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.