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New Research Finds Popularity Distance Between a Visited Restaurant's Location and a Person's Hometown Biases their Online Rating up to 11%

  • 1.  New Research Finds Popularity Distance Between a Visited Restaurant's Location and a Person's Hometown Biases their Online Rating up to 11%

    Posted 11 days ago

    CATONSVILLE, MD, February 6, 2020 – Product reviews and ratings have a strong impact on consumer consideration. In restaurant reviews, new research 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%.

    Click here to read the full press release.



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    Ashley Smith
    INFORMS
    Catonsville MD
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  • 2.  RE: New Research Finds Popularity Distance Between a Visited Restaurant's Location and a Person's Hometown Biases their Online Rating up to 11%

    Posted 10 days ago
    Sounds like customer preconceptions (flawed, perhaps?) are at work! The 7% average effect of popularity-difference bias for restaurant reviews doesn't seems significant, but considering that more customers take to the internet and sites like Yelp before committing to an eatery, and in addition to the sheer competition in the restaurant industry, I acknowledge that that percent difference could be a big deal for managers. The findings do make sense. I think of the sentiment "The food/performance/service was all right for X" in this circumstance. We have lower expectations for places we believe to be less popular or for people we believe to be less skilled, which can translate to more negative evaluations.

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    Abigail Lindner
    Student
    Regent University
    Virginia Beach, VA
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  • 3.  RE: New Research Finds Popularity Distance Between a Visited Restaurant's Location and a Person's Hometown Biases their Online Rating up to 11%

    Posted 10 days ago
    Edited by Rahul Saxena 10 days ago
    Timely and interesting article as I'm working on reputation analyses for car dealers and trying to figure out what drives the ratings.

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    Rahul Saxena
    Cobot Systems
    Bangalore
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