 Exploring customer sentiment regarding online retail services: A topic-based approachJia-Jhou Wu and Sue-Ting Chang Journal of Retailing and Consumer Services, 2020, vol. 55, issue C Abstract: User-generated content is a valuable source for understanding online shoppers' emotions. Using text-mining techniques, this study identifies seven topics regarding online retail services in online posts: product, retailer promotion, delivery, payment, communication, return/refund, and price. The topics are associated with the sentiment polarity of online shoppers' posts. This study further explores whether the emotional responses from domestic and cross-border online shoppers differ with regard to these topics. The results show that differences exist in these two groups' sentiments concerning product and payment. Furthermore, there are differences in the two groups’ respective negative emotions (i.e., anger, sadness, and fear) concerning delivery, communication, and return/refund. The findings of this study provide online retailers with important managerial implications. Keywords: Online retailing; Cross-border online shopping; Topic modeling; Latent dirichlet allocation; Sentiment analysis (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:joreco:v:55:y:2020:i:c:s096969891930997x DOI: 10.1016/j.jretconser.2020.102145 Access Statistics for this article Journal of Retailing and Consumer Services is currently edited by Harry Timmermans More articles in Journal of Retailing and Consumer Services from Elsevier |
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