CATONSVILLE, MD, February 6, 2020 - Product reviews and ratings have a strong impact on consumer consideration. In restaurant reviews, new research upcoming in the INFORMS journal Information Systems Research shows that location bias, based on the popularity difference between the reviewer's hometown and the distance to their destination, can affect a reviewers online rating by as much as 11%.
The study, "Your Hometown Matters: Popularity-Difference Bias in Online Reputation Platforms," conducted by Marios Kokkodis of Boston College and Theodoros Lappas of Stevens Institute of Technology, found when reviewers travel to a less popular location than their hometown, they review with a negative tendency. When reviewers travel to a more popular location than their hometown they review with a positive tendency.
In this study, Kokkodis and Lappas analyzed more than 760,000 restaurant reviews from nearly 1,500 cities in the continental U.S. In that dataset alone they said bias affected 98% of the restaurants.
"This effect on ratings alters the probability that an average customer will consider a restaurant by up to 16%. This is because the bias can distort online reputations, leading to misrepresented businesses and misinformed users," said Kokkodis, a professor in the Carroll School of Management at Boston College.
Awareness of the popularity-difference bias allows managers to improve the design of their ranking systems. The study shows such improvements can lead to up to 12% higher reviewer satisfaction and up to 24% more diversified top-restaurant recommendations.
About INFORMS and Information Systems Research
Information Systems research is a premier peer-reviewed scholarly journal focused on the latest theory, research and intellectual development to advance knowledge about the effective and efficient utilization of information technology. It is published by INFORMS, the leading international association for operations research and analytics professionals. More information is available at http://www.informs.org or @informs.
Information Systems Research