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February 12, 2026Naval Research Logistics (NRL)0 citations

Customer Reviews Subject to Reporting Bias: Its Influence on Customers, Firms, and Platform

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FHFengfeng HuangPGPengfei GuoYWYulan Wang

Key Points

  • This research explores the effect of reporting bias on customer evaluations and firm pricing strategies in online marketplaces.
  • Analyzed customer review behavior in the context of reporting bias.
  • Examined how different quality probabilities affect customer perceptions.
  • Assessed the impact of review-solicitation programs and platform interventions on mitigating bias.
  • Reporting bias leads to distorted customer perceptions of product quality.
  • High-quality firms suffer from bias, while low-quality firms may benefit.
  • Review solicitation programs help high-quality firms signal product quality but may not universally alleviate bias.

Abstract

ABSTRACT Customers tend to share extreme experiences more than moderate ones, a phenomenon known as reporting bias. Reporting bias diminishes the visibility of moderate experiences and polarizes customer opinions. It raises the following questions: How does reporting bias affect customers' evaluations of product quality? How should firms adjust their pricing strategies to address this reporting bias? What can online platforms do to mitigate its impact? We consider a firm selling a product of uncertain quality through an independent platform. Product quality can be high or low, and the probability of high quality is the firm's private information. Customers with heterogeneous preferences arrive sequentially and infer quality based on observed reviews. After consumption, customers decide whether to leave a review, with their review decisions subject to reporting bias. We assess the effectiveness of two common practices: review‐solicitation programs and platform interventions that automatically assign positive reviews to unreviewed transactions. We show that customers cannot learn the high‐quality probability from reviews subject to reporting bias: they make downward‐biased estimations if the high‐quality probability exceeds a threshold and upward‐biased estimations otherwise. The firm's optimal pricing ultimately converges to a static price that maximizes the expected current profit. Reporting bias hurts a high‐quality firm (i.e., a firm whose high‐quality probability is above the threshold) but benefits a low‐quality firm. While review‐solicitation programs can alleviate reporting bias, only a high‐quality firm is interested in participating. Platform intervention does not necessarily alleviate reporting bias and, worse yet, may harm high‐quality firms. Our findings suggest that online platforms should implement review‐solicitation programs to mitigate reporting bias. These programs enhance the quality of information for customers, facilitating more informed purchasing decisions and allowing high‐quality sellers to signal their product quality through participation.

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Cite This Study

Huang et al. (2026) studied this question.

synapsesocial.com/papers/698d6dae5be6419ac0d52d72https://doi.org/10.1002/nav.70056
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