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Pengxiang Zhao

Forskare

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Exploring the structural characteristics of intra-urban shared freight network and their associations with socioeconomic status

Författare

  • Zijian Guo
  • Pengxiang Zhao
  • Ahmad M. Senousi
  • Xintao Liu
  • Ali Mansourian

Summary, in English

In recent years, shared freight systems have emerged in many cities as a new modality of freight transportation. However, little attention has been paid to the impact of a city's socioeconomic status on the characteristics of a shared freight network. To fill this gap, in this study, the structural characteristics of an intra-urban shared freight network are measured from the perspective of complex networks, and the correlations between network structure and socioeconomic status are examined. A case study is conducted in Hong Kong using large amounts of GPS trajectory data for freight vehicles and socioeconomic data. The results show that socioeconomic variables such as population size, percentage of elderly residents, percentage of residents with a marital status classified as “other” (i.e., separated, widowed, or divorced), and percentage of residents employed in the tertiary sector have distinct correlations with the structural characteristics. These correlations display spatial non-stationarity. This research can potentially assist decision-makers in improving the operating efficiency of shared freight systems and the governance of digital freight transport.

Avdelning/ar

  • MECW: The Middle East in the Contemporary World
  • Institutionen för naturgeografi och ekosystemvetenskap
  • Centrum för geografiska informationssystem (GIS-centrum)
  • Centrum för Mellanösternstudier (CMES)
  • BECC: Biodiversity and Ecosystem services in a Changing Climate

Publiceringsår

2023-07

Språk

Engelska

Publikation/Tidskrift/Serie

Travel Behaviour and Society

Volym

32

Dokumenttyp

Artikel i tidskrift

Förlag

Elsevier

Ämne

  • Earth and Related Environmental Sciences
  • Transport Systems and Logistics

Nyckelord

  • Complex network
  • Geographically weighted regression
  • Shared freight transportation
  • Socioeconomic status

Status

Published

ISBN/ISSN/Övrigt

  • ISSN: 2214-367X