Effects of Personalized Recommendations versus Aggregate Ratings on Post-Consumption Preference Responses

Forthcoming, MIS Quarterly

31 Pages Posted: 15 Mar 2021

See all articles by Gediminas Adomavicius

Gediminas Adomavicius

University of Minnesota - Twin Cities - Carlson School of Management

Jesse Bockstedt

University of Arizona - Department of Management Information Systems

Shawn Curley

University of Minnesota - Minneapolis

Jingjng Zhang

Indiana University - Kelley School of Business - Department of Operation & Decision Technologies

Date Written: March 11, 2021

Abstract

Online retailers use product ratings to signal quality and help consumers identify products for purchase. These ratings commonly take the form of either non-personalized, aggregate product ratings (i.e., the average rating a product received from a number of consumers such as “the average rating is 4.5/5 based on 100 reviews”), or personalized predicted preference ratings for a product (i.e., recommender-system-generated predictions for a consumer’s rating of a product such as “we think you’d rate this product 4.5/5”). Ratings in either format can provide decision aid to the consumer, but the two formats convey different types of product quality information and operate with different psychological mechanisms. Prior research has indicated that each recommendation type can significantly affect consumer’s post-experience preference ratings, constituting a judgmental bias, but has not compared the effects of these two common product-rating formats. Using a laboratory experiment, we show that aggregate ratings and personalized recommendations create similar biases on post-experience preference ratings when shown separately. Shown together, there is no cumulative increase in the effect. Instead, personalized recommendations tend to dominate. Our findings can help retailers determine how to use these different types of product ratings to most effectively serve their customers. Additionally, these results help to educate the consumer on how product-rating displays influence their stated preferences.

Keywords: online product ratings, recommender systems, personalized ratings, aggregate ratings, recommendation bias, laboratory experiments

Suggested Citation

Adomavicius, Gediminas and Bockstedt, Jesse and Curley, Shawn and Zhang, Jingjng, Effects of Personalized Recommendations versus Aggregate Ratings on Post-Consumption Preference Responses (March 11, 2021). Forthcoming, MIS Quarterly, Available at SSRN: https://ssrn.com/abstract=3802867

Gediminas Adomavicius

University of Minnesota - Twin Cities - Carlson School of Management ( email )

19th Avenue South
Minneapolis, MN 55455
United States

Jesse Bockstedt

University of Arizona - Department of Management Information Systems ( email )

AZ
United States

Shawn Curley

University of Minnesota - Minneapolis ( email )

110 Wulling Hall, 86 Pleasant St, S.E.
308 Harvard Street SE
Minneapolis, MN 55455
United States

Jingjng Zhang (Contact Author)

Indiana University - Kelley School of Business - Department of Operation & Decision Technologies ( email )

1309 E. Tenth Street
HH4143
Bloomington, IN 47401
United States

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