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Journals / Uluslararası Anadolu Sosyal Bilimler Dergisi (Internatıonal Anatolian Social Sciences Journal) / 2026 / Cilt: 10 Sayı: 3

THE IMPACT OF AI WASHING PRACTICES ON CONSUMER-BASED BRAND EQUITY IN DIGITAL MARKETING: A CONCEPTUAL REVIEW OF THE MEDIATING ROLE OF AI BOOING

DİJİTAL PAZARLAMADA AI WASHING UYGULAMALARININ TÜKETİCİ TEMELLİ MARKA DEĞERİ ÜZERİNDEKİ ETKİSİ: AI BOOING'İN ARACI ROLÜNE İLİŞKİN KAVRAMSAL BİR İNCELEME

Bülent Şen(TOKAT GAZİOSMANPAŞA ÜNİVERSİTESİ)0000-0001-8561-8173
Pages
523–533
Publication Date
2026-09-30
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

As one of the first studies to conceptually integrate the relationship between AI Washing and brand equity, it develops propositions regarding the mediating role of AI Booing, offers implications for digital marketing managers on responsible AI communication strategies, and puts forward a testable conceptual model for future empirical research.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study aims to examine the impact of AI Washing practices on consumer-based brand equity (CBBE) in the context of digital marketing, with AI Booing as a mediating variable.
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Key Findings & Data:The research proposes an original conceptual model integrating Keller's (1993) consumer-based brand equity framework with Ozturkcan and Bozdağ's (2025) AI Washing–AI Booing cycle of mistrust.
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Conclusion & Impact:As one of the first studies to conceptually integrate the relationship between AI Washing and brand equity, it develops propositions regarding the mediating role of AI Booing, offers implications for digital marketing managers on responsible AI communication strategies, and puts forward a testable conceptual model for future empirical research.
🔬Design:Review & Systematic Survey
📍Scope:2025 Verileri
⚙️Variables:AI Washing · AI Booing · Tüketici Temelli Marka Değeri

Abstract

This study aims to examine the impact of AI Washing practices on consumer-based brand equity (CBBE) in the context of digital marketing, with AI Booing as a mediating variable. The instrumentalization of artificial intelligence technologies in marketing communication has led companies to position their brands with claims exceeding their actual AI capabilities, thereby threatening brand equity through the erosion of consumer trust. The research proposes an original conceptual model integrating Keller's (1993) consumer-based brand equity framework with Ozturkcan and Bozdağ's (2025) AI Washing–AI Booing cycle of mistrust. Accordingly, drawing on the greenwashing, ethics washing, and CSR-washing literatures, the study adopts an integrative review approach to examine the relationships among AI Washing, AI Booing, and consumer-based brand equity through a proposed conceptual framework. As one of the first studies to conceptually integrate the relationship between AI Washing and brand equity, it develops propositions regarding the mediating role of AI Booing, offers implications for digital marketing managers on responsible AI communication strategies, and puts forward a testable conceptual model for future empirical research.

Özet

Bu çalışma, dijital pazarlama bağlamında AI Washing (yapay zekâ yıkama) uygulamalarının tüketici temelli marka değeri üzerindeki etkisini, AI Booing (yapay zekâya tepki) olgusunun aracı rolü çerçevesinde incelemeyi amaçlamaktadır. Yapay zekâ teknolojilerinin pazarlama iletişiminde araçsallaştırılması, şirketlerin gerçek YZ kapasitelerini aşan iddialarla marka konumlandırması yapmasına yol açmakta; bu durum ise tüketici güvenini erozyona uğratarak marka değerini tehdit etmektedir. Araştırma, Keller'ın (1993) tüketici temelli marka değeri modeli ile Ozturkcan ve Bozdağ'ın (2025) AI Washing-AI Booing güvensizlik döngüsü çerçevesini bütünleştiren özgün bir kavramsal model önermektedir. Bu doğrultuda çalışma; greenwashing, ethics washing ve CSR-washing yazınlarından beslenen kavramsal bir çerçeve önererek AI Washing, AI Booing ve tüketici temelli marka değeri arasındaki ilişkileri bütünleştirici bir derleme yaklaşımıyla ele almaktadır. Çalışma, AI Washing ile marka değeri arasındaki ilişkiyi kavramsal düzeyde bütünleştiren ilk çalışmalardan biri olarak AI Booing'in bu ilişkideki aracı rolüne dair önermeler geliştirmekte; dijital pazarlama yöneticilerine sorumlu YZ iletişim stratejileri konusunda çıkarımlar sunmakta ve ileride yürütülecek görgül araştırmalar için sınanabilir bir kavramsal model ortaya koymaktadır.

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Cite This Article

Şen, B. (2026). THE IMPACT OF AI WASHING PRACTICES ON CONSUMER-BASED BRAND EQUITY IN DIGITAL MARKETING: A CONCEPTUAL REVIEW OF THE MEDIATING ROLE OF AI BOOING. Uluslararası Anadolu Sosyal Bilimler Dergisi (Internatıonal Anatolian Social Sciences Journal), Cilt: 10 Sayı: 3, 523–533. https://doi.org/10.47525/ulasbid.1985312

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References (38)

  1. Aaker, D. A. (1991). Managing brand equity: Capitalizing on the value of a brand name. Free Press.
  2. Ahluwalia, R., Burnkrant, R. E. ve Unnava, H. R. (2000). Consumer response to negative publicity: The moderating role of commitment. Journal of Marketing Research, 37(2), 203–214. [https://doi.org/10.1509/jmkr.37.2.203.18734](https://doi.org/10.1509/jmkr.37.2.203.18734)
  3. Appel, G., Grewal, L., Hadi, R. ve Stephen, A. T. (2020). The future of social media in marketing. Journal of the Academy of Marketing Science, 48(1), 79–95.
  4. Bitektine, A. ve Haack, P. (2015). The “macro” and the “micro” of legitimacy: Toward a multilevel theory of the legitimacy process. Academy of Management Review, 40(1), 49–75.
  5. Boston Consulting Group [BCG]. (2025, 12 Aralık). Building lasting brand equity in the age of AI. [https://www.bcg.com/publications/2025/building-lasting-brand-equity-in-the-age-of-ai](https://www.bcg.com/publications/2025/building-lasting-brand-equity-in-the-age-of-ai)
  6. Chakraborty, A. ve Harbaugh, R. (2010). Persuasion by cheap talk. American Economic Review, 100(5), 2361–2382.
  7. Cisco. (2024). 2024 Cisco consumer privacy survey. Cisco Systems. [https://www.cisco.com/c/en/us/about/trust-center/consumer-privacy-survey.html](https://www.cisco.com/c/en/us/about/trust-center/consumer-privacy-survey.html)
  8. Delmas, M. A. ve Burbano, V. C. (2011). The drivers of greenwashing. California Management Review, 54(1), 64–87.
  9. Dietvorst, B. J., Simmons, J. P. ve Massey, C. (2015). Algorithm aversion: People erroneously avoid algorithms after seeing them err. Journal of Experimental Psychology: General, 144(1), 114.
  10. Du, X. (2015). How the market values greenwashing? Evidence from China. Journal of Business Ethics, 128(3), 547–574.
  11. Elhajjar, S. ve Itani, O. S. (2025). AI washing: A conceptual exploration. AMS Review. [https://doi.org/10.1007/s13162-025-00323-y](https://doi.org/10.1007/s13162-025-00323-y)
  12. Festinger, L. (1957). A theory of cognitive dissonance. Stanford University Press.
  13. Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V.,. ve Vayena, E. (2018). AI4People—An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and Machines, 28(4), 689–707.
  14. Gartner. (2026, 16 Mart). Gartner marketing survey finds 50% of consumers prefer brands that avoid using GenAI in consumer-facing content [Basın bülteni]. [https://www.gartner.com/en/newsroom/press-releases/2026-03-16-gartner-marketing-survey-finds-50-percent-of-consumers-prefer-brands-that-avoid-using-genai-in-consumer-facing-content](https://www.gartner.com/en/newsroom/press-releases/2026-03-16-gartner-marketing-survey-finds-50-percent-of-consumers-prefer-brands-that-avoid-using-genai-in-consumer-facing-content)
  15. Grégoire, Y. ve Fisher, R. J. (2008). Customer betrayal and retaliation: When your best customers become your worst enemies. Journal of the Academy of Marketing Science, 36(2), 247–261. [https://doi.org/10.1007/s11747-007-0054-0](https://doi.org/10.1007/s11747-007-0054-0)
  16. Hardin, G. (1968). The tragedy of the commons. Science, 162(3859), 1243–1248.
  17. Huang, M. H. ve Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49(1), 30–50.
  18. Hue, T. T., Nguyen, K. L. ve Le, H. L. (2026). Impact of artificial intelligence on brand equity: Primary schools of thought and future research directions. İçinde A. Elbanna, M. Janssen, Y. K. Dwivedi, M. Hossain ve A. S. Islind (Ed.), Digital adoption, diffusion and innovation in the augmented and digital society: TDIT 2025. IFIP Advances in Information and Communication Technology (Cilt 779, ss. 1–15). Springer. [https://doi.org/10.1007/978-3-032-16779-8_22](https://doi.org/10.1007/978-3-032-16779-8_22)
  19. Keller, K. L. (1993). Conceptualizing, measuring, and managing customer-based brand equity. Journal of Marketing, 57(1), 1–22.
  20. LaGrandeur, K. (2024). The consequences of AI hype. AI and Ethics, 4(3), 653–656.
  21. Laupichler, M. C., Knoth, N., Schleiss, J. ve Raupach, T. (2025). Algorithm aversion revisited: The role of AI literacy and attitudes towards AI in shaping perceptions of AI-generated texts. British Journal of Educational Technology. [https://doi.org/10.1111/bjet.70035](https://doi.org/10.1111/bjet.70035)
  22. Laufer, W. S. (2003). Social accountability and corporate greenwashing. Journal of Business Ethics, 43, 253–261.
  23. Leffrang, D. ve Mueller, O. (2023). AI washing: The framing effect of labels on algorithmic advice utilization. Proceedings of the International Conference on Information Systems (ICIS).
  24. McKinsey & Company. (2025, 22 Temmuz). McKinsey technology trends outlook 2025. [https://www.mckinsey.com/capabilities/tech-and-ai/our-insights/the-top-trends-in-tech](https://www.mckinsey.com/capabilities/tech-and-ai/our-insights/the-top-trends-in-tech)
  25. Metzinger, T. (2019, 8 Nisan). Ethics washing made in Europe. Tagesspiegel.
  26. Noor, J. (2026). AI washing: How firms use artificial intelligence narratives to mask offshoring, recessionary cost-cutting, and post-pandemic restructuring. SSRN Working Paper. [https://doi.org/10.2139/ssrn.6523802](https://doi.org/10.2139/ssrn.6523802)
  27. Nyilasy, G. ve Gangadharbatla, H. (2025). AI-washing: The asymmetric effects of its two types on consumer moral judgments. arXiv preprint arXiv:2507.04352. [https://arxiv.org/abs/2507.04352](https://arxiv.org/abs/2507.04352)
  28. Ozturkcan, S. ve Bozdağ, A. A. (2025). Responsible AI in marketing: AI booing and AI washing cycle of AI mistrust. International Journal of Market Research, 67(6), 696–722. [https://doi.org/10.1177/14707853251379285](https://doi.org/10.1177/14707853251379285)
  29. Petty, R. E. ve Cacioppo, J. T. (1986). The elaboration likelihood model of persuasion. İçinde L. Berkowitz (Ed.), Advances in experimental social psychology (Cilt 19, ss. 123–205). Academic Press.
  30. Pinch, T. J. ve Bijker, W. E. (1984). The social construction of facts and artefacts: Or how the sociology of science and the sociology of technology might benefit each other. Social Studies of Science, 14(3), 399–441.
  31. Pope, S. ve Wæraas, A. (2016). CSR-washing is rare: A conceptual framework, literature review, and critique. Journal of Business Ethics, 137, 173–193.
  32. Rogers, E. M. (1962). Diffusion of innovations. Free Press.
  33. Seele, P. ve Schultz, M. D. (2022). From greenwashing to machinewashing: A model and future directions derived from reasoning by analogy. Journal of Business Ethics, 178(4), 1063–1089. [https://doi.org/10.1007/s10551-022-05054-9](https://doi.org/10.1007/s10551-022-05054-9)
  34. Song, X., Hou, W., Hao, F. ve Ouyang, Z. (2026). AI washing: Strategic disclosure and backlash. Finance Research Letters, 95, 1–8. [https://doi.org/10.1016/j.frl.2026.109684](https://doi.org/10.1016/j.frl.2026.109684)
  35. Spence, M. (1978). Job market signaling. İçinde P. Diamond ve M. Rothschild (Ed.), Uncertainty in economics (ss. 281–306). Academic Press.
  36. Spence, M. (2002). Signaling in retrospect and the informational structure of markets. American Economic Review, 92(3), 434–459.
  37. Sun, Z., Wen, Y., Zhao, L., Almugren, I. ve Galgotia, A. (2026). Unveiling AI washing: Bridging corporate technological gaps through a cognitive dissonance lens. Technological Forecasting and Social Change, 225, 124511. [https://doi.org/10.1016/j.techfore.2025.124511](https://doi.org/10.1016/j.techfore.2025.124511)
  38. Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V.,. ve Vayena, E. (2018). AI4People—An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and Machines, 28(4), 689–707.