Mobility heterogeneity of urban freight areas: Geospatial evidence from shared logistics dynamics

Zidong Yu, Haotian Wang and Xintao Liu

Transportation Research Part E: Logistics and Transportation Review, 2024, vol. 188, issue C

Abstract: Amid rising mobility services in cities, the logistics sector plays a crucial role in envisioning daily services for local neighborhoods. Previous research has primarily identified key freight areas (KFAs) in small-scale regions using traditional census and travel survey data. However, differing from KFAs, other areas with distinct freight patterns remain largely unexamined, and there is a lack of comprehensive indicators to evaluate the travel behaviors of large-scale freight vehicles. This study introduces a data-driven geospatial framework to characterize and understand the patterns exhibited by different freight areas through freight dynamics data collected in cities. To analyze key aspects of freight mobility within spatial units, a set of areal indicators is developed using GPS trajectories of shared freight vehicles in Hong Kong. Descriptive statistics illustrate the inherent differences across various areas and their spatial distributions. A hierarchical clustering approach groups all areas based on proposed indicators, providing a quantitative evaluation of collective spatial patterns. The analysis also explores the non-linear relationships between different categories of freight activities and the local built environments and socioeconomic conditions. The results suggest a strong spatial heterogeneity in the areal mobility profile of Hong Kong. Loading and unloading behaviors are frequently observed in districts such as Eastern Kowloon, Kwai Chung, and the Airport, highlighting prevalent freight trip origins and destinations. In contrast, areas with high transit times are mostly found in suburban regions, particularly on the periphery. This study provides essential insights for area-based planning and management of urban freight activities, with relevant practical implications.

Keywords: Key freight areas (KFAs); Shared logistics sector; Areal freight profile; Collective mobility patterns; Spatial heterogeneity (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.tre.2024.103657

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