. https://doi.org/10.1016/j.ausmj.2020.07.006
• Frank, B. (2021). Artificial intelligence-enabled environmental sustainability of products: Marketing benefits and their variation by consumer, location, and product types. Journal of Cleaner Production, 285, 125242. https://doi.org/10.1016/j.jclepro.2020.125242
• Gao, P., Meng, F., Mata, M. N., Martins, J. M., Iqbal, S., Correia, A. B., ... & Farrukh, M. (2021). Trends and future research in electronic marketing: A bibliometric analysis of twenty years. Journal of Theoretical and Applied Electronic Commerce Research, 16(5), 1667-1679. https://doi.org/10.3390/jtaer16050094
• Giroux, M., Kim, J., Lee, J. C., & Park, J. (2022). Artificial intelligence and declined guilt: Retailing morality comparison between human and AI. Journal of Business Ethics, 178(4), 1027-1041. https://doi.org/10.1007/s10551-022-05056-7
• Gülşen, İ. (2019). İşletmelerde yapay zeka uygulamaları ve faydaları: perakende sektöründe bir derleme. Tüketici ve Tüketim Araştırmaları Dergisi, 11(2), 407-436.
• Haleem, A., Javaid, M., Qadri, M. A., Singh, R. P., & Suman, R. (2022). Artificial intelligence (AI) applications for marketing: A literature-based study. International Journal of Intelligent Networks. 3(1), 119-132. https://doi.org/10.1016/j.ijin.2022.08.005
• 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
• Hong, Y. Y., & Hsiao, C. Y. (2002). Locational marginal price forecasting in deregulated electricity markets using artificial intelligence. IEE Proceedings Generation, Transmission and Distribution, 149(5), 621-626. https://doi.org/10.1049/ip gtd:20020371
• Hood, W. W., & Wilson, C. S. (2001). The literature of bibliometrics, scientometrics, and informetrics. Scientometrics, 52, 291-314. https://doi.org/10.1023/A:1017919924342
• Hossain, M. A., Agnihotri, R., Rushan, M. R. I., Rahman, M. S., & Sumi, S. F. (2022). Marketing analytics capability, artificial intelligence adoption, and firms' competitive advantage: evidence from the manufacturing industry. Industrial Marketing Management, 106, 240-255. https://doi.org/10.1016/j.indmarman.2022.08.017
• Huang, M. H., & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49, 30–50. https://doi.org/10.1007/s11747-020-00749-9
• Huang, A. Y., Lu, O. H., & Yang, S. J. (2023). Effects of artificial Intelligence–Enabled personalized recommendations on learners’ learning engagement, motivation, and outcomes in a flipped classroom. Computers & Education, 194, 104684. https://doi.org/10.1016/j.compedu.2022.104684
• Jarek, K. ve Mazurek, G. (2019). Marketing and artificial ıntelligence. Central European Business Review, 8(2), 46-55.
• Kaplan, A. (2021). Artificial intelligence, marketing, and the fourth industrial revolution: criteria, concerns, cases. In Handbook of research on applied AI for international business and marketing applications (pp. 1-13). IGI Global.
• Kumar, V., & Reinartz, W. (2016). Creating enduring customer value. Journal of Marketing, 80(6), 36-68. https://doi.org/10.1509/jm.15.0414
• Kurutkan, M. N., & Orhan, F. (2018). Kalite prensiplerinin görsel haritalama tekniğine göre bibliyometrik analizi. Sage Yayıncılık San. Tic. ve Ltd. Şti, 1, 7-14.
• Kitsios, F., & Kamariotou, M. (2021). Artificial intelligence and business strategy towards digital transformation: A research agenda. Sustainability, 13(4), 2025. https://doi.org/10.3390/su13042025
• Kühl, N., Mühlthaler, M. ve Goutier, M. (2019). Supporting customer-oriented marketing with artificial intelligence: automatically quantifying customer needs from social media. Electronic Markets, OnlineFirst, https://doi.org/10.1007/s12525-019-00351-0.
• 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
• Marr, B. (2023). Amazing Real-World Applications Of AI Everyone Should Know About. https://www.forbes.com/sites/bernardmarr/2023/05/10/15-amazing-real-world applications-of-ai-everyone-should-know-about/?sh=73875efc85e8 (Access Date: 01.08.2023)
• Martínez-López, F. J., & Casillas, J. (2013). Artificial intelligence-based systems applied in industrial marketing: An historical overview, current and future insights. Industrial Marketing Management, 42(4), 489-495. https://doi.org/10.1016/j.indmarman.2013.03.001
• Muñoz-Leiva, F., Sánchez-Fernández, J., Liébana-Cabanillas, F. J., & Martínez Fiestas, M. (2013). Detecting salient themes in financial marketing research from 1961 to 2010, The Service Industries Journal, 33(9-10), 925-940. https://doi.org/10.1080/02642069.2013.719884
• Mustak, M., Salminen, J., Plé, L., & Wirtz, J. (2021). Artificial intelligence in marketing: Topic modeling, scientometric analysis, and research agenda. Journal of Business Research, 124, 389-404. https://doi.org/10.1016/j.jbusres.2020.10.044
• Nabiyev, V. (2012). Yapay Zeka. Ankara: Seçkin Yayıncılık.
• Parvatiyar, A., & Sisodia, R. (Eds.). (2019). Handbook of advances in marketing in an era of disruptions: Essays in Honour of Jagdish N. Sheth. SAGE Publications India.
• Paschen, J., Kietzmann, J., & Kietzmann, T. C. (2019). Artificial intelligence (AI) and its implications for market knowledge in B2B marketing. Journal of business & industrial marketing, 34(7), 1410-1419. https://doi.org/10.1108/JBIM-10 2018-0295
• Păvăloaia, V. D., Anastasiei, I. D., & Fotache, D. (2020). Social media and e-mail marketing campaigns: Symmetry versus convergence. Symmetry, 12(12), 1940. https://doi.org/10.3390/sym12121940
• Pedersen, I., & Duin, A. (2022). AI agents, humans and untangling the marketing of artificial intelligence in learning environments. Proceedings of the 55th Hawaii International Conference On System Sciences.
• Peres, R., Schreier, M., Schweidel, D., & Sorescu, A. (2023). On ChatGPT and beyond: How generative artificial intelligence may affect research, teaching, and practice. International Journal of Research in Marketing, 40(2). https://doi.org/10.1016/j.ijresmar.2023.03.001
• Peyravi, B., Nekrošienė, J., & Lobanova, L. (2020). Revolutionised technologies for marketing: Theoretical review with focus on artificial intelligence. Business: Theory and Practice, 21(2), 827-834.
• Pritchard, A., & Groos, O. V. (1969). Documentation notes, Journal of Documentation, 25(4), 344-349.
• Raiter, O. (2021). Segmentation of bank consumers for artificial intelligence marketing. International Journal of Contemporary Financial Issues, 1(1), 39-54. http://dx.doi.org/10.17613/q0h8-m266
• Rutskiy, V., Mousavi, R., Chudopal, N., Amrani, Y. E., Everstova, V., & Tsarev, R. (2021). Artificial intelligence as a disruptive technology for digital marketing. In Proceedings of the Computational Methods in Systems and Software (pp. 895-900). Cham: Springer International Publishing.
• Schultz, C. D., Koch, C., & Olbrich, R. (2023). Dark sides of artificial intelligence: The dangers of automated decision‐making in search engine advertising. Journal of the Association for Information Science and Technology. https://doi.org/10.1002/asi.24798
• Shah, N., Engineer, S., Bhagat, N., Chauhan, H., & Shah, M. (2020). Research trends on the usage of machine learning and artificial intelligence in advertising. Augmented Human Research, 5, 1-15. https://doi.org/10.1007/s41133-020-00038-8
• Soltani-Fesaghandis, G., & Pooya, A. (2018). Design of an artificial intelligence system for predicting success of new product development and selecting proper market-product strategy in the food industry. International Food and Agribusiness Management Review, 21(7), 847-864. https://doi.org/10.22434/IFAMR2017.0033
• Tchelidze, L. (2019). Potential and skill requirements of artificial intelligence in digital marketing. Calitatea, 20(S3), 73-78.
• Thelwall, M. (2008). Bibliometrics to webometrics. Journal of Information Science. https://doi.org/10.1177/0165551507087238
• Üsdiken, B., & Pasadeos, Y. (1992). Türkiye’de yayınlanan yönetimle ilgili veri temelli makalelerde yöntem. ODTÜ Gelişme Dergisi, 19(2), 249-266.
• Vlačić, B., Corbo, L., e Silva, S. C., & Dabić, M. (2021). The evolving role of artificial intelligence in marketing: A review and research agenda. Journal of Business Research, 128, 187-203. https://doi.org/10.1016/j.jbusres.2021.01.055
• Wang, X., Lin, X., & Shao, B. (2022). How does artificial intelligence create business agility? Evidence from chatbots. International journal of information management, 66, 102535. https://doi.org/10.1016/j.ijinfomgt.2022.102535
• Wirtz, J. (2021), Artificial Intelligence in Marketing: Bibliometric Analysis, Topic Modeling and Research Agenda, Journal of Business Research, (124), 389-404. https://doi.org/10.1016/j.jbusres.2020.10.044