Recommender systems, consumer preferences, and anchoring effects

Gediminas Adomavicius, Jesse Bockstedt, Shawn Curley, Jingjing Zhang

Research output: Contribution to journalConference article

25 Scopus citations

Abstract

Recommender systems are becoming a salient part of many e-commerce websites. Much research has focused on advancing recommendation technologies to improve the accuracy of predictions, while behavioral aspects of using recommender systems are often overlooked. In this study, we explore how consumer preferences at the time of consumption are impacted by predictions generated by recommender systems. We conducted three controlled laboratory experiments to explore the effects of system recommendations on preferences. Studies 1 and 2 investigated user preferences for television programs, which were surveyed immediately following program viewing. Study 3 broadened to an additional context-preferences for jokes. Results provide strong evidence viewers' preferences are malleable and can be significantly influenced by ratings provided by recommender systems. Additionally, the effects of pure number-based anchoring can be separated from the effects of the perceived reliability of a recommender system. Finally, the effect of anchoring is roughly continuous, operating over a range of perturbations of the system.

ASJC Scopus subject areas

  • Computer Science(all)

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