Recommendation agents (RAs) provide consumers with personalized product recommenda-tions based on their needs and preferences, helping them to purchase online. An increasing number of merchants use biased RAs on their online store providing recommendations not solely made to match consumers' preferences but biased towards their strategic goals. Although biased RAs are widespread in practice (e.g., Amazon, Netflix, Hotel.de), studying their effects on consumer behavior has received limited attention in the existing literature. Based on agency theory, signal detection theory, psychological contract violation theory and prior research on biased RAs, this PhD thesis aims to contribute to fill this gap by investigating the effects of biased RAs on consumer behavior. By providing a better understanding of consumers' vulner-ability and behavior to the business practices of online merchants, the results of this PhD thesis offer a valuable contribution to research and practice.
Charles et al. (Wed,) studied this question.