Earticle

초록

영어

Online reviews play a significant role in consumer purchase decisions on e-commerce platforms. To address information overload in the context of online reviews, factors that drive review helpfulness have received considerable attention from scholars and practitioners. The purpose of this study is to explore the differential effects of discrete emotions (anger, disgust, fear, joy, sadness, and surprise) on perceived review helpfulness, drawing on cognitive appraisal theory of emotion and expectation-confirmation theory. Emotions embedded in 56,157 hotel reviews collected from TripAdvisor.com were extracted based on a transfer learning model to measure emotion variables as an alternative to dictionary-based methods adopted in previous research. We found that anger and fear have positive impacts on review helpfulness, while disgust and joy exert negative impacts. Moreover, hotel star-classification significantly moderates the relationships between several emotions (disgust, fear, and joy) and perceived review helpfulness. Our results extend the understanding of review assessment and have managerial implications for hotel managers and e-commerce vendors.

목차

ABSTRACT
Ⅰ. Introduction
Ⅱ. Conceptual Background
2.1. Discrete Emotions
2.2. Review Helpfulness
2.3. Hotel Star-classification
2.4. Emotion Analysis
Ⅲ. Research Model and Hypotheses
Ⅳ. Methodology
4.1. Data Collection and Preprocessing
4.2. Emotion Analysis
4.3. Regression Analysis
Ⅴ. Results
Ⅵ. Discussion and Conclusion
6.1. Discussion of Findings
6.2. Theoretical Implications
6.3. Managerial Implications
6.4. Limitations and Future Research
Acknowledgements

저자

• Dahee Lee [ Ph.D. Candidate, School of Business, Hanyang University, Korea ]
• Jong Woo Kim [ Professor, School of Business, Hanyang University, Korea ] Corresponding Author

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