Yapay Zekâ ile Dönüşen Oyun Temelli Reklamcılık: Yeni Nesil Dijital Stratejiler

Yıl 2025, Cilt: 7 Sayı: 2, 344 - 362, 29.12.2025

Mustafa Merdin

https://doi.org/10.53281/kritik.1800828

Öz

Bu çalışma, yapay zekâ (YZ) teknolojilerinin oyun temelli reklamcılık üzerindeki dönüştürücü etkilerini psikolojik, teknolojik ve stratejik boyutlarıyla incelemektedir. Dijital reklamcılık, geleneksel tek yönlü mesaj aktarımından çıkarak, kullanıcıların aktif katılım gösterdiği etkileşimli yapılara evrilmiştir. Bu dönüşümün merkezinde, yapay zekâ destekli oyunlaştırma uygulamaları ve oynanabilir reklamlar yer almaktadır. Oyun temelli reklamcılıkta yapay zekâ, kullanıcı davranışlarını analiz ederek kişiselleştirilmiş ve adaptif içerik stratejileri geliştirmekte, böylece kullanıcı deneyimini dinamik ve katılımcı hâle getirmektedir. Psikolojik Tepkisellik Kuramı çerçevesinde değerlendirilen bulgular, yapay zekâ destekli reklamların özgürlük tehdidi algısını azalttığını, kontrol hissini güçlendirdiğini ve marka algısı üzerinde olumlu etkiler yarattığını göstermektedir. Ayrıca, yapay zekânın duygu analizi, derin öğrenme ve doğal dil işleme teknolojileriyle birleşmesi, reklamcılığın yalnızca bir pazarlama aracı olmaktan çıkıp deneyim temelli bir iletişim biçimine dönüşmesine yol açmıştır. Çalışma, insan-merkezli yapay zekâ uygulamalarının dijital reklamcılığın geleceğinde belirleyici bir rol üstleneceğini vurgulamaktadır.

Anahtar Kelimeler

Yapay Zekâ , Oyun Temelli Reklamcılık , Oyunlaştırma , Oynanabilir Reklamlar , Psikolojik Tepkisellik , Kişiselleştirme , Kullanıcı Deneyimi.

Game-Based Advertising Transformed by Artificial Intelligence: Next-Generation Digital Strategies

Öz

This study explores the transformative impact of artificial intelligence (AI) technologies on game-based advertising through psychological, technological, and strategic perspectives. Digital advertising has evolved from a one-way communication model to interactive systems in which users actively participate. At the center of this transformation lie AI-driven gamification applications and playable ads. In game-based advertising, AI analyzes user behaviors to create personalized and adaptive content strategies, thereby transforming user experience into a dynamic and participatory process. Findings interpreted within the framework of Psychological Reactance Theory indicate that AI-supported advertisements reduce perceived threats to freedom, enhance the sense of control, and positively influence brand perception. Furthermore, the integration of AI with emotion analysis, deep learning, and natural language processing technologies has turned advertising from a mere marketing tool into an experience-based form of communication. The study emphasizes that human-centered AI implementations will play a decisive role in shaping the future of digital advertising.

Anahtar Kelimeler

Artificial intelligence , game-based advertising , gamification , playable ads , psychological reactance , personalization , user experience.

Kaynakça

• Akcan, B. (2021). Kaybolan hikayeler. İçinde A. Gülerarslan Özdengül (Ed.), Hikayenin İletişimi (ss. 397- 406). Nobel.
• Akcan, B. (2023). Tüketim toplumunda reklam okuryazarlığı. İçinde F. B. Aydın-Varol (Ed.), 21. Yüzyılda okuryazarlık ve iletişim (ss. 129-152). Literatürk Academia.
• Arora, N., Dreze, X., Ghose, A., Hess, J. D., Iyengar, R., Jing, B., & Shankar, V. (2008). Putting one-to-one marketing to work: Personalization, customization, and choice. Marketing Letters, 19(3-4), 305-321.
• Bailey, A. A., Dahlen, M., & Engeset, M. G. (2022). Programmatic advertising and the digital consumer: New ethical challenges. Journal of Advertising, 51(1), 102–116.
• Banerjee, S. (2018). Designing compassionate AI systems: Empathy, ethics, and artificial intelligence. Jour- nal of Artificial Intelligence Research, 63, 1101–1120.
• Bang, H., & Wojdynski, B. W. (2016). Tracking users’ responses to native advertising: Insights from eye movement and survey data. Journal of Advertising, 45(2), 166–182.
• Bleier, A., & Eisenbeiss, M. (2015). Personalized online advertising effectiveness: The interplay of what, when, and where. Marketing Science, 34(5), 669-688.
• Boerman, S. C., Kruikemeier, S., & Zuiderveen Borgesius, F. J. (2017). Online behavioral advertising: A lit- erature review and research agenda. Journal of Advertising, 46(3), 363–376.
• Bose, I., & Mahapatra, R. K. (2021). Business data analytics: A machine learning perspective. Information Systems Frontiers, 23(3), 669–690.
• Brehm, J. W. (1966). A theory of psychological reactance. Academic Press.
• Chaffey, D., & Ellis-Chadwick, F. (2019). Digital Marketing. Pearson Education Limited.
• Chatterjee, P., Nguyen, B., Ghosh, B., Bhattacharjee, K. K., & Bhattacharjee, S. (2020). Adoption of ar- tificial intelligence in advertising: A customer perspective. Journal of Consumer Behaviour, 19(5), 529–545.
• Chatterjee, S., Rana, N. P., Tamilmani, K., & Sharma, A. (2020). The era of artificial intelligence and its im- pact on marketing. Journal of Business Research, 120, 474–483.
• Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. Harper & Row.
• Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. Springer Science & Business Media.
• Deterding, S., Dixon, D., Khaled, R., & Nacke, L. (2011). From game design elements to gamefulness: De- fining gamification. Proceedings of the 15th International Academic MindTrek Conference: Envision- ing Future Media Environments, 9–15.
• Deterding, S., Dixon, D., Khaled, R., & Nacke, L. (2011). From game design elements to gamefulness: Defining gamification. In Proceedings of the 15th International Academic MindTrek Conference(pp. 9–15).
• Dwivedi, Y. K., et al. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging chal- lenges, opportunities, and agenda for research, practice and policy. International Journal of Informa- tion Management, 57, 101994.
• Fennis, B. M., & Stroebe, W. (2015). The psychology of advertising. Routledge.
• Fransen, M. L., Smit, E. G., & Verlegh, P. W. J. (2015). Strategies and motives for resistance to persuasion: An integrative framework. Frontiers in Psychology, 6, 1201.
• Gursoy, D., Chi, C. G., Lu, L., & Nunkoo, R. (2022). Consumers acceptance of artificially intelligent (AI) device use in service delivery. International Journal of Hospitality Management, 102, 103119.
• Hamari, J., & Koivisto, J. (2015). “Working out for likes”: An empirical study on social influence in exercise gamification. Computers in Human Behavior, 50, 333–347.
• Hamari, J., & Koivisto, J. (2015). Why do people use gamification services? International Journal of Infor- mation Management, 35(4), 419–431.
• Hamari, J., & Tuunanen, J. (2014). Player types: A meta-synthesis. Transactions of the Digital Games Re- search Association, 1(2).
• Hamari, J., Koivisto, J., & Sarsa, H. (2014). Does gamification work? A literature review of empirical stud- ies on gamification. 47th Hawaii International Conference on System Sciences, 3025–3034.
• Hassenzahl, M. (2010). Experience design: Technology for all the right reasons. Morgan & Claypool Pub- lishers.
• Hou, W., & Xu, H. (2021). Design revolution: AI and environmental design. Advances in Intelligent Systems and Computing, 1253, 431–442. (https://doi.org/10.1007/978-3-030-55057-2_48)
• Irbite, D., & Strode, A. (2021). Artificial Intelligence in design: Challenges and opportunities. In Hu- man Computer Interaction. HCI Applications and Services (s. 381–397). Springer. (https://doi. org/10.1007/978-3-030-78224-9_27)
• Kantar. (2021). Media Reactions 2021: The importance of context and trust in advertising. Kantar Research Report.
• Kaput, M., & Muñoz, J. (2022). AI in advertising: The state of play. Marketing AI Institute.
• Kaput, M., Rowles, D., & Dredge, M. (2020). AI in Marketing: How Artificial Intelligence is Transforming the Marketing Landscape. Kogan Page.
• Kietzmann, J., Paschen, J., & Treen, E. R. (2018). Artificial intelligence in advertising: How marketers can leverage AI. Journal of Advertising Research, 58(3), 263–267.
• Kim, K., Kim, S., & Nam, Y. (2020). Playable ads and their influence on mobile app installs: A field study. Mobile Marketing Review, 6(1), 12–28.
• Knowles, E. S., & Linn, J. A. (2004). Resistance and persuasion. Lawrence Erlbaum Associates.
• Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Pren- tice-Hall.
• Lang, A. (2000). The limited capacity model of mediated message processing. Journal of Communication, 50(1), 46–70.
• Li, Y. (2019). Creative thinking and AI in content generation. International Journal of Emerging Technology and Advanced Engineering, 9(6), 122–127.
• Liu, J. (2022). Symbolic interaction in AI-enhanced graphic design. Journal of Visual Communication, 18(3), 221–234.
• Liu, Y. (2024). Hybrid intelligence in design practice: Human-AI collaboration for sustainable solutions. De- sign Studies, 85, 102544. (https://doi.org/10.1016/j.destud.2023.102544)
• Liu, Y., Alex Wang, Y. J., & Wu, L. (2017). Enhancing consumer experience in digital advertising through gamification. Journal of Interactive Advertising, 17(3), 181–193.
• Liu, Y., Ma, Y., & Xu, H. (2023). Personalization in AI-powered advertising: Review and research agenda. Computers in Human Behavior Reports, 10, 100111.
• Maksoud, N. A. (2024). Automation in design: Enhancing creative processes through AI. Journal of Creative Technologies, 5(1), 15–30.
• Martin, K., & Murphy, P. E. (2017). The role of data privacy in marketing. Journal of the Academy of Mar- keting Science, 45(2), 135–155.
• Nelson, M. R., Keum, H., & Yaros, R. A. (2004). Advertainment or ad creep? Game players’ attitudes toward advertising and product placements in computer games. Journal of Interactive Advertising, 5(1), 3–21. Newzoo. (2023). Global Games Market Report.
• Nissenbaum, H. (2010). Privacy in context: Technology, policy, and the integrity of social life. Stanford Uni- versity Press.
• Picard, R. W. (2000). Affective computing. MIT Press.
• Pine, B. J., & Gilmore, J. H. (1999). The experience economy: Work is theatre & every business a stage. Harvard Business Press.
• Quick, B. L., & Stephenson, M. T. (2008). Examining the role of trait reactance and sensation seeking on perceived threat, state reactance, and reactance restoration. Human Communication Research, 34(3), 448–476.
• Rains, S. A. (2013). The nature of psychological reactance revisited: A meta-analytic review. Human Com- munication Research, 39(1), 47–73.
• Rana, N. P., et al. (2023). Generative AI in digital marketing: Opportunities and challenges. Computers in Human Behavior Reports, 9, 100201.
• Ravaja, N., Saari, T., Salminen, M., Laarni, J., & Kallinen, K. (2006). Phasic emotional reactions to video game events: A psychophysiological investigation. Media Psychology, 8(4), 343–367.
• Ricci, F., Rokach, L., & Shapira, B. (2015). Recommender Systems Handbook. Springer.
• Ringold, D. J. (2002). Boomerang effects in response to public health interventions: Some unintended conse- quences in the alcoholic beverage market. Journal of Consumer Policy, 25(1), 27–63.
• Ryan, R. M., Rigby, C. S., & Przybylski, A. (2006). The motivational pull of video games: A self-determina- tion theory approach. Motivation and Emotion, 30(4), 344–360.
• Sailer, M., Hense, J., Mayr, S. K., & Mandl, H. (2017). How gamification motivates: An experimental study of the effects of specific game design elements on psychological need satisfaction. Computers in Hu- man Behavior, 69, 371–380. Schmitt, B. (1999). Experiential marketing. Journal of Marketing Management, 15(1–3), 53–67.
• Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., Van Den Driessche, G., & Hassabis, D. (2016). Mastering the game of Go with deep neural networks and tree search. Nature, 529(7587), 484–489.
• Silvia, P. J. (2006). Reactance and the dynamics of disagreement: Multiple paths from threatened freedom to resistance to persuasion. European Journal of Social Psychology, 36(5), 673–685.
• Singh, S., Dalal, R., & Pandey, R. (2021). Interactivity in digital advertising: A systematic literature review. Journal of Interactive Advertising, 21(3), 173–189.
• Sundar, S. S., & Marathe, S. S. (2010). Personalization versus customization: The importance of agency, pri- vacy, and power usage. Human Communication Research, 36(3), 298–322.
• Sundar, S. S., Bellur, S., Oh, J., Jia, H., & Kim, H. S. (2014). Theoretical importance of contingency in hu- man–computer interaction: Effects of message interactivity on user engagement. Communication Re- search, 41(5), 595–625.
• Terlutter, R., & Capella, M. L. (2008). The gamification of advertising: An exploratory study. Journal of Ad- vertising Research, 48(1), 92–102.
• Terlutter, R., & Capella, M. L. (2013). The gamification of advertising: Analysis and research directions of in-game advertising, advergames, and advertising in social network games. Journal of Advertising,
• Tucker, C. E. (2014). Social networks, personalized advertising, and privacy controls. Journal of Marketing Research, 51(5), 546–562. Tuten, T. L., & Solomon, M. R. (2017). Social Media Marketing. Sage Publications.
• Vashisht, D., & Pillai, S. (2016). Are they being served? The impact of interactive ads on attitude and pur- chase intention. Journal of Interactive Advertising, 16(2), 111–125.
• Voigt, P., & Von dem Bussche, A. (2017). The EU General Data Protection Regulation (GDPR). Springer. Werbach, K., & Hunter, D. (2012). For the win: How game thinking can revolutionize your business. Whar- ton Digital Press.
• Xu, H. (2011). The effects of personalization on user engagement in advertising: A self-determination theory perspective. Journal of Interactive Advertising, 12(1), 41–56.
• Yan, T. (2023). Exploring new visual languages with AI tools. Digital Art & Design, 29(2), 45–58. Yang, C. C., Smith, R., & Telang, R. (2006). Interactivity and advertising effectiveness. Journal of Interac- tive Marketing, 20(2), 48–60.
• Yin, Z., Zhao, M., & Chen, C. (2020). Emotion-based advertising optimization using deep learning. IEEE Transactions on Affective Computing, 11(1), 86–99.
• Zajonc, R. B. (2001). Mere exposure: A gateway to the subliminal. Current Directions in Psychological Sci- ence, 10(6), 224–228.
• Zhang, H. (2023). Reinforcement learning in NPC behavior modeling. International Journal of Game De- sign and Technology, 11(1), 33–47.
• Zhou, Y., Xu, J., & Zhang, W. (2022). HTML5-based mobile playable advertising: Design challenges and development trends. Interactive Technologies Journal, 8(1), 33–45.
• Zichermann, G., & Cunningham, C. (2011). Gamification by Design: Implementing Game Mechanics in Web and Mobile Apps. O’Reilly Media.