Corresponding Author

Yang Li

Document Type

Work in Progress

Abstract

With the rapid development of the Internet, cross-border e-commerce has become an important channel for promoting international trade. Simultaneously, more and more customers express their views and comments on cross-border e-commerce services on the Internet. To understand and satisfy customers’ requirements, it is required to find out helpful information from consumer feedback and make an improvement as soon as possible. The relevant firms will provide a more friendly and satisfactory service for customers by this way. Cross-border e-commerce will also achieve a better development. Therefore, this study proposes a method which combines text mining and Kansei engineering to analyze cross-border e-commerce service. Kansei engineering (KE) is a kind of approach to design the elements which transforms customers’ affective and emotional perceptions into products and services. Therefore, this study applies a KE-based approach to analyze the associations between service elements (property space) of cross-border e-commerce and customers’ emotional perceptions (semantic space), and provides a new idea for further improvement of cross-border e-commerce service.

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