Effects of Online Recommendations on Consumers’ Willingness to Pay

Gediminas Adomavicius (), Jesse C. Bockstedt (), Shawn P. Curley () and Jingjing Zhangc ()
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Gediminas Adomavicius: Information and Decision Sciences, Carlson School of Management, University of Minnesota, Minneapolis, Minnesota 55455
Jesse C. Bockstedt: Information Systems and Operations Management, Goizueta Business School, Emory University, Atlanta, Georgia 30322
Shawn P. Curley: Information and Decision Sciences, Carlson School of Management, University of Minnesota, Minneapolis, Minnesota 55455
Jingjing Zhangc: Operations and Decision Technologies, Kelley School of Business, Indiana University, Bloomington, Indiana 47405

Information Systems Research, 2018, vol. 29, issue 1, 84-102

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), and we 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 as well as for online retail practices.

The online appendix is available at https://doi.org/10.1287/isre.2017.0703 .

Keywords: behavioral economics; electronic commerce; laboratory experiments; preferences; recommender systems; willingness to pay (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (14)

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