Unveiling a Hidden Driver of Online Rating Bias: The Role of Consumer Variety-Seeking Behavior
Variety-seeking is a fundamental motivation in consumer decision making, yet its subsequent effect on consumer behavior is not fully understood. Thus, this study aims to investigate how consumers’ variety-seeking behaviors influence their subsequent ratings on online reputation platforms. We proposed a framework and constructed econometric models to validate it based on large-scale restaurant-review data from an online reputation platform. Several robustness-check methods were employed to ensure the reliability of our results. The empirical results demonstrate that consumers exhibit a positive rating bias in their reviews for variety-seeking options, compared to regular ones. Further analysis reveals that the influence of variety-seeking dynamically changes with the time-varying characteristics of consumers and restaurants. Specifically, as consumers accumulate a larger number of similar experiences and as restaurants age, the observed rating bias gradually diminishes. This study found a previously undocumented but widely prevalent factor causing rating bias on online reputation platforms, and its significant impact warrants attention. The findings also extend the theoretical application scope of variety-seeking in the field of consumer behavior and offer practical implications for managers and platform designers.
Authors
- Rob Law (ORCID: https://orcid.org/0000-0001-7199-3757)
- Basak Denizci Guillet (ORCID: https://orcid.org/0000-0001-5883-1729)
- Yixing Lisa Gao (ORCID: https://orcid.org/0000-0001-6919-434X)
- Baiqing Sun (ORCID: https://orcid.org/0000-0003-3384-5029)
- Shida Ni
Institutions
- Griffith University (AU)
- Hong Kong Polytechnic University (HK)
- University of Macau (MO)
- Harbin Institute of Technology (CN)
Publication Details
- Journal
- Journal of theoretical and applied electronic commerce research
- Published
- 2025-08-19
- DOI
- https://doi.org/10.3390/jtaer20030216
- Citations
- 2
- Primary Topic
- Digital Marketing and Social Media
- Type
- article
- Field-Weighted Citation Impact
- 8.40
Funders
- National Natural Science Foundation of China