Effects of online recommendations on consumers' willingness to pay

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

Research output: Contribution to journalArticle

22 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)84-102
Number of pages19
JournalInformation Systems Research
Volume29
Issue number1
DOIs
StatePublished - Mar 1 2018

Keywords

  • Behavioral economics
  • Electronic commerce
  • Laboratory experiments
  • Preferences
  • Recommender systems
  • Willingness to pay

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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