Bottlenecks and Regional Economic Impact: Simulations with the CODE24 Transport Model

Hansjörg Drewello (), Marcel Huschebeck () and Norbert Schick ()
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Hansjörg Drewello: University of Applied Sciences Kehl
Marcel Huschebeck: PTV Group
Norbert Schick: PTV Group

A chapter in Integrated Spatial and Transport Infrastructure Development, 2016, pp 117-131 from Springer

Abstract: Abstract Bottlenecks in transport infrastructure will change the behavior of logistics companies because of increasing costs of transportation. If a bottleneck in a railway network occurs, railway freight transport will be shifted to roadways. Railway congestion causes, for example, a decrease in reliability and a considerable increase in transport costs, and thus road transport becomes less expensive. The CODE24 Transport Model supports decision-making about choice of transport modes. All available information potentially affecting those decisions, such as regions, transport networks, terminals and logistic services, costs as well as transport or monetary flows, are integrated into the model. The model tries to find the shortest or most efficient route, e.g. with regard to transport costs. In this article, economic effects along the railway corridor Rotterdam-Genoa were analyzed in a simulation of three different types of bottlenecks on railways by using the CODE24 Transport Model. The simulation shows a shift of freight transport from rail to road or from rail to barge, depending on different transport distances. The change of intermodal behavior increases transport costs, which can be calculated within the model. The simulation allows a better insight into the regional and overall costs generated by transport bottlenecks. The analysis indicates that an increase in transport costs for one transport mode, due to a bottleneck, has an impact on all the regions along the corridor and even more so on specific regions outside the corridor.

Keywords: Transport Cost; Transport Mode; Capacity Utilisation; Transport Infrastructure; Shipping Route (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/978-3-319-15708-5_7

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