Unveiling a Hidden Driver of Online Rating Bias: The Role of Consumer Variety-Seeking Behavior

• Published in: Journal of theoretical and applied electronic commerce research Vol. 20; no. 3; p. 216
• Main Authors: Ni, Shida, Denizci Guillet, Basak, Gao, Yixing, Law, Rob, Sun, Baiqing
• Format: Journal Article
• Language: English
• Published: 19.08.2025
• ISSN: 0718-1876; 0718-1876
• DOI: 10.3390/jtaer20030216

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.