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A complex network approach to understand commercial vehicle movement

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  • Johan Joubert
  • Kay Axhausen

Abstract

We introduce complex network analysis and use a commercial vehicle’s observed trip as a proxy for a business relation between two facilities in its activity chain. We extract facility locations by applying density-based clustering to GPS data of commercial vehicle activities. The network among the facilities is then extracted by analysing the activity chains of more than 25,000 commercial vehicles. Centrality metrics prove useful and novel in identifying and locating key logistics players. Transport planners and decision makers can benefit from such an approach as it allows them to design more targeted initiatives and policy interventions. Copyright Springer Science+Business Media, LLC. 2013

Suggested Citation

  • Johan Joubert & Kay Axhausen, 2013. "A complex network approach to understand commercial vehicle movement," Transportation, Springer, vol. 40(3), pages 729-750, May.
    • Handle: RePEc:kap:transp:v:40:y:2013:i:3:p:729-750
    DOI: 10.1007/s11116-012-9439-0
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    References listed on IDEAS

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    Cited by:

    1. Johan Joubert & Sumarie Meintjes, 2015. "Computational considerations in building inter-firm networks," Transportation, Springer, vol. 42(5), pages 857-878, September.
    2. Nadia M. Viljoen & Johan W. Joubert, 2018. "The Road most Travelled: The Impact of Urban Road Infrastructure on Supply Chain Network Vulnerability," Networks and Spatial Economics, Springer, vol. 18(1), pages 85-113, March.
    3. Trent, Nadia M. & Joubert, Johan W., 2022. "Logistics sprawl and the change in freight transport activity: A comparison of three measurement methodologies," Journal of Transport Geography, Elsevier, vol. 101(C).
    4. 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.
    5. Joubert, Johan W. & Meintjes, Sumarie, 2015. "Repeatability & reproducibility: Implications of using GPS data for freight activity chains," Transportation Research Part B: Methodological, Elsevier, vol. 76(C), pages 81-92.
    6. Meead Saberi & Hani S. Mahmassani & Dirk Brockmann & Amir Hosseini, 2017. "A complex network perspective for characterizing urban travel demand patterns: graph theoretical analysis of large-scale origin–destination demand networks," Transportation, Springer, vol. 44(6), pages 1383-1402, November.
    7. Magdalena I. Asborno & Sarah Hernandez & Manzi Yves, 2021. "GIS-based identification and visualization of multimodal freight transportation catchment areas," Transportation, Springer, vol. 48(6), pages 2939-2968, December.
    8. Viljoen, Nadia M. & Joubert, Johan W., 2019. "Supply chain micro-communities in urban areas," Journal of Transport Geography, Elsevier, vol. 74(C), pages 211-222.

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