Do recommender systems manipulate consumer preferences? A study of anchoring effects

Gediminas Adomavicius, Jesse C. Bockstedt, Shawn P. Curley, Jingjing Zhang

Research output: Contribution to journalArticle

74 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 accuracy of predictions, although behavioral aspects of using recommender systems are often overlooked. In our studies, 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 across a variety of conditions, which were surveyed immediately following program viewing. Study 3 investigated the granularity of the observed effects within individual participants. Results provide strong evidence that the rating presented by a recommender system serves as an anchor for the consumer's constructed preference. Viewers' preference ratings are malleable and can be significantly influenced by the recommendation received. The effect is sensitive to the perceived reliability of a recommender system and, thus, not a purely numerical or priming-based effect. Finally, the effect of anchoring is continuous and linear, operating over a range of perturbations of the system. These general findings have a number of important implications (e.g., on recommender systems performance metrics and design, preference bias, potential strategic behavior, and trust), which are discussed.

Original languageEnglish (US)
Pages (from-to)956-975
Number of pages20
JournalInformation Systems Research
Volume24
Issue number4
DOIs
StatePublished - Oct 22 2013

Keywords

  • Anchoring effects
  • Behavioral decision making
  • Behavioral economics
  • Electronic commerce
  • Experimental research
  • Preferences
  • Recommender systems

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Computer Networks and Communications
  • Information Systems and Management
  • Library and Information Sciences

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