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Beyond the Stars : The Impact of Rating-Text Inconsistency on Perceived Review Usefulness

초록

영어

Online reviews have a significant influence on purchasing decisions. Online reviews typically comprise star ratings and text content, both of which consumers consider when evaluating a product to reduce uncertainty. Previous studies have primarily concentrated on the isolated effects of these factors, assuming a strong correlation between star ratings and text context. However, there is a lack of research on the effect of review inconsistency on consumer perceptions, in which the sentiment conveyed in the text differs from the assigned star rating. By arguing that review inconsistency may provide more nuanced insights for consumers and has the potential to be positive in certain situations, this study explored the impact of review inconsistency on the perceived usefulness of reviews. In particular, we investigate the impact of two different inconsistencies between star ratings and review text, namely, degree and direction inconsistencies, by examining the circumstances under which these inconsistencies may stimulate consumer curiosity and prompt more comprehensive information processing. The analysis of data from 41,258 reviews of 183 products on Amazon.com suggests that review inconsistency can be perceived positively depending on contextual factors such as product awareness and review negativity. This study provides novel insights into consumer information processing and review platform design.

목차

ABSTRACT
Ⅰ. Introduction
Ⅱ. Conceptual Background
2.1. Review Usefulness
2.2. Review Inconsistency
2.3. Curiosity Theory
Ⅲ. Hypotheses
Ⅳ. Research Methodology
4.1. Data Collection
4.2. Definition of Variables
4.3. Descriptive Statistics
Ⅴ. Data Analysis and Results
Ⅵ. Discussion and Implications
6.1. Discussion of Findings
6.2. Implications for Research and Practice
6.3. Limitations and Future Research Directions
Acknowledgements

저자정보

  • Boram Kwon Assistant Professor, College of Business, Chosun University, Korea
  • Junyeong Lee Associate Professor, Department of Management Information Systems, Chungbuk National University, Korea
  • Jinyoung Min Associate Professor, College of Business & Economics, Chung-Ang University, Korea
  • Chanhee Kwak Assistant Professor, Department of Artificial Intelligence Convergence, Kangnam University, Korea
  • HanByeol Stella Choi Assistant Professor, Department of Management Information Systems, Myongji University, Korea

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