Investigation of Home Delivery Models and Logistics Services in China

Abstract

The last-mile issue is of great concern in coping with the considerable development of the internet shopping market in China. Several issues arise from home delivery activities for fulfilling internet shopping orders; for example, increased operating costs for handling failed home deliveries, and deteriorating traffic conditions resulting from frequent delivery trips. To improve the logistics efficiency of home delivery operations and solve the problem of delivery failures, pick-up points (PPs) and self-delivery boxes (SDBs) are being implemented in China. This study investigates three home delivery models including the traditional model, the PP model, and the SDB model. Under each model, the carrier’s delivery distance and the customer’s collection distance are calculated. According to the distance, the costs of the three delivery models are compared. To simulate the carrier’s delivery route, an ant colony algorithm combined with genetic algorithm is developed to optimize the delivery route in this research. The research findings are: (1) Both the PP model and the SDB model are capable of reducing the customer’s collection cost significantly, by between 29.1% and 84%, when at least 30% of home deliveries are missed. (2) The SDB model is more favorable in relation to reducing the delivery costs of the express company, by between 67.1% and 71.3% when the proportion of missed home deliveries ranges from 20% to 50%. (3) Among PPs using the post office, convenience store, and subway station, the subway station network is the most effective scheme in relation to reducing the customer’s collection cost, by 84%.