Cluster analysis of user groups for self-collection service

• 1、School of Management, Wuhan University of Science and Technology, Wuhan 430065

Abstract：With rapid development of e-commerce and the tendency of the terminal delivery mode to be intelligent, self-collection service can better meet the growing demand of consumers. From the perspective of user experience, the paper employs the methods of interview and questionnaire. The purpose is to understand the key dimensions of self-service service (Reception Box and Collection and Delivery Points) and the types of user segments, so as to provide optimization references for terminal delivery service providers. Firstly, five key dimensions were distilled in self-collection service through interview, including practicability, security, environment friendly, sociality and hedonic; then a scale questionnaire was constructed to collect 267 user questionnaires. And the data was analyzed by K-means clustering method to obtain four user types-positive users, cautious users, indifferent users, and repulsive users; finally, the qualitative analysis of the user types drew conclusions and put forward corresponding recommendations.

Keywords： management science terminal delivery interview questionnaire survey K-means customer segmentation