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Recommendation agents (RAs) provide consumers with personalized product recommendations based on their needs and preferences, helping them to purchase online. An increasing number of merchants use biased RAs on their online stores providing recommendations not solely made to match consumers' preferences but biased towards their strategic goals. The literature did not investigate whether consumers are aware of this phenomenon. Based on agency theory, signal detection theory and prior research on biased RAs, this study empirically investigates the effects of the level of bias intensity in RA's recommendations, perceived personalization, perceived relevance, and consumer's experience with the RA on consumer's ability to detect biased RAs. By providing a better understanding of consumers' vulnerability to the business practices of online merchants, and of the mechanisms underlying bias detection, the results of this study offer a valuable contribution to research and practice.
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Charles, C., Ducarroz, C., & Vande Kerckhove, C. (2025). Evaluating Consumer’s Ability to Detect Biased Recommendation Agents. AMS Annual Conference, Montreal. https://hdl.handle.net/2078.5/239263