Mining Express Service Innovation Opportunity From Online Reviews

Ning Zhang, Rui Zhang, Zhiliang Pang, Xue Liu, Wenfei Zhao

OAI: oai:igi-global.com:276515 • DOI: 10.4018/JOEUC.20211101.oa3

In order to further meet the diversified needs of customers and enhance market competitiveness, it is necessary for express delivery enterprises to carry out service innovation. From the perspective of customer demand, we propose a framework for mining service innovation opportunities. This framework uses text mining to analyze user generated content and tries to provide a scientific service innovation scheme for express enterprises. Firstly, we crawl online reviews of express companies and use LDA model to identify service attributes. Secondly, customer satisfaction is calculated by sentiment analysis, and simultaneously, the importance of each service attribute is calculated. Finally, we carry out an opportunity algorithm with the results of text mining to quantify the innovation opportunities of service attributes. The results show that the framework can effectively identify service innovation opportunities from the perspective of customer demand. This study provides a new way to explore the direction of service innovation from the perspective of customer demand.

End-User Computing Social Sciences and Humanities Human Aspects of Technology