Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/209287 
Year of Publication: 
2015
Citation: 
[Editor:] Blecker, Thorsten [Editor:] Kersten, Wolfgang [Editor:] Ringle, Christian M. [Title:] Operational Excellence in Logistics and Supply Chains: Optimization Methods, Data-driven Approaches and Security Insights. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 22 [ISBN:] 978-3-7375-4058-2 [Publisher:] epubli GmbH [Place:] Berlin [Year:] 2015 [Pages:] 233-266
Publisher: 
epubli GmbH, Berlin
Abstract: 
Macroeconomic freight transport models serve as decision support for transport policy development. To evaluate infrastructure investments or policy measures these tools need to capture the underlying complexity of freight transport networks in a sufficient way. Recent developments in this field outline possibilities to combine aggregated and disaggregated approaches in freight transport modelling in order to integrate more realistic freight agent behaviour. In contrast to aggregated models, disaggregated approaches are able to simulate the decision behaviour on the microlevel of an individual decision maker. In maritime container supply chains liner carriers or their brokers/agents and freight forwarders face a variety of interconnected logistical choices such as carrier, port, mode, route, shipment, or inventory choice. Modelling at least parts of these choices in disaggregated way could be of high value for adequate maritime hinterland policy development. This paper provides both an overview of present freight transport models with and without a logistics step and applied methods to study maritime supply chain freight agents' behaviour. A summarizing framework for behavioural freight transport modelling in maritime container supply chains is introduced. Finally, the framework is applied to a container freight transport model under development.
Subjects: 
Freight Transport Modelling
Maritime Container Supply Chain
Choice Modelling
Creative Commons License: 
cc-by-sa Logo
Document Type: 
Conference Paper

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