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AI Labels, Perceived Authenticity, and Consumer Trust in User-Generated Reviews
University of Latvia, Riga, Latvia.
Halmstad University, School of Business, Innovation and Sustainability.ORCID iD: 0000-0002-2427-3148
2026 (English)In: Journal of Theoretical and Applied Electronic Commerce Research, E-ISSN 0718-1876, Vol. 21, no 5, p. 1-25, article id 154Article in journal (Refereed) Published
Abstract [en]

With growing interest in the effects of AI disclosure on user-generated content, empirical studies have produced mixed results. While some studies report negative consequences of disclosure, others suggest that transparent AI use does not necessarily reduce perceived authenticity or product evaluations. There is still limited knowledge about how AI disclosure in online reviews influences consumer perceptions when AI is presented as a support tool rather than a replacement for human input. To address this gap, the present study examines how AI disclosure and AI-related review cues influence consumer trust. The study compares three labeled review scenarios—reviews without AI-related information, AI-assisted labeled reviews, and AI-generated labeled reviews. The textual content of the reviews remained constant across conditions, while only AI-related labels and images were varied. This study also examines how these labeled scenarios relate to perceived authenticity and whether perceived authenticity mediates the relationship between labeled review scenarios and consumer trust. Based on survey data from 370 users of digital marketplaces in Latvia, analyzed using repeated-measures ANOVA, pairwise comparisons, and mediation analysis, this study found that: (1) reviews labeled as AI-generated showed the lowest levels of consumer trust and perceived authenticity, whereas AI-assisted labeled reviews were evaluated more favorably than AI-generated labeled reviews; (2) differences across the three scenarios were statistically significant for both consumer trust and perceived authenticity; and (3) perceived authenticity significantly mediated the relationship between labeled review scenarios and consumer trust. This study contributes to the literature by providing a more nuanced understanding of how AI disclosure and AI-related review cues shape consumer trust. It suggests that the key issue is not AI disclosure alone, but how AI-related cues shape perceived authenticity and, in turn, consumer trust. © 2026 by the authors.

Place, publisher, year, edition, pages
Basel: MDPI, 2026. Vol. 21, no 5, p. 1-25, article id 154
Keywords [en]
user generated content, artificial intelligence, consumer trust, e-commerce
National Category
Business Administration
Identifiers
URN: urn:nbn:se:hh:diva-60062DOI: 10.3390/jtaer21050154ISI: 001774680300001Scopus ID: 2-s2.0-105039969373OAI: oai:DiVA.org:hh-60062DiVA, id: diva2:2086811
Available from: 2026-07-16 Created: 2026-07-16 Last updated: 2026-07-16Bibliographically approved

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