Consumer Reviews and Host Strategies: Managing Rating Deviations for Optimal Airbnb Performance

This research addresses the issue of inflated ratings in the Airbnb property space, which often generates misleading consumption and performance data. We analyse how positive and negative rating deviations influence Airbnb hosts’ performance metrics. Our study further investigates the moderating effects of the Superhost badge and the distinction between single- vs. multi-listing hosts. We model the London Airbnb industry between 2015 and 2021 using a two-level mixed-effect model to account for host characteristics and neighbourhood (borough-level) effects and predict the influence of online rating deviations on host performance. Empirical insights reveal that positive deviations significantly enhance host performance, particularly benefiting single listing hosts. In contrast, negative deviations detrimentally impact performance, with single listing hosts experiencing greater adverse effects. Notably, the Superhost badge amplifies the overall relationship between review deviations and host performance.

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Publication Details

Journal
Journal of Smart Tourism
Published
2026-08-25
DOI
https://doi.org/10.1177/27652157261480713
Primary Topic
Sharing Economy and Platforms
Type
article
Field-Weighted Citation Impact
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article

Consumer Reviews and Host Strategies: Managing Rating Deviations for Optimal Airbnb Performance

Shih‐Chuan Lin, I‐Heng Wu, Yoo Ri Kim
Journal of Smart Tourism
Sharing Economy and Platforms
article

Consumer Reviews and Host Strategies: Managing Rating Deviations for Optimal Airbnb Performance

Shih‐Chuan Lin, I‐Heng Wu, Yoo Ri Kim
article en

Abstract

This research addresses the issue of inflated ratings in the Airbnb property space, which often generates misleading consumption and performance data. We analyse how positive and negative rating deviations influence Airbnb hosts’ performance metrics. Our study further investigates the moderating effects of the Superhost badge and the distinction between single- vs. multi-listing hosts. We model the London Airbnb industry between 2015 and 2021 using a two-level mixed-effect model to account for host characteristics and neighbourhood (borough-level) effects and predict the influence of online rating deviations on host performance. Empirical insights reveal that positive deviations significantly enhance host performance, particularly benefiting single listing hosts. In contrast, negative deviations detrimentally impact performance, with single listing hosts experiencing greater adverse effects. Notably, the Superhost badge amplifies the overall relationship between review deviations and host performance.

Journal of Smart Tourism
University of Central Florida (US), Tamkang University (TW), University of New Mexico (US)
Openalex Percentile: Top 5%
Sharing Economy and Platforms
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Consumer Reviews and Host Strategies: Managing Rating Deviations for Optimal Airbnb Performance — Shih‐Chuan Lin, I‐Heng Wu, et al. · Journal of Smart Tourism (2026) | TGRS Research Map | TGRS