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.


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    Title :

    A complex network approach to understand commercial vehicle movement


    Contributors:

    Published in:

    Publication date :

    2012




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    BKL:    74.75$jVerkehrsplanung$jVerkehrspolitik / 55.80$jVerkehrswesen$jTransportwesen: Allgemeines / 55.80 Verkehrswesen, Transportwesen: Allgemeines / 74.75 Verkehrsplanung, Verkehrspolitik



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