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Reklam Ajanslarının Yapay Zekâ Teknolojilerini Kullanımlarına İlişkin Bir İnceleme

Year 2024, Issue: 16, 19 - 37, 29.06.2024
https://doi.org/10.55609/yenimedya.1434419

Abstract

Bu makale, Türkiye'de reklam sektöründe yapay zekânın benimsenmesi ve kabul edilmesinin arkasındaki mekanizmaları keşfetmeyi amaçlamaktadır. Çalışmada yapay zekâ destekli uygulamaların kullanım alanlarını ve kullanım koşullarını keşfetmek için ajans uygulayıcıları ile teknoloji kabul modelinden yola çıkılarak yarı yapılandırılmış görüşmeler gerçekleştirilmiştir. Katılımcılar, kolayda ve kartopu örnekleme yöntemlerine uygun olarak seçilmiştir. Araştırma sonuçları, literatürün dört ana başlığına ilişkin önemli içgörüler sağlamaktadır. Bunlar: Teknoloji kullanışlılığı, kullanım kolaylığı, teknolojilere yönelik tutumlar ve teknolojilerin kullanımını engelleyen ve kısıtlayan engellerdir. Reklam uygulayıcılarının, yaratıcı üretimlerde yapay zekânın verimliliğe olan katkısını vurgulayarak iş süreçlerinde bu teknolojiyi etkin bir şekilde kullandıkları anlaşılmaktadır. Ancak teknolojiler aktif olarak kullanılırken, arka planda anlama ve keşfetme süreci hala devam etmektedir. Sonuçlar, literatürle uyumlu olarak, reklam ajansı çalışanları ile reklamverenler arasındaki şüpheci yaklaşıma işaret etmektedir. Yapay zekâ araçlarının faydalı ve kullanımının kolay bulunmasının bir sonucu olarak, katılımcıların yapay zekâya yönelik genel tutumlarının olumlu eğilimde olduğu dikkat çekmektedir. Katılımcılar, yapay zekâ tarafından işlerinden olma konusunda herhangi bir endişeleri olmadığını belirtmişlerdir. Bu konudaki güvenlerinin sebebi, YZ'nin ancak insan zekâsı ile işbirliği içinde en verimli haline ulaşabileceği fikrine dayanmaktadır.

Ethical Statement

Bu çalışmanın etik kurul izinleri Yozgat Bozok Üniversitesi Etik Komisyonu'ndan 192371 sayılı 09.01.2024 tarihli 10/18 no'lu karar ile alınmıştır. Çalışmada etik bir sorun olmadığına karar verilmiştir.

References

  • Argan, M., Dinc, H., Kayac, S., & Tokay Argan, M. (2022). Artificial intelligence (AI) in advertising: Understanding and schematizing the behaviors of social media users. Advances in Distributed Computing and Artificial Intelligence Journal, 11(3), 331-348. https://doi.org/10.14201/adcaij.28331.
  • Baryannis, G., Validi, S., Dani, S., & Antoniou, G. (2019). Supply chain risk management and artificial intelligence: State of the art and future research directions. International Journal of Production Research, 57(7), 2179–2202. https://doi.org/10.1080/00207543.2018.1530476
  • Brewerton, P., & Millward, L. (2001). Organizational research methods. Sage.
  • Cao, G., Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2021). Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making. Technovation, 106, https://doi.org/102312.
  • Corbyn, B. (August, 2023). Kreatif yöneticilere göre yapay zekânın 3 ilgi çekici kullanım alanı. https://www.thinkwithgoogle.com/intl/tr-tr/pazarlama-stratejileri/otomasyon/reklam-ogeleri-icin-ai-destekli-araclar/ dated 06.12.2023.
  • Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of ınformation technology. MIS Quarterly, 13(3), 319.
  • Enache, M. C. (2020). AI for Advertising. Annals of the University Dunarea de Jos of Galati: Fascicle: I, Economics & Applied Informatics, 26(1), 28-32. https://doi.org/10.35219/eai1584040978
  • Gansser, O. A., & Reich, C. S. (2021). A new acceptance model for artificial intelligence with extensions to UTAUT2: An empirical study in three segments of application. Technology in Society, 65, 101535. https://doi.org/10.1016/j.techsoc.2021.101535
  • Guda van Noort, Itai Himelboim, Jolie Martin & Tom Collinger (2020). Introducing a Model of Automated Brand-Generated Content in an Era of Computational Advertising, Journal of Advertising, 49:4, 411-427, https://doi.org/10.1080/00913367.2020.1795954
  • Kar, S., Kar, A. K., & Gupta, M. P. (2021). Modeling drivers and barriers of artificial intelligence adoption: Insights from a strategic management perspective. Intelligent Systems in Accounting, Finance and Management, 28(4), 217-238.
  • Kruhse-Lehtonen, U., & Hofmann, D. (2020). How to define and execute your data and AI strategy. Harvard Data Science Review. https://doi. org/10.1162/99608f92.a010feeb
  • Lee, J., Davari, H., Singh, J., and Pandhare, V. (2018). Industrial artificial intelligence for industry 4.0-based manufacturing systems. Manuf. Lett. 18, 20–23. https://doi 10.1016/j.mfglet.2018.09.002
  • Leszczynski, G.; Salamon, K. & Zeilinski, M. (2022). Acceptance of artificial ıntelligence in advertising agencies. 37th International Business-Information-Management Association Conference.
  • Liang, H., Xue, Y. (2009). Avoidance of information technology threats: a theoretical perspective. MIS Quarterly, 71–90.
  • Liang, H., Xue, Y. (2010). Understanding security behaviors in personal computer usage: a threat avoidance perspective. J. Assoc. Inf. Syst. Online, 11 (7), 394–413.
  • Lichtenthaler, U. (2020). Extremes of acceptance: employee attitudes toward artificial intelligence. Journal of Business Strategy, 41(5), 39-45. https://doi.org/10.1108/JBS-12-2018-0204
  • Hairong Li (2019) Special section introduction: Artificial intelligence and advertising. Journal of Advertising, 48(4), 333-337, DOI: 10.1080/00913367.2019.1654947
  • Marangunic’, N., & Granic’. A. (2015). Technology acceptance model: A literature review from 1986 to 2013. Universal Access in the Information Society. 14(1), 81-95.
  • Nam, T. (2019). Technology usage, expected job sustainability, and perceived job insecurity. Technological Forecasting and Social Change, 138, 155–165. https://doi.org/10.1016/j.techfore.2018.08.017
  • Nesterenko, V., & Olefirenko, O. (2023). The impact of AI development on the development of marketing communications. Marketing and Management of Innovations, 1, 169-181. https://doi.org/10.21272/mmi.2023.1-15
  • Olsen, T. L., and Tomlin, B. (2020). Industry 4.0: opportunities and challenges for operations management. Manuf. Serv. Oper. Manag. 22, 113–122. https://doi: 10.1287/msom.2019.0796
  • Pegg, J. (7 Nov 2023). 70+ Top AI Statistics 2023-24: Market, Users, Chatgpt, Gpt-4. https://findweb3.com/posts/ai-statistics dated 13.12.2023.
  • Shank, D.B., Stefanik, C., Stuhlsatz, C., Kacirek, K., & Belfi, A.M. (2022). AI composer bias: Listeners like music less when they think it was composed by an AI. Journal of experimental psychology. Applied.
  • Schuetz, S. & Venkatesh, V. (2020). Research perspectives: the rise of human machines: How cognitive computing systems challenge assumptions of user-system ınteraction. Journal of the Association for Information Systems, 21(2). https://doi: 10.17705/1jais.00608
  • Tarafdar, M., Beath, C. M., & Ross, J. W. (2019). Using AI to enhance business operations. MIT Sloan Manag. Rev. 60, 37–44.
  • Tariq, M. U., Poulin, M., & Abonamah, A. A. (2021). Achieving operational excellence through artificial intelligence: Driving forces and barriers. Frontiers in Psychology, 12, 686624.
  • Tornatzky, L. G., Fleischer, M. & Chakrabarti, A. K. (1990). Processes of Technological Innovation. Lexington books.
  • van Noort, G., Himelboim, I., Martin, J.M., & Collinger, T. (2020). Introducing a model of automated brand-generated content in an era of computational advertising. Journal of Advertising, 49, 411 - 427.
  • Vasiljeva, T., Kreituss, I., & Lulle, I. (2021). Artificial intelligence: the attitude of the public and representatives of various industries. Journal of Risk and Financial Management, 14(8), 339.
  • Yampolskiy, R. V. (2020). On defining differences between intelligence and artificial intelligence. Journal of Artificial General Intelligence, 11(2), 68-70.
  • Yu, Y. (2022). The role and influence of artificial intelligence on advertising industry. Advances in Social Science, Education and Humanities Research. Proceedings of the 2021 International Conference on Social Development and Media Communication. https://doi.org/10.2991/assehr.k.220105.037
  • Williams, M.D., Rana, N.P. and Dwivedi, Y.K. (2015). The unified theory of acceptance and use of technology (UTAUT): A literature review. Journal of Enterprise Information Management, 28(3), 443-488. https://doi.org/10.1108/JEIM-09-2014-0088

An Examination of the Utilization of Artificial Intelligence Technologies by Advertising Agencies

Year 2024, Issue: 16, 19 - 37, 29.06.2024
https://doi.org/10.55609/yenimedya.1434419

Abstract

This article aims to discover the mechanisms behind the adoption and acceptance of AI in advertising industry in Turkey. Semi-structured interviews reflecting technology acceptance literature conducted with agency practitioners to discover the usages and conditions of AI supported applications. Participants are selected in accordance with convenience and snowball sampling methods. The results provide important insights into four main strands of the literature: Technology usefulness, ease of use, attitudes toward technologies and barriers preventing and restricting the use of technologies. It is understood that practitioners effectively utilize AI in their business processes highlighting its contribution to efficiency in creative production. While technologies are being actively utilized, the process of understanding and exploring is still ongoing in the background. In line with the literature, agency practitioners point out the skepticism that exists among advertisers. It is noticable that as a result of finding AI tools useful and easy to use, overall attitude of participants toward AI tend to be positive. Participants asserted that they do not have any concerns about being replaced by AI. Their confidence on this matter seems to be based on the idea that AI could be most efficient in cooperation with human intelligence.

References

  • Argan, M., Dinc, H., Kayac, S., & Tokay Argan, M. (2022). Artificial intelligence (AI) in advertising: Understanding and schematizing the behaviors of social media users. Advances in Distributed Computing and Artificial Intelligence Journal, 11(3), 331-348. https://doi.org/10.14201/adcaij.28331.
  • Baryannis, G., Validi, S., Dani, S., & Antoniou, G. (2019). Supply chain risk management and artificial intelligence: State of the art and future research directions. International Journal of Production Research, 57(7), 2179–2202. https://doi.org/10.1080/00207543.2018.1530476
  • Brewerton, P., & Millward, L. (2001). Organizational research methods. Sage.
  • Cao, G., Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2021). Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making. Technovation, 106, https://doi.org/102312.
  • Corbyn, B. (August, 2023). Kreatif yöneticilere göre yapay zekânın 3 ilgi çekici kullanım alanı. https://www.thinkwithgoogle.com/intl/tr-tr/pazarlama-stratejileri/otomasyon/reklam-ogeleri-icin-ai-destekli-araclar/ dated 06.12.2023.
  • Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of ınformation technology. MIS Quarterly, 13(3), 319.
  • Enache, M. C. (2020). AI for Advertising. Annals of the University Dunarea de Jos of Galati: Fascicle: I, Economics & Applied Informatics, 26(1), 28-32. https://doi.org/10.35219/eai1584040978
  • Gansser, O. A., & Reich, C. S. (2021). A new acceptance model for artificial intelligence with extensions to UTAUT2: An empirical study in three segments of application. Technology in Society, 65, 101535. https://doi.org/10.1016/j.techsoc.2021.101535
  • Guda van Noort, Itai Himelboim, Jolie Martin & Tom Collinger (2020). Introducing a Model of Automated Brand-Generated Content in an Era of Computational Advertising, Journal of Advertising, 49:4, 411-427, https://doi.org/10.1080/00913367.2020.1795954
  • Kar, S., Kar, A. K., & Gupta, M. P. (2021). Modeling drivers and barriers of artificial intelligence adoption: Insights from a strategic management perspective. Intelligent Systems in Accounting, Finance and Management, 28(4), 217-238.
  • Kruhse-Lehtonen, U., & Hofmann, D. (2020). How to define and execute your data and AI strategy. Harvard Data Science Review. https://doi. org/10.1162/99608f92.a010feeb
  • Lee, J., Davari, H., Singh, J., and Pandhare, V. (2018). Industrial artificial intelligence for industry 4.0-based manufacturing systems. Manuf. Lett. 18, 20–23. https://doi 10.1016/j.mfglet.2018.09.002
  • Leszczynski, G.; Salamon, K. & Zeilinski, M. (2022). Acceptance of artificial ıntelligence in advertising agencies. 37th International Business-Information-Management Association Conference.
  • Liang, H., Xue, Y. (2009). Avoidance of information technology threats: a theoretical perspective. MIS Quarterly, 71–90.
  • Liang, H., Xue, Y. (2010). Understanding security behaviors in personal computer usage: a threat avoidance perspective. J. Assoc. Inf. Syst. Online, 11 (7), 394–413.
  • Lichtenthaler, U. (2020). Extremes of acceptance: employee attitudes toward artificial intelligence. Journal of Business Strategy, 41(5), 39-45. https://doi.org/10.1108/JBS-12-2018-0204
  • Hairong Li (2019) Special section introduction: Artificial intelligence and advertising. Journal of Advertising, 48(4), 333-337, DOI: 10.1080/00913367.2019.1654947
  • Marangunic’, N., & Granic’. A. (2015). Technology acceptance model: A literature review from 1986 to 2013. Universal Access in the Information Society. 14(1), 81-95.
  • Nam, T. (2019). Technology usage, expected job sustainability, and perceived job insecurity. Technological Forecasting and Social Change, 138, 155–165. https://doi.org/10.1016/j.techfore.2018.08.017
  • Nesterenko, V., & Olefirenko, O. (2023). The impact of AI development on the development of marketing communications. Marketing and Management of Innovations, 1, 169-181. https://doi.org/10.21272/mmi.2023.1-15
  • Olsen, T. L., and Tomlin, B. (2020). Industry 4.0: opportunities and challenges for operations management. Manuf. Serv. Oper. Manag. 22, 113–122. https://doi: 10.1287/msom.2019.0796
  • Pegg, J. (7 Nov 2023). 70+ Top AI Statistics 2023-24: Market, Users, Chatgpt, Gpt-4. https://findweb3.com/posts/ai-statistics dated 13.12.2023.
  • Shank, D.B., Stefanik, C., Stuhlsatz, C., Kacirek, K., & Belfi, A.M. (2022). AI composer bias: Listeners like music less when they think it was composed by an AI. Journal of experimental psychology. Applied.
  • Schuetz, S. & Venkatesh, V. (2020). Research perspectives: the rise of human machines: How cognitive computing systems challenge assumptions of user-system ınteraction. Journal of the Association for Information Systems, 21(2). https://doi: 10.17705/1jais.00608
  • Tarafdar, M., Beath, C. M., & Ross, J. W. (2019). Using AI to enhance business operations. MIT Sloan Manag. Rev. 60, 37–44.
  • Tariq, M. U., Poulin, M., & Abonamah, A. A. (2021). Achieving operational excellence through artificial intelligence: Driving forces and barriers. Frontiers in Psychology, 12, 686624.
  • Tornatzky, L. G., Fleischer, M. & Chakrabarti, A. K. (1990). Processes of Technological Innovation. Lexington books.
  • van Noort, G., Himelboim, I., Martin, J.M., & Collinger, T. (2020). Introducing a model of automated brand-generated content in an era of computational advertising. Journal of Advertising, 49, 411 - 427.
  • Vasiljeva, T., Kreituss, I., & Lulle, I. (2021). Artificial intelligence: the attitude of the public and representatives of various industries. Journal of Risk and Financial Management, 14(8), 339.
  • Yampolskiy, R. V. (2020). On defining differences between intelligence and artificial intelligence. Journal of Artificial General Intelligence, 11(2), 68-70.
  • Yu, Y. (2022). The role and influence of artificial intelligence on advertising industry. Advances in Social Science, Education and Humanities Research. Proceedings of the 2021 International Conference on Social Development and Media Communication. https://doi.org/10.2991/assehr.k.220105.037
  • Williams, M.D., Rana, N.P. and Dwivedi, Y.K. (2015). The unified theory of acceptance and use of technology (UTAUT): A literature review. Journal of Enterprise Information Management, 28(3), 443-488. https://doi.org/10.1108/JEIM-09-2014-0088
There are 32 citations in total.

Details

Primary Language English
Subjects Communication Studies, New Media
Journal Section Research Articles
Authors

Görkem Bir 0009-0006-7220-4805

Simge Aksu 0000-0002-1818-0455

Early Pub Date June 28, 2024
Publication Date June 29, 2024
Submission Date February 9, 2024
Acceptance Date June 10, 2024
Published in Issue Year 2024 Issue: 16

Cite

APA Bir, G., & Aksu, S. (2024). An Examination of the Utilization of Artificial Intelligence Technologies by Advertising Agencies. Yeni Medya(16), 19-37. https://doi.org/10.55609/yenimedya.1434419