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Caught in the Act: Natural recognition of deepfake UGC ad, expectancy violation and consumer responses

Author

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  • Yang, Jing
  • Lee, Susanna S.

Abstract

This study investigates how consumers' awareness of deepfake user-generated content-style advertisements in different pathways (i.e., natural recognition, no recognition, and post-disclosure) influences their psychological and behavioral intentions, using the theoretical lenses of the persuasion knowledge model and expectancy violation theory. Across three interconnected studies, findings consistently show that natural recognition elicits more negative responses compared to both no recognition and post-disclosure. Natural recognition triggers a greater negative expectancy violation and a stronger sense of betrayal, which mediates the relationship between recognition and the consumer responses. While the post-disclosure pathway leads to a higher magnitude of expectancy violation, it is still less negatively violating than natural recognition due to perceived novelty. Furthermore, priming significantly increases consumers’ likelihood of natural recognition. This serves as a proxy, indicating that as real-world awareness of deepfake user-generated content advertisements increases, it may lead to negative evaluations and ultimately reduce overall effectiveness.

Suggested Citation

  • Yang, Jing & Lee, Susanna S., 2026. "Caught in the Act: Natural recognition of deepfake UGC ad, expectancy violation and consumer responses," Journal of Retailing and Consumer Services, Elsevier, vol. 88(C).
    • Handle: RePEc:eee:joreco:v:88:y:2026:i:c:s0969698925003145
    DOI: 10.1016/j.jretconser.2025.104535
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