Earticle

초록

영어

As online reviews increasingly combine text and user-generated images, prior research has paid limited attention to whether visual quality contributes to review helpfulness beyond image presence. Using 80,145 reviews from MercadoLibre Chile, this study examines how aesthetic image quality (MUSIQ), technical image quality (BRISQUE), and textual characteristics shape review helpfulness for search and experience goods. Predictive models show that visual quality provides modest but clearer performance gains for experience goods than for search goods. Fuzzy-set Qualitative Comparative Analysis (fsQCA) further shows that visual quality is not a core condition in high-helpfulness pathways. Instead, sufficient configurations are more consistently linked to authentic writing and balanced evaluative tone. The findings suggest that prediction model performance and configurational analysis provide different forms of evidence. This study contributes by offering a product-type-sensitive view of visual quality and by showing that visual quality can support helpfulness without defining its main configurational pathways.

목차

Abstract
Introduction
Literature Review
Review Helpfulness and Multimodal Review Information
Visual Quality in Review Helpfulness
Product Type Differences: Search and Experience Goods
Predictive and Configurational Approaches
Methodology
Data Collection
Variable Operationalization
Two Phase Analytical Approach: Predictive and Configurational Methods
Results
Product-Type Differences in Prediction
Configurational Patterns
Discussion
Implications
Limitations and Further Research Directions
Acknowledgments
References

키워드

저자

• Camila Estefania Painefilo Hermosilla [ School of Business, Pusan National University ]
• YoungKi Park [ School of Business, George Washington University ]
• Taeho Hong [ School of Business, Pusan National University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국경영정보학회 정기 학술대회 [KMIS Conference]

• 간기

  반년간

• 수록기간

  1990~2026

• 십진분류

  KDC 325 DDC 658