Collaboration Model for Service Clustering in Last-Mile Delivery

Abstract

As e-commerce is rapidly expanding, efficient and competitive product delivery system to the final customer is highly required. Recently, the emergence of a smart platform is leading the transformation of distribution, performance, and quality in express delivery services, especially in the last-mile delivery. The business to consumer (B2C) through smart platforms such as Amazon in America and Coupang in Korea utilizes the differentiated delivery rates to increase the market share. In contrast, the small and medium-sized express delivery companies with low market share are trying hard to expand their market share. In order to fulfill all customer needs, collaboration is needed. This study aims to construct a collaboration model to maximize the net profit by considering the market density of each company. A Baduk board game is used to derive the last-mile delivery time function of market density. All companies in collaboration have to specialize the delivery items into certain service clustering types, which consist of regular, big sized/weighted, and cold items. The multi-objective programming model is developed based on max-sum and max-min criteria. The Shapley value and nucleolus approaches are applied to find the profit allocation. Finally, the applicability of the proposed collaboration model is shown through a numerical example.