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A multimodal transport chain choice model for container transport

Authors :
de Bok, M.A. (author)
de Jong, Gerard (author)
Tavasszy, Lorant (author)
Van Meijeren, Jaco (author)
Davydenko, Igor (author)
Benjamins, Michiel (author)
Groot, Noortje (author)
Miete, Onno (author)
Van den Berg, Monique (author)
de Bok, M.A. (author)
de Jong, Gerard (author)
Tavasszy, Lorant (author)
Van Meijeren, Jaco (author)
Davydenko, Igor (author)
Benjamins, Michiel (author)
Groot, Noortje (author)
Miete, Onno (author)
Van den Berg, Monique (author)
Publication Year :
2018

Abstract

A large part of freight transport movements are part of a multimodal transport chain, in particular for port-related containerized transport flows. Because data of multimodal transports are unavailable it is challenging to develop a multimodal transport chain models. This paper describes the development of a new module for multimodal transport chains for modelling container transport within the Dutch strategic freight transport model “BasGoed”. The choice model distinguishes unimodal, bi-modal or tri-modal transport chains, depending on whether the transport chain is port-related. A direct road chain is available between each production and consumption combination; direct barge or rail transport is only available between seaports. A route enumeration module generates a choice set for each observed uni- or multimodal container transport. Since no directly observed PC data are available, a synthetic dataset was constructed with container flows between locations of production and consumption, using uni-modal observed transport data. Main assumption is that each container transported by rail or barge requires a road leg at the side of destination and/or origin, to complete the multimodal transport chain. Discrete choice models were estimated with different model structures. The best choice model that was found was a multinomial logit model, segmented by port dependency. The results show that a choice model can be estimated with significant parameters, and with plausible model sensitivities.<br />Transport and Planning<br />Transport and Logistics

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1062420399
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.1016.j.trpro.2018.09.049