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.

The Growth of E-Commerce Due to COVID-19 and the Need for Urban Logistics Centers Using Electric Vehicles: Bratislava Case Study

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Use of artificial intelligence in last mile delivery

“…It represents a part of logistics, which includes the direction of vehicles to physical distribution and thus plays a crucial role in ensuring the delivery of goods, in the right quantity and within predetermined deadlines, to customers. [1,2,3] In many cases, logistics providers, face many challenges and problems in overcoming the last mile. Such challenges include: high order fulfillment costs for high price sensitive customers, strong competitive external pressure on free delivery services, increased customer expectations due to short delivery times, individually scheduled delivery times, the ability to track and customize specific shipments along with the possibility of choosing an alternative place of delivery of consignments as well as a large number of unsuccessful attempts to deliver or return products.…”

Logistics Service Mode Selection for Last Mile Delivery: An Analysis Method Considering Customer Utility and Delivery Service Cost

“…The rapid development of last mile delivery is mainly driven by accelerated urbanization and population growth [8], e-commerce development [9,10], the change of consumer behavior [9,11], innovation [12] and application of new technology [13]. In addition, some factors can affect the logistics service of express enterprises, such as delivery service cost, delivery capacity, delivery efficiency, customer satisfaction, customer selection behavior and carbon emissions [14][15][16][17]. In this study, we mainly focus on the impacts of customer utility and delivery service cost.…”