Recommender systems are an integral part of the online retail environment. Prior research has focused largely on computational approaches to improving recommendation accuracy, and only recently researchers have started to study their behavioral implications and potential side effects.We used three controlled experiments, in the context of purchasing digital songs, to explore the willingness-to-pay judgments of individual consumers after being shown personalized recommendations. In Study 1, we found strong evidence that randomly assigned song recommendations affected participants' willingness to pay, even when controlling for participants' preferences and demographics. In Study 2, participants viewed actual system-generated recommendations that were intentionally perturbed (introducing recommendation error), andwe observed similar effects. In Study 3,we showed that the influence of personalized recommendations on willingness-to-pay judgments was obtained even when preference uncertainty was reduced through immediate and mandatory song sampling prior to pricing. The results demonstrate the existence of important economic side effects of personalized recommender systems and inform our understanding of how system recommendations can influence our everyday preference judgments. The findings have significant implications for the design and application of recommender systems aswell as for online retail practices.
Bibliographical noteFunding Information:
History: Yong Tan, Senior Editor; Alessandro Acquisti, Associate Editor. Funding:This work was supported in part by a research grant provided by the Carlson School of Management. SupplementalMaterial: The online appendix is available at https://doi.org/10.1287/isre.2017.0703.
© 2017 INFORMS.
- Behavioral economics
- Electronic commerce
- Laboratory experiments
- Recommender systems
- Willingness to pay