Earticle

초록

영어

This study employs text mining techniques to analyze online customer reviews, focusing on two product categories—hedonic and utilitarian—as well as corresponding seller responses. Using sentiment analysis and Latent Dirichlet Allocation (LDA) topic modeling, the research identifies key themes in negative reviews, revealing the specific aspects of the purchasing experience that consumers emphasize when expressing dissatisfaction. Furthermore, the study examines seller response patterns to assess the effectiveness of various response strategies in mitigating the impact of negative feedback. Results show that Consumer concerns vary by product type: buyers of utilitarian products primarily highlight functional failures, whereas buyers of hedonic products tend to focus on emotional dissatisfaction. These findings offer insights into businesses, contributing to a deeper understanding of consumer behavior in the face of negative reviews. The results can inform the development of more effective crisis management strategies and optimized response mechanisms, enhancing consumer trust and encouraging repurchase intentions.

목차

Abstract
Introduction
Literature Review
The Growth of E-Commerce Platform and Negative Reviews
Product Typology
Methodology
Data Analysis
Conclusions and Discussion
References

키워드

저자

• 김엘레나 [ 순천향대학교 경영학과 ]
• 이슬럼존 [ 순천향대학교 경영학과 ]
• 최재원 [ 순천향대학교 경영학과 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국경영정보학회 정기 학술대회 [KMIS Conference]

• 간기

  반년간

• 수록기간

  1990~2025

• 십진분류

  KDC 325 DDC 658