Earticle

초록

영어

Online reviews crucially shape consumer purchasing decisions, with visual cues receiving increasing attention. However, the specific impact of human faces within these visuals remains underexplored. This study investigates how user-generated photos (UGPs) and facial characteristics affect review helpfulness. Using 152,320 Amazon clothing reviews, we analyze the role of UGPs, face presence, quantity, quality, and expression across different valences. Our findings reveal that while both UGPs and human faces enhance review helpfulness, general UGPs are more effective in positive reviews, whereas human faces are more impactful in negative ones. Furthermore, results do not support the “more is better” assumption, showing that reviews with multiple faces are generally less helpful than single-face ones, a pattern reversed only when facial clarity is high, or the review is negative. Finally, non-smiling faces enhance the helpfulness of negative reviews, supporting the role of consistency. Theoretically, this study enriches media richness theory by highlighting the fit between content type and review valence, provides evidence that information-processing constraints limit the benefits of visual quantity, and extends internal consistency to expression-rating alignment. In practice, we offer guidance to reviewers on selecting credible images and to platforms on optimizing algorithms to prioritize high-value visual cues.

목차

ABSTRACT
Ⅰ. Introduction
Ⅱ. Literature Review
2.1. Review Helpfulness and the Role of User-Generated Photos
2.2. Human Faces in User-Generated Photos
Ⅲ. Theory and Hypotheses Development
3.1. Media Richness Theory and the Impact of Visual Cues
3.2. Negativity Bias and Review Valence
3.3. Facial Expressions and Online Review Internal Consistency
Ⅳ. Methods
4.1. Data Collection
4.2. Facial Feature Extraction
4.3. Variable Measurement
Ⅴ. Results
5.1. Descriptive Statistics
5.2. Hypotheses Testing
5.3. Robustness Analyses
Ⅵ. Discussion
6.1. Key Findings
6.2. Theoretical Contributions
6.3. Practical Contributions
6.4. Limitations and Future Research
Acknowledgements

Appendices

키워드

저자

• Yan Sun [ Ph.D. Candidate, School of Management, Kyung Hee University, Korea ]
• Sung-Byung Yang [ Professor, School of Management, Kyung Hee University, Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  Asia Pacific Journal of Information Systems

• 간기

  계간

• pISSN

  2288-5404

• eISSN

  2288-6818

• 수록기간

  1990~2026

• 등재여부

  KCI 등재,SCOPUS

• 십진분류

  KDC 325 DDC 658