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Research on the Complex Characteristics of Freight Transportation from a Multiscale Perspective Using Freight Vehicle Trip Data

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  • Ling Zhang

    (School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, Sichuan, China
    Yunnan Integrated Transport Development and Regional Logistics Management Think Tank, Kunming University of Science and Technology, Kunming 650504, Yunnan, China
    Yunnan Engineering Research Center of Modern Logistics, Kunming University of Science and Technology, Kunming 650504, Yunnan, China)

  • Jingjing Hao

    (School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, Sichuan, China
    Yunnan Integrated Transport Development and Regional Logistics Management Think Tank, Kunming University of Science and Technology, Kunming 650504, Yunnan, China
    Yunnan Engineering Research Center of Modern Logistics, Kunming University of Science and Technology, Kunming 650504, Yunnan, China)

  • Xiaofeng Ji

    (Yunnan Integrated Transport Development and Regional Logistics Management Think Tank, Kunming University of Science and Technology, Kunming 650504, Yunnan, China
    Yunnan Engineering Research Center of Modern Logistics, Kunming University of Science and Technology, Kunming 650504, Yunnan, China)

  • Lan Liu

    (School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, Sichuan, China)

Abstract

To better guide the sustainable developing of freight transport aligning with environmental objectives it is of strategic importance to capture freight transportation characteristics more realistically. This paper characterizes freight transportation by using a complex network approach from multidimensional perspectives based on freight vehicle trips data. We first build two subnetworks from prefecture-level city-scale and county-level city-scale. Subsequently, network analysis indices based on complex network theory were applied to examine the topological structure and complexity of the freight transportation networks. Furthermore, the community detection method is introduced to reveal the networks’ clustering characteristics. The findings show that the prefecture-level city-scale network and the county-level city-scale network both have obvious small-world network characteristics, but the prefecture-level city-scale network has higher operating efficiency for goods movement. Additionally, the influence of the cross-border effect on the freight transportation network was verified. In terms of the community structure, the freight network shows distinct clustering features only at the county-level city-scale.

Suggested Citation

  • Ling Zhang & Jingjing Hao & Xiaofeng Ji & Lan Liu, 2019. "Research on the Complex Characteristics of Freight Transportation from a Multiscale Perspective Using Freight Vehicle Trip Data," Sustainability, MDPI, vol. 11(7), pages 1-20, March.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:7:p:1897-:d:218262
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    References listed on IDEAS

    as
    1. Jun Yang & Andong Guo & Xueming Li & Tai Huang, 2018. "Study of the Impact of a High-Speed Railway Opening on China’s Accessibility Pattern and Spatial Equality," Sustainability, MDPI, vol. 10(8), pages 1-13, August.
    2. Didier Plat & Charles Raux, 1998. "Frontier Impedance Effects And The Growth Of International Exchanges: An Empirical Analysis For France," Papers in Regional Science, Wiley Blackwell, vol. 77(2), pages 155-172, April.
    3. Luo, Xiao & Dong, Liang & Dou, Yi & Liang, Hanwei & Ren, Jingzheng & Fang, Kai, 2016. "Regional disparity analysis of Chinese freight transport CO2 emissions from 1990 to 2007: Driving forces and policy challenges," Journal of Transport Geography, Elsevier, vol. 56(C), pages 1-14.
    4. Lordan, Oriol & Sallan, Jose M. & Simo, Pep, 2014. "Study of the topology and robustness of airline route networks from the complex network approach: a survey and research agenda," Journal of Transport Geography, Elsevier, vol. 37(C), pages 112-120.
    5. Chen, Bi Yu & Lam, William H.K. & Sumalee, Agachai & Li, Qingquan & Li, Zhi-Chun, 2012. "Vulnerability analysis for large-scale and congested road networks with demand uncertainty," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 501-516.
    6. T. Ravi Kumar, 2002. "The Impact of Regional Infrastructure Investment in India," Regional Studies, Taylor & Francis Journals, vol. 36(2), pages 194-200.
    7. Ye Li & Lei Bao & Wenxiang Li & Haopeng Deng, 2016. "Inventory and Policy Reduction Potential of Greenhouse Gas and Pollutant Emissions of Road Transportation Industry in China," Sustainability, MDPI, vol. 8(12), pages 1-19, November.
    8. Fan, Shenggen & Chan-Kang, Connie, 2008. "Regional road development, rural and urban poverty: Evidence from China," Transport Policy, Elsevier, vol. 15(5), pages 305-314, September.
    9. Jenelius, Erik & Petersen, Tom & Mattsson, Lars-Göran, 2006. "Importance and exposure in road network vulnerability analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(7), pages 537-560, August.
    10. Viljoen, Nadia M. & Joubert, Johan W., 2016. "The vulnerability of the global container shipping network to targeted link disruption," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 396-409.
    11. Ballantyne, Erica E.F. & Lindholm, Maria & Whiteing, Anthony, 2013. "A comparative study of urban freight transport planning: addressing stakeholder needs," Journal of Transport Geography, Elsevier, vol. 32(C), pages 93-101.
    12. Yu Liu & Chaogui Kang & Song Gao & Yu Xiao & Yuan Tian, 2012. "Understanding intra-urban trip patterns from taxi trajectory data," Journal of Geographical Systems, Springer, vol. 14(4), pages 463-483, October.
    13. Meiling He & Jiaren Shen & Xiaohui Wu & Jianqiang Luo, 2018. "Logistics Space: A Literature Review from the Sustainability Perspective," Sustainability, MDPI, vol. 10(8), pages 1-24, August.
    14. Wang, Jiaoe & Mo, Huihui & Wang, Fahui, 2014. "Evolution of air transport network of China 1930–2012," Journal of Transport Geography, Elsevier, vol. 40(C), pages 145-158.
    15. Martine Mostert & Sabine Limbourg, 2016. "External Costs as Competitiveness Factors for Freight Transport — A State of the Art," Transport Reviews, Taylor & Francis Journals, vol. 36(6), pages 692-712, November.
    16. Johan Joubert & Kay Axhausen, 2013. "A complex network approach to understand commercial vehicle movement," Transportation, Springer, vol. 40(3), pages 729-750, May.
    17. Boarnet, Marlon G. & Hong, Andy & Santiago-Bartolomei, Raul, 2017. "Urban spatial structure, employment subcenters, and freight travel," Journal of Transport Geography, Elsevier, vol. 60(C), pages 267-276.
    18. Ni, Linglin & Wang, Xiaokun (Cara) & Zhang, Dapeng, 2016. "Impacts of information technology and urbanization on less-than-truckload freight flows in China: An analysis considering spatial effects," Transportation Research Part A: Policy and Practice, Elsevier, vol. 92(C), pages 12-25.
    19. Allen, J. & Browne, M. & Cherrett, T., 2012. "Investigating relationships between road freight transport, facility location, logistics management and urban form," Journal of Transport Geography, Elsevier, vol. 24(C), pages 45-57.
    20. Dai, Liang & Derudder, Ben & Liu, Xingjian, 2018. "The evolving structure of the Southeast Asian air transport network through the lens of complex networks, 1979–2012," Journal of Transport Geography, Elsevier, vol. 68(C), pages 67-77.
    21. Liu, Xi & Gong, Li & Gong, Yongxi & Liu, Yu, 2015. "Revealing travel patterns and city structure with taxi trip data," Journal of Transport Geography, Elsevier, vol. 43(C), pages 78-90.
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