Araştırma Makalesi
BibTex RIS Kaynak Göster

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

Yıl 2024, Cilt: 5 Sayı: 2, 83 - 104

Öznur Aktaş

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

Öz

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.

Anahtar Kelimeler

Yapay Zekâ (AI) Influencer Bibliyometrik Analiz Bibliyometri Influencer Pazarlama

Kaynakça

  • 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.
  • Freberg, K., Graham, K., McGaughey, K., & Freberg, L. A. (2011). Who are the social media influencers? A study of public perceptions of personality. Public Relations Review, 37(1), 90-92. https://doi.org/10.1016/Jpubrev.2010.11.001
  • 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.
  • 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.
  • Grewal, D., Hulland, J., Kopalle, P. K., & Karahanna, E. (2020). The future of technology and marketing: A multidisciplinary perspective. Journal of the Academy of Marketing Science, 48, 1-8.
  • Guerini, M., Strapparava, C., & Ozbal, G. (2011). Exploring text virality in social networks. In Proceedings Of The İnternational AAAI Conference on Web and Social Media, 5(1), 506-509. https://doi.org/10.1609/icwsm.v5i1.14169
  • Hall, J. (2015). Build authentic audience experiences through influencer marketing. Retrieved from: https://www.forbes.com/sites/johnhall/2015/12/17/buildauthentic-audience-experiences-through-influencer-marketing/#5f75d5624ff2 Retrieved date: 11/06/2024
  • Hamilton, R., Ferraro, R., Haws, K. L., & Mukhopadhyay, A. (2021). Traveling with companions: The social customer journey. Journal of Marketing, 85(1), 68-92. https://doi.org/10.1177/0022242920908227
  • Hanson, S. (2020). Artificial intelligence software market to reach $126.0 billion in annual worldwide revenue by 2025, according to Tractica. Retrieved from: https://www.omdia.com/newsroom/press-releases/artificial-intelligence-software-market-toreach-126-0-billion-in-annual-worldwide-revenue-by-2025, Retrieved date: 11/06/2024
  • Hatzius, J. (2023). The potentially large effects of artificial ıntelligence on economic growth (briggs/kodnani). Goldman Sachs, 1.
  • Hillyer, H. (2019). The Rise of the robots: How virtual influencers are taking over instagram, Image.ie. Retrieved from: https://www.image.ie/amp/life/rise-virtual-influencers-fake-cgi-real-154227 Retrieved date: 16/06/2024
  • Jarek, K., & Mazurek, G. (2019). Marketing and artificial intelligence. Central European Business Review, 8(2).
  • Kim, J., Kang, S., & Lee, K. H. (2021). Evolution of digital marketing communication: Bibliometric analysis and network visualization from key articles. Journal of Business Research, 130, 552-563. https://doi.org/10.1016/j.jbusres.2019.09.043
  • Kim, S., Bak, J., & Oh, A. (2012). Do you feel what i feel? social aspects of emotions in twitter conversations. In Proceedings of the International AAAI Conference on Web and Social Media, 6(1), 495-498.
  • Kiss, C., & Bichler, M. (2008). Identification of influencers—measuring influence in customer networks. Decision Support Systems, 46(1), 233-253. https://doi.org/10.1016/j.dss.2008.06.007
  • Koutanaei, F. N., Sajedi, H., & Khanbabaei, M. (2015). A hybrid data mining model of feature selection algorithms and ensemble learning classifiers for credit scoring. Journal of Retailing and Consumer Services, 27, 11-23. https://doi.org/10.1016/j.jretconser.2015.07.003
  • Köbis, N., Bonnefon, J. F., & Rahwan, I. (2021). Bad machines corrupt good morals. Nature Human Behaviour, 5(6), 679-685.
  • Köksal, Y., & Özdemir, Ş. (2013). Bir iletişim aracı olarak sosyal medya’nın tutundurma karması içerisindeki yeri üzerine bir inceleme. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 18(1), 323-337.
  • Lalicic, L., & Weismayer, C. (2021). Consumers’ reasons and perceived value co-creation of using artificial intelligence-enabled travel service agents. Journal of Business Research, 129, 891-901. https://doi.org/10.1016/j.jbusres.2020.11.005
  • Lieto, A., Bhatt, M., Oltramari, A., & Vernon, D. (2018). The role of cognitive architectures in general artificial intelligence. Cognitive Systems Research, 48, 1-3. https://doi.org/10.1016/j.cogsys.2017.08.003
  • Lou, C., & Yuan, S. (2019). Influencer marketing: How message value and credibility affect consumer trust of branded content on social media. Journal of Interactive Advertising, 19(1), 58-73. https://doi.org/10.1080/15252019.2018.1533501
  • Lou, C., Kiew, S. T. J., Chen, T., Lee, T. Y. M., Ong, J. E. C., & Phua, Z. (2023). Authentically fake? How consumers respond to the influence of virtual influencers. Journal of Advertising, 52(4), 540-557.
  • Mavnacıoğlu, K. (2013). Kurumsal iletişimde sosyal medya yönetimi: İletişim sektöründe sosyal medya yönetiminin algılanmasına yönelik bir analiz. Sosyal Medya Araştırmaları, Sosyalleşen Birey 1. https://hdl.handle.net/20.500.12294/774
  • Mazurek, G. (2014). Network value creation through marketing, management & business administration. Central Europe, 22(4), 70-77.
  • Nanji, A. (2017). The State Of Influencer Marketing İn 2017. Retrieved From: https://www.marketingprofs.com/ charts/2017/31524/the-state-of-influencer-marketing in-2017 Retrieved date: 11/06/2024
  • Özçelik, A. B., & Varnalı, K. (2019). Effectiveness of online behavioral targeting: A psychological perspective. Electronic Commerce Research and Applications, 33, 100819. https://doi.org/10.1016/j.elerap.2018.11.006
  • Pitt, C., Mulvey, M., & Kietzmann, J. (2018). Quantitative insights from online qualitative data: An example from the health care sector. Psychology And Marketing, 35(12), 1010–1017. https://doi.org/ 10.1002/Mar.21152
  • Purnat, T. D., Vacca, P., Czerniak, C., Ball, S., Burzo, S., Zecchin, T., & Nguyen, T. (2021). Infodemic signal detection during the COVID-19 Pandemic: Development of a methodology for identifying potential information voids in online conversations. JMIR Infodemiology, 1(1), E30971.
  • 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
  • Roelens, I., Baecke, P., & Benoit, D. F. (2016). Identifying influencers in a social network: The value of real referral data. Decision Support Systems, 91, 25-36. https://doi.org/10.1016/j.dss.2016.07.005
  • Saima, & Khan, M. A. (2020). Effect of social media influencer marketing on consumers’ purchase intention and the mediating role of credibility. Journal of Promotion Management, 27(4), 503-523. https://doi.org/10.1080/10496491.2020.1851847
  • Sands, S., Campbell, C. L., Plangger, K., & Ferraro, C. (2022). Unreal influence: Leveraging AI in influencer marketing. European Journal of Marketing, 56(6), 1721-1747. https://doi.org/10.1108/EJM-12-2019-0949
  • Sands, S., Ferraro, C., Demsar, V., & Chandler, G. (2022). False idols: Unpacking the opportunities and challenges of falsity in the context of virtual influencers. Business Horizons, 65(6), 777-788. https://doi.org/10.1016/j.bushor.2022.08.002
  • Shankar, V. (2018). How AI is reshaping retailing. Journal of Retailing, 94(4), 6-11.
  • Simon, J. P. (2019). Artificial intelligence: Scope, players, markets and geography. Digital Policy, Regulation and Governance, 21(3), 208–237.
  • Sun, Y., Wang, R., Cao, D., & Lee, R. (2022). Who are social media influencers for luxury fashion consumption of the Chinese Gen Z? Categorisation and empirical examination. Journal of Fashion Marketing and Management: An International Journal, 26(4), 603-621. https://doi.org/10.1108/JFMM-07-2020-0132
  • Thakur, J., & Kushwaha, B. P. (2024). Artificial intelligence in marketing research and future research directions: Science mapping and research clustering using bibliometric analysis. Global Business and Organizational Excellence, 43(3), 139-155. https://doi.org/10.1002/joe.22233
  • Thomas, V. L., & Fowler, K. (2021). Close encounters of the AI kind: Use of AI influencers as brand endorsers. Journal of Advertising, 50(1), 11-25. https://doi.org/10.1080/00913367.2020.1810595
  • Varsha, P. S., Akter, 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 (JGIM), 29(4), 221-246.
  • Verma, S., Sharma, R., Deb, S., & Maitra, D. (2021). Artificial intelligence in marketing: Systematic review and future research direction. International Journal of Information Management Data Insights, 1(1), 100002. https://doi.org/10.1016/j.jjimei.2020.100002
  • Vuong, Q. H., Ho, M. T., Vuong, T. T., La, V. P., Ho, M. T., Nghiem, K. C. P., ... & Ho, R. C. (2019). Artificial intelligence vs. natural stupidity: Evaluating AI readiness for the vietnamese medical information system. Journal of Clinical Medicine, 8(2), 168. https://doi.org/10.3390/jcm8020168
  • Wen, T., & Deng, Y. (2020). Identification of influencers in complex networks by local information dimensionality. Information Sciences, 512, 549-562. https://doi.org/10.1016/j.ins.2019.10.003
  • Yeo, S. F., Tan, C. L., Kumar, A., Tan, K. H., & Wong, J. K. (2022). Investigating the impact of AI-Powered technologies on ınstagrammers’ purchase decisions in digitalization era–a study of the fashion and apparel industry. Technological Forecasting And Social Change, 177, 121551. https://doi.org/10.1016/j.techfore.2022.121551

Yapay Zekâ ve Influencer Pazarlamasının Kesişiminin Bibliyometrik Analiz ile İncelenmesi

Yıl 2024, Cilt: 5 Sayı: 2, 83 - 104

Öznur Aktaş

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

Öz

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.

Anahtar Kelimeler

Yapay Zekâ (AI) Influencer Bibliyometrik Analiz Bibliyometri Influencer Pazarlama

Etik Beyan

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

Kaynakça

  • 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.
  • Freberg, K., Graham, K., McGaughey, K., & Freberg, L. A. (2011). Who are the social media influencers? A study of public perceptions of personality. Public Relations Review, 37(1), 90-92. https://doi.org/10.1016/Jpubrev.2010.11.001
  • 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.
  • 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.
  • Grewal, D., Hulland, J., Kopalle, P. K., & Karahanna, E. (2020). The future of technology and marketing: A multidisciplinary perspective. Journal of the Academy of Marketing Science, 48, 1-8.
  • Guerini, M., Strapparava, C., & Ozbal, G. (2011). Exploring text virality in social networks. In Proceedings Of The İnternational AAAI Conference on Web and Social Media, 5(1), 506-509. https://doi.org/10.1609/icwsm.v5i1.14169
  • Hall, J. (2015). Build authentic audience experiences through influencer marketing. Retrieved from: https://www.forbes.com/sites/johnhall/2015/12/17/buildauthentic-audience-experiences-through-influencer-marketing/#5f75d5624ff2 Retrieved date: 11/06/2024
  • Hamilton, R., Ferraro, R., Haws, K. L., & Mukhopadhyay, A. (2021). Traveling with companions: The social customer journey. Journal of Marketing, 85(1), 68-92. https://doi.org/10.1177/0022242920908227
  • Hanson, S. (2020). Artificial intelligence software market to reach $126.0 billion in annual worldwide revenue by 2025, according to Tractica. Retrieved from: https://www.omdia.com/newsroom/press-releases/artificial-intelligence-software-market-toreach-126-0-billion-in-annual-worldwide-revenue-by-2025, Retrieved date: 11/06/2024
  • Hatzius, J. (2023). The potentially large effects of artificial ıntelligence on economic growth (briggs/kodnani). Goldman Sachs, 1.
  • Hillyer, H. (2019). The Rise of the robots: How virtual influencers are taking over instagram, Image.ie. Retrieved from: https://www.image.ie/amp/life/rise-virtual-influencers-fake-cgi-real-154227 Retrieved date: 16/06/2024
  • Jarek, K., & Mazurek, G. (2019). Marketing and artificial intelligence. Central European Business Review, 8(2).
  • Kim, J., Kang, S., & Lee, K. H. (2021). Evolution of digital marketing communication: Bibliometric analysis and network visualization from key articles. Journal of Business Research, 130, 552-563. https://doi.org/10.1016/j.jbusres.2019.09.043
  • Kim, S., Bak, J., & Oh, A. (2012). Do you feel what i feel? social aspects of emotions in twitter conversations. In Proceedings of the International AAAI Conference on Web and Social Media, 6(1), 495-498.
  • Kiss, C., & Bichler, M. (2008). Identification of influencers—measuring influence in customer networks. Decision Support Systems, 46(1), 233-253. https://doi.org/10.1016/j.dss.2008.06.007
  • Koutanaei, F. N., Sajedi, H., & Khanbabaei, M. (2015). A hybrid data mining model of feature selection algorithms and ensemble learning classifiers for credit scoring. Journal of Retailing and Consumer Services, 27, 11-23. https://doi.org/10.1016/j.jretconser.2015.07.003
  • Köbis, N., Bonnefon, J. F., & Rahwan, I. (2021). Bad machines corrupt good morals. Nature Human Behaviour, 5(6), 679-685.
  • Köksal, Y., & Özdemir, Ş. (2013). Bir iletişim aracı olarak sosyal medya’nın tutundurma karması içerisindeki yeri üzerine bir inceleme. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 18(1), 323-337.
  • Lalicic, L., & Weismayer, C. (2021). Consumers’ reasons and perceived value co-creation of using artificial intelligence-enabled travel service agents. Journal of Business Research, 129, 891-901. https://doi.org/10.1016/j.jbusres.2020.11.005
  • Lieto, A., Bhatt, M., Oltramari, A., & Vernon, D. (2018). The role of cognitive architectures in general artificial intelligence. Cognitive Systems Research, 48, 1-3. https://doi.org/10.1016/j.cogsys.2017.08.003
  • Lou, C., & Yuan, S. (2019). Influencer marketing: How message value and credibility affect consumer trust of branded content on social media. Journal of Interactive Advertising, 19(1), 58-73. https://doi.org/10.1080/15252019.2018.1533501
  • Lou, C., Kiew, S. T. J., Chen, T., Lee, T. Y. M., Ong, J. E. C., & Phua, Z. (2023). Authentically fake? How consumers respond to the influence of virtual influencers. Journal of Advertising, 52(4), 540-557.
  • Mavnacıoğlu, K. (2013). Kurumsal iletişimde sosyal medya yönetimi: İletişim sektöründe sosyal medya yönetiminin algılanmasına yönelik bir analiz. Sosyal Medya Araştırmaları, Sosyalleşen Birey 1. https://hdl.handle.net/20.500.12294/774
  • Mazurek, G. (2014). Network value creation through marketing, management & business administration. Central Europe, 22(4), 70-77.
  • Nanji, A. (2017). The State Of Influencer Marketing İn 2017. Retrieved From: https://www.marketingprofs.com/ charts/2017/31524/the-state-of-influencer-marketing in-2017 Retrieved date: 11/06/2024
  • Özçelik, A. B., & Varnalı, K. (2019). Effectiveness of online behavioral targeting: A psychological perspective. Electronic Commerce Research and Applications, 33, 100819. https://doi.org/10.1016/j.elerap.2018.11.006
  • Pitt, C., Mulvey, M., & Kietzmann, J. (2018). Quantitative insights from online qualitative data: An example from the health care sector. Psychology And Marketing, 35(12), 1010–1017. https://doi.org/ 10.1002/Mar.21152
  • Purnat, T. D., Vacca, P., Czerniak, C., Ball, S., Burzo, S., Zecchin, T., & Nguyen, T. (2021). Infodemic signal detection during the COVID-19 Pandemic: Development of a methodology for identifying potential information voids in online conversations. JMIR Infodemiology, 1(1), E30971.
  • 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
  • Roelens, I., Baecke, P., & Benoit, D. F. (2016). Identifying influencers in a social network: The value of real referral data. Decision Support Systems, 91, 25-36. https://doi.org/10.1016/j.dss.2016.07.005
  • Saima, & Khan, M. A. (2020). Effect of social media influencer marketing on consumers’ purchase intention and the mediating role of credibility. Journal of Promotion Management, 27(4), 503-523. https://doi.org/10.1080/10496491.2020.1851847
  • Sands, S., Campbell, C. L., Plangger, K., & Ferraro, C. (2022). Unreal influence: Leveraging AI in influencer marketing. European Journal of Marketing, 56(6), 1721-1747. https://doi.org/10.1108/EJM-12-2019-0949
  • Sands, S., Ferraro, C., Demsar, V., & Chandler, G. (2022). False idols: Unpacking the opportunities and challenges of falsity in the context of virtual influencers. Business Horizons, 65(6), 777-788. https://doi.org/10.1016/j.bushor.2022.08.002
  • Shankar, V. (2018). How AI is reshaping retailing. Journal of Retailing, 94(4), 6-11.
  • Simon, J. P. (2019). Artificial intelligence: Scope, players, markets and geography. Digital Policy, Regulation and Governance, 21(3), 208–237.
  • Sun, Y., Wang, R., Cao, D., & Lee, R. (2022). Who are social media influencers for luxury fashion consumption of the Chinese Gen Z? Categorisation and empirical examination. Journal of Fashion Marketing and Management: An International Journal, 26(4), 603-621. https://doi.org/10.1108/JFMM-07-2020-0132
  • Thakur, J., & Kushwaha, B. P. (2024). Artificial intelligence in marketing research and future research directions: Science mapping and research clustering using bibliometric analysis. Global Business and Organizational Excellence, 43(3), 139-155. https://doi.org/10.1002/joe.22233
  • Thomas, V. L., & Fowler, K. (2021). Close encounters of the AI kind: Use of AI influencers as brand endorsers. Journal of Advertising, 50(1), 11-25. https://doi.org/10.1080/00913367.2020.1810595
  • Varsha, P. S., Akter, 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 (JGIM), 29(4), 221-246.
  • Verma, S., Sharma, R., Deb, S., & Maitra, D. (2021). Artificial intelligence in marketing: Systematic review and future research direction. International Journal of Information Management Data Insights, 1(1), 100002. https://doi.org/10.1016/j.jjimei.2020.100002
  • Vuong, Q. H., Ho, M. T., Vuong, T. T., La, V. P., Ho, M. T., Nghiem, K. C. P., ... & Ho, R. C. (2019). Artificial intelligence vs. natural stupidity: Evaluating AI readiness for the vietnamese medical information system. Journal of Clinical Medicine, 8(2), 168. https://doi.org/10.3390/jcm8020168
  • Wen, T., & Deng, Y. (2020). Identification of influencers in complex networks by local information dimensionality. Information Sciences, 512, 549-562. https://doi.org/10.1016/j.ins.2019.10.003
  • Yeo, S. F., Tan, C. L., Kumar, A., Tan, K. H., & Wong, J. K. (2022). Investigating the impact of AI-Powered technologies on ınstagrammers’ purchase decisions in digitalization era–a study of the fashion and apparel industry. Technological Forecasting And Social Change, 177, 121551. https://doi.org/10.1016/j.techfore.2022.121551
Toplam 67 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Yapay Zeka (Diğer), Dijital Pazarlama, Tüketici Davranışı
Bölüm Araştırma Makaleleri
Yazarlar

Öznur Aktaş

Erken Görünüm Tarihi 18 Kasım 2024
Yayımlanma Tarihi
Gönderilme Tarihi 27 Haziran 2024
Kabul Tarihi 28 Ekim 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 5 Sayı: 2

Kaynak Göster

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
 Kapak Resmi İndir

Dizinler (Indexing)

31143 21387  3122531320257993114421388  21386  24076 28325 28331 28684