Template-Type: ReDIF-Article 1.0
Author-Name: Han, Xiaomei
Author-Name-First: Xiaomei
Author-Name-Last: Han
Author-Email: 21010239@siswa.unimas.my
Author-Workplace-Name: Anhui Finance and Trade Vocational College, Hefei, Anhui, China; & Faculty of Economics and Business, Universiti Malaysia Sarawak (UNIMAS), Kota Samarahan, Sarawak, Malaysia
Author-Name: Latif, Hamrila Abdul
Author-Name-First: Hamrila Abdul
Author-Name-Last: Latif
Author-Email: 21010239@siswa.unimas.my
Author-Workplace-Name: Anhui Finance and Trade Vocational College, Hefei, Anhui, China
Author-Name: Puah, Chin-Hong
Author-Name-First: Chin-Hong
Author-Name-Last: Puah
Author-Email: 21010239@siswa.unimas.my
Author-Workplace-Name: Anhui Finance and Trade Vocational College, Hefei, Anhui, China
Title: What Drives Satisfaction in Fresh E-Commerce? Evidence from Review-Based Topic and Sentiment Analysis
Abstract: This study explores key determinants of customer satisfaction in China's fresh e-commerce sector by analyzing large-scale user-generated reviews from JD Fresh. Unlike prior research relying on surveys, this study integrates semantic segmentation, high-frequency textual data, and multivariate modeling to offer a data-driven and fine-grained understanding of customer experience. Nine service dimensions were identified: Freshness, Affordability, Size, Taste, Ice Pack, Delivery, Quality, Storage, and Platform Functionality. Sentiment scores were calculated for each dimension and used in a multiple linear regression model to assess their impact on overall satisfaction. Results indicate that all nine factors significantly affect satisfaction, with Taste, Quality, and Storage being the most influential. These findings demonstrate the effectiveness of combining text mining and sentiment analysis in identifying service quality dimensions and predicting satisfaction. The study also highlights the value of online reviews as a scalable source for service evaluation and provides actionable insights for improving user experience and repurchase intention in the highly competitive fresh e-commerce industry.
Keywords: Fresh E-Commerce, Customer Satisfaction, Online Reviews, Sentiment Analysis, Topic Modeling, Text Mining
Journal: International Review of Management and Marketing
Pages: 267-274
Volume: 16
Issue: 1
Year: 2025
Month: 11
DOI: 10.32479/irmm.21172
File-URL: https://econjournals.com/index.php/irmm/article/download/21172/9526
File-Format: application/pdf
Handle: RePEc:eco:journ3:v:16:y:2025:i:1:id:21172