Generative AI in Fashion E-Commerce Product Imagery: An Experimental Test of Image Origin and Transparency Labelling on Consumer Trust, Perceived Product Quality and Purchase Intention
DOI:
https://doi.org/10.51137/wrp.ijaaib.1062Keywords:
Generative Artificial Intelligence, AI Disclosure, Fashion E-Commerce, Consumer TrustAbstract
Retailers are increasingly replacing photographic model shoots with synthetic product imagery generated by text-to-image systems, a deployment decision that couples substantial production savings with an unresolved question about consumer response and about the transparency obligations attached to synthetic content. This study examines how AI-generated and photographic product images are evaluated in fashion e-commerce and how a visible origin label affects that evaluation. A 2 (image origin: AI-generated vs. photograph) × 2 (labelling: absent vs. present) between-subjects online experiment was conducted with 150 participants. Consumer trust, perceived product quality and purchase intention were measured with established scales, and general attitude toward artificial intelligence was tested as a moderator. Without labelling, no statistically significant differences between the two image types emerged on any dependent variable. The visible label reduced perceived product quality significantly but modestly, while effects on trust and purchase intention, the image origin by label interaction and moderation were not statistically significant.
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