Label “Buatan AI” pada Iklan TikTok untuk Produk Hedonik: Peran Pengetahuan Persuasi (Konseptual vs. Sikap) terhadap Sikap terhadap Iklan “AI-Generated” Labeling in TikTok Advertisements for Hedonic Products: The Role of Persuasion Knowledge (Conceptual vs. Attitudinal) in Attitude toward the Advertisement
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Page Numbers:
3070-3080
Digital Object Identifier:
10.58578/arzusin.v5i6.8474
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Authors:Rospita Simamora1*, Fadli Fadli2, Muhammad Dharma Tuah Putra Nasution3
Copyright :Authors retain copyright and grant the journal right of first publication.
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Abstract
The adoption of AI auto-labeling by TikTok since 2024 has established transparency in AI use as a new standard in digital advertising; however, its impact on consumer responses, particularly for hedonic products that are sensitive to warmth and authenticity, remains insufficiently understood. Drawing on the Persuasion Knowledge Model (PKM), this study distinguishes ad-specific persuasion knowledge (PK) into a conceptual dimension (recognition of content as advertising) and an attitudinal dimension (skepticism toward persuasive motives), and examines how the “AI-generated” label influences both dimensions and, in turn, attitude toward the ad (Aad). Using a between-subjects experimental design with a sample of 387 Indonesian TikTok users aged 18–35 years, this research manipulated the presence of an AI label on TikTok ads for a hedonic product (premium snacks). Data were analyzed using path analysis with PLS-SEM. The results show that the AI label significantly increases conceptual PK (β = .487, p < .001) and attitudinal PK (β = .312, p < .001), while conceptual PK in turn strengthens attitudinal PK (β = .394, p < .001). Attitudinal PK subsequently reduces Aad significantly (β = –.618, p < .001). Serial mediation analysis confirms the pathway AI label → conceptual PK → attitudinal PK → Aad (β = –.118, 95% CI [–.172, –.066]) with full mediation (total effect β = –.391). These findings provide three main contributions: (1) formalizing the separation of cognitive (conceptual PK) and affective (attitudinal PK) effects of AI-use disclosure; (2) demonstrating a trade-off between AI transparency and the advertising effectiveness of hedonic products in short-form video contexts; and (3) offering practical implications for TikTok advertisers in the form of content humanization strategies (human-in-the-loop narratives, warmth cues) and label format design (placement at the beginning of the video, semi-transparent display) to preserve affective effectiveness while remaining ethical and transparent. The study concludes that AI transparency, although normative and increasingly unavoidable, entails persuasive costs that need to be mitigated through warm and authentic creative design.
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References
Amazeen, M. A., & Wojdynski, B. W. (2019). Reducing native advertising deception: Revisiting the antecedents and consequences of persuasion knowledge in digital news contexts. Mass Communication and Society, 22(2), 222–247. https://doi.org/10.1080/15205436.2018.1530792
Appel, G., Grewal, L., Hadi, R., & Stephen, A. T. (2020). The future of social media in marketing. Journal of the Academy of Marketing Science, 48(1), 79–95. https://doi.org/10.1007/s11747-019-00695-1
Baek, T. H., Kim, J., & Kim, J. H. (2024). Effect of disclosing AI-generated content on prosocial advertising evaluation. International Journal of Advertising. Advance online publication. https://doi.org/10.1080/02650487.2024.2401319
Barrett, J. A. M., Jaakkola, E., Heller, J., & Brüggen, E. C. (2025). Customer engagement in utilitarian vs. hedonic service contexts. Journal of Service Research, 28(4), 614–633. https://doi.org/10.1177/10946705241242901
Eisend, M., van Reijmersdal, E. A., Boerman, S. C., & Tarrahi, F. (2020). A meta-analysis of the effects of disclosing sponsored content. Journal of Advertising, 49(3), 344–366. https://doi.org/10.1080/00913367.2020.1765909
Han, J., & Balabanis, G. (2024). Meta-analysis of social media influencer impact: Key antecedents and theoretical foundations. Psychology & Marketing, 41(2), 394–426. https://doi.org/10.1002/mar.21927
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
Kaur, G., Modi, P., & Mantok, S. (2023). New product innovations in times of crisis: How did women entrepreneurs survive the COVID-19 crisis? Industrial Marketing Management, 111, 19–29. https://doi.org/10.1016/j.indmarman.2023.03.004
Nunes, J. C., Ordanini, A., & Giambastiani, G. (2021). The concept of authenticity: What it means to consumers. Journal of Marketing, 85(4), 1–20. https://doi.org/10.1177/0022242921997081
Pera, R., Quinton, S., & Baima, G. (2020). I am who I am: Sharing photos on social media by older consumers and its influence on subjective well-being. Psychology & Marketing, 37(6), 782–795. https://doi.org/10.1002/mar.21337
Sarstedt, M., Hair, J. F., Ringle, C. M., & Liengaard, B. D. (2022). Progress in partial least squares structural equation modeling use in marketing research in the last decade. Psychology & Marketing, 39(5), 1035–1064. https://doi.org/10.1002/mar.21640
van Reijmersdal, E. A., Fransen, M. L., van Noort, G., Opree, S. J., Vandeberg, L., Reusch, S., & van Lieshout, F. (2016). Effects of disclosing sponsored content in blogs: How the use of resistance strategies mediates effects on persuasion. American Behavioral Scientist, 60(12), 1458–1474. https://doi.org/10.1177/0002764216660141
Voorveld, H. A. M., Meppelink, C. S., & Boerman, S. C. (2024). Consumers’ persuasion knowledge of algorithms in social media advertising: Identifying consumer groups based on awareness, appropriateness, and coping ability. International Journal of Advertising, 43(6), 960–986. https://doi.org/10.1080/02650487.2023.2264045
Waltenrath, A. (2024). Consumers’ ambiguous perceptions of advertising disclosures in influencer marketing: Disentangling the effects on current and future social media engagement. Electronic Markets, 34(1), 1–24. https://doi.org/10.1007/s12525-023-00679-8
Wojdynski, B. W., & Evans, N. J. (2016). Going native: Effects of disclosure position and language on the recognition and evaluation of online native advertising. Journal of Advertising, 45(2), 157–168. https://doi.org/10.1080/00913367.2015.1115380