How review environments shape review voting: the roles of competition intensity and attention intensity

Purpose Most platforms feature online reviews with voting functions that act as peer-based social feedback. Beyond prior research that examines how review and reviewer characteristics shape voting outcomes, this study investigates how two environmental factors, competition intensity and attention intensity, affect voting outcomes. Design/methodology/approach This study draws on communication models and uses Poisson Pseudo Maximum Likelihood regression with high-dimensional fixed effects, using 293,670 Yelp reviews from 29,842 reviewers across 11,436 US restaurants to empirically test our communication-based framework. Findings We find that competition intensity reduces the number of votes a review receives, whereas attention intensity increases it. We also show that review deviation and reviewer status mitigate the negative effect of competition; review deviation amplifies, whereas reviewer status weakens, the positive effect of attention. Practical implications Our findings demonstrate that the environment surrounding a review meaningfully shapes how it communicates with readers, guiding users' attention allocation and engagement. The results offer practical implications for reviewers seeking to strategically improve voting outcomes and for platforms aiming to manage information overload and enhance user engagement efficiency. Originality/value This study is among the first empirical investigations into how the broader communication context of online reviews – defined by the volume of competing messages and the concentration of audience attention – influences user responses to individual reviews.

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Publication Details

Journal
Industrial Management & Data Systems
Published
2026-11-04
DOI
https://doi.org/10.1108/imds-01-2026-0083
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
0.00
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article

How review environments shape review voting: the roles of competition intensity and attention intensity

Zhaoyang Yu, Hong Wang, Shaohui Wu, Yuhan Zhang et al.
Industrial Management & Data Systems
Digital Marketing and Social Media
article

How review environments shape review voting: the roles of competition intensity and attention intensity

Zhaoyang Yu, Hong Wang, Shaohui Wu, Yuhan Zhang, Ruonan Zhang
article en

Abstract

Purpose Most platforms feature online reviews with voting functions that act as peer-based social feedback. Beyond prior research that examines how review and reviewer characteristics shape voting outcomes, this study investigates how two environmental factors, competition intensity and attention intensity, affect voting outcomes. Design/methodology/approach This study draws on communication models and uses Poisson Pseudo Maximum Likelihood regression with high-dimensional fixed effects, using 293,670 Yelp reviews from 29,842 reviewers across 11,436 US restaurants to empirically test our communication-based framework. Findings We find that competition intensity reduces the number of votes a review receives, whereas attention intensity increases it. We also show that review deviation and reviewer status mitigate the negative effect of competition; review deviation amplifies, whereas reviewer status weakens, the positive effect of attention. Practical implications Our findings demonstrate that the environment surrounding a review meaningfully shapes how it communicates with readers, guiding users' attention allocation and engagement. The results offer practical implications for reviewers seeking to strategically improve voting outcomes and for platforms aiming to manage information overload and enhance user engagement efficiency. Originality/value This study is among the first empirical investigations into how the broader communication context of online reviews – defined by the volume of competing messages and the concentration of audience attention – influences user responses to individual reviews.

Industrial Management & Data Systems
Hong Kong Polytechnic University (HK), Harbin Institute of Technology (CN), Tsinghua University (CN)
Openalex Percentile: Top 8%
Digital Marketing and Social Media
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