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

Loading...
Thumbnail Image
File version

Version of Record (VoR)

Author(s)
Ni, Shida
Denizci Guillet, Basak
Gao, Yixing
Law, Rob
Sun, Baiqing
Griffith University Author(s)
Primary Supervisor
Other Supervisors
Editor(s)
Date
2025
Size
File type(s)
Location
Abstract

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.

Journal Title

Journal of Theoretical and Applied Electronic Commerce Research

Conference Title
Book Title
Edition
Volume

20

Issue

3

Thesis Type
Degree Program
School
Publisher link
Patent number
Funder(s)
Grant identifier(s)
Rights Statement
Rights Statement

© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Item Access Status
Note
Access the data
Related item(s)
Subject

Business systems in context

Marketing

Information systems

Persistent link to this record
Citation

Ni, S; Denizci Guillet, B; Gao, Y; Law, R; Sun, B, Unveiling a Hidden Driver of Online Rating Bias: The Role of Consumer Variety-Seeking Behavior, Journal of Theoretical and Applied Electronic Commerce Research, 2025, 20 (3), pp. 216

Collections