Heterogeneity of Spatial Distribution and Factors Influencing Unattended Locker Points in Guangzhou, China: The Case of Hive Box

Abstract

Hive Box is a company that operates a network of express unattended collection and delivery points (UCDPs) in China. Hive Box distribution enhances community-based end-to-end delivery services and low-carbon city logistics. It is argued that UCDPs compared with attended collection and delivery points (ACDPs) should be considered for further investigation. Therefore, the present study employed kernel density estimation, spatial autocorrelation analysis, and geographically weighted regression to investigate the spatial heterogeneity of Hive Box distribution across Guangzhou. Hive Box location data were collected from smartphone apps. The results were as follows: (1) the kernel density declined from the city center toward the outskirts, and showed point-like spatial agglomerations in the city center; (2) the Moran’s I index analysis showed that Hive Box distribution exhibited spatial agglomeration from a global perspective and geographic variations in locality in space; the heterogeneity of urban–rural differences implies the uneven development of Hive Box distribution in Guangzhou; and (3) the factors influencing Hive Box distribution were multilevel, and their effects were complex and varied across regions. These results shed light on the agglomeration and heterogeneity characteristics of the spatial distribution and influencing factors of Hive Boxes. For an enhanced community-based end-to-end delivery service, this study suggested the identification of the geographic variations of Hive Box distribution and the combined effects of multiple factors in intensifying the infrastructure of unattended locker points.

Keywords

• last-mile logistics
• end-to-end delivery service
• collection and delivery point (CDP)
• smart locker
• Hive Box
• geographically weighted regression (GWR)