Analyzing Customers’ Perception of Service and Market Trends in Fresh Food E-commerce: Application of Text Mining Techniques

As the competition in the fresh food e-commerce market intensifies, it has become important to identify various drivers that influence customers’ perception of the e-commerce service. The purpose of this paper is to analyze the fresh food e-commerce trend and the customers’ perception of fresh food e-commerce service. We apply text mining to online review data which show voluntary and direct experience or feedback from customers. To the best of our knowledge, this study is the first to conduct latent Dirichlet allocation(LDA), a topic modeling approach, and word cloud to a large number of customer online reviews for investigating the e-commerce market and service. The results reveal the continuous interest in the delivery service and delivery speed for fresh food products in the e-commerce market. Furthermore, various topics and topics’ relative importance which represent customers’ perception of fresh food e-commerce service suggest the insights for the direction of e-commerce corporate. We expect that this paper could fill the gap in studies about the fresh food E-commerce. Furthermore, such results can provide valuable information for the fresh food E-commerce corporations in establishing operational strategies.