Kangning Zheng , Xiaoxin Huo , Sajjad Jasimuddin , Justin Zuopeng Zhang , Olga Battaïa
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Logistics distribution optimization: Fuzzy clustering analysis of e-commerce customers’ demands
E-commerce customers’ demands for delivery services have become more personalized, diversified, and complex. In this paper, we conduct cluster analysis on the customer demand attributes resulting in a list of attributes including quantitative and qualitative expectations that can be relevant for creating efficient distribution routes taking into account the delivery time and customer satisfaction. A fuzzy clustering optimization method is elaborated for the treatment of above-mentioned customer attributes for distribution management in order to generate efficient delivery strategies. A case study from Shun-Feng (SF) International Express is used to demonstrate the effectiveness and practicability of the proposed method. The obtained results show that both customer satisfaction and the net profit of the enterprise have considerably increased due to an efficient distribution management.
期刊介绍:
The objective of Computers in Industry is to present original, high-quality, application-oriented research papers that:
• Illuminate emerging trends and possibilities in the utilization of Information and Communication Technology in industry;
• Establish connections or integrations across various technology domains within the expansive realm of computer applications for industry;
• Foster connections or integrations across diverse application areas of ICT in industry.