Logistics distribution optimization: Fuzzy clustering analysis of e-commerce customers’ demands

Abstract

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.