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A decision analysis framework for intermodal transport: Comparing fuel price increases and the internalisation of external costs

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  • Macharis, Cathy
  • Van Hoeck, Ellen
  • Pekin, Ethem
  • van Lier, Tom
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    Abstract

    This paper presents the impact of fuel price increases on the market area of intermodal transport terminals. Aim of this research is to determine whether an increase in fuel prices is sufficient enough to raise the market area of intermodal transport to the same degree that would be accomplished by stimulating intermodal transport through policy instruments. Therefore, several fuel price scenarios are analysed in order to verify the impact of different fuel price evolutions on the market area of unimodal road transport compared to intermodal transport in Belgium. The LAMBIT-model (Location Analysis for Belgian Intermodal Terminals), which is a GIS-based model (Macharis and Pekin, 2008), is used to analyse the different fuel price increases and enables a visualisation of the impact on the market area. The LAMBIT model incorporates the different network layers for each transport mode by setting up a GIS network that includes four different layers: the road network, the rail network, the inland waterways network and the final haulage network. The geographic locations of the intermodal terminals and the port of Antwerp are added as nodes in the network and the Belgian municipality centres are defined and connected to the different network layers. Based on the different fuel price scenarios representing respectively a fuel price increase with 10% (low price case), 50% (business as usual case) and 90% (high price case), the results of the LAMBIT model show that the market areas rise in favour of intermodal barge/road and intermodal rail/road. Depending on the scenario, the degree of modal shift however differs. Additionally, in order to compare policy measures with the effect of a fuel price increase, the internalisation of the external costs is analysed with the LAMBIT model. For some years, the European Commission is supporting the idea that transportation costs should reflect the true impacts on environment and society, and is relentlessly pushing towards the so called 'internalisation of external costs' as a policy instrument in order to establish fair and efficient pricing of different transport modes. This requires monetarizing the external effects of transport and adding them to the already internalized costs in order to give the correct price signals. Results of this comparative analysis performed with the LAMBIT model are also presented in this paper.

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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part A: Policy and Practice.

    Volume (Year): 44 (2010)
    Issue (Month): 7 (August)
    Pages: 550-561

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    Handle: RePEc:eee:transa:v:44:y:2010:i:7:p:550-561

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    Related research

    Keywords: Intermodal transport Fuel price External costs Location analysis GIS network model;

    References

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    1. Ricci, Andrea & Black, Ian, 2005. "The Social Costs of Intermodal Freight Transport," Research in Transportation Economics, Elsevier, vol. 14(1), pages 245-285, January.
    2. Bontekoning, Y. M. & Macharis, C. & Trip, J. J., 2004. "Is a new applied transportation research field emerging?--A review of intermodal rail-truck freight transport literature," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(1), pages 1-34, January.
    3. Erik T. Verhoef, 2000. "articles: The implementation of marginal external cost pricing in road transport Long run vs short run and first-best vs second-best," Papers in Regional Science, Springer, vol. 79(3), pages 307-332.
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    Cited by:
    1. Bigazzi, Alexander Y. & Figliozzi, Miguel A., 2013. "Marginal costs of freeway traffic congestion with on-road pollution exposure externality," Transportation Research Part A: Policy and Practice, Elsevier, vol. 57(C), pages 12-24.
    2. Iannone, Fedele, 2012. "The private and social cost efficiency of port hinterland container distribution through a regional logistics system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(9), pages 1424-1448.
    3. Reis, Vasco, 2014. "Analysis of mode choice variables in short-distance intermodal freight transport using an agent-based model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 61(C), pages 100-120.
    4. Bastani, Parisa & Heywood, John B. & Hope, Chris, 2012. "The effect of uncertainty on US transport-related GHG emissions and fuel consumption out to 2050," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 517-548.

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