Badge Tenure as a Moderator of Review Cues: An Elaboration Likelihood Model Perspective on Yelp’s Elite Reviewers
Online reviews are increasingly pivotal in consumer decision-making, with platforms employing mechanisms such as badges to denote reviewer credibility. Although prior research has examined the influence of expert reviewers, it has typically treated badge holders as a homogeneous group, overlooking how variation in tenure within expert tiers shapes the way readers process review content. This article examines how Yelp Elite badge tenure, operationalized as Red (1–4 years), Gold (5–9 years), and Black (10+ years) tiers and treated as a proxy for accumulated platform-recognized expertise, moderates the effects of peripheral cues (Extremity, Length) and central cues (Readability, Subjectivity, and Plutchik’s eight emotions) on perceived helpfulness within an Elaboration Likelihood Model (ELM) framework. The analysis draws on the full population of 324,426 restaurant reviews authored by Yelp Elite badge holders between 2019 and 2021, using a pooled count-model specification with badge tier as a categorical moderator. The primary specification is estimated using Poisson quasi-maximum likelihood with HC1-robust standard errors, and full negative binomial estimation is reported as a robustness check. Wald tests indicate that badge tenure significantly moderates eight of twelve cue–helpfulness relationships (χ2(24)=4938, p<0.001). The effect of readability is monotonically positive and increases sharply with tenure, while the effect of joy varies across tenure groups. These findings suggest that reviewer expertise signals are not monolithic, refining theoretical insights on how tenure-based credibility cues moderate cue processing and offering practical implications for review platform management. The findings also indicate that platforms applying uniform ranking or surfacing rules across all Elite reviewers risk misallocating visibility, and that tenure-conditional weighting of textual cues warrants consideration.
Authors
- Youngju Cho
- Heejun Park (ORCID: https://orcid.org/0000-0003-4349-7697)
- Joon-Woo Yoo (ORCID: https://orcid.org/0000-0001-6343-7419)
- Junyoung Yoo
Institutions
- Yonsei University (KR)
Publication Details
- Journal
- Journal of theoretical and applied electronic commerce research
- Published
- 2026-05-21
- DOI
- https://doi.org/10.3390/jtaer21050158
- Primary Topic
- Digital Marketing and Social Media
- Type
- article
- Field-Weighted Citation Impact
- 0.00