Tapia, RJ, de Jong, G orcid.org/0000-0003-3405-6523, Larranaga, AM et al. (1 more author) (2020) Application of MDCEV to infrastructure planning in regional freight transport. Transportation Research Part A: Policy and Practice, 133. pp. 255-271. ISSN 0965-8564
Abstract
The main objective of the paper is to develop a model capable of evaluating the societal impact of rail infrastructure investment in Argentina, using a Multiple Discrete Extreme Value Model (MDCEV) estimated on Stated and Revealed preference data. The decision modelled is the mode and port choice at a planning level, where multiple alternatives can be chosen simultaneously. The relevant variables were the Free Alongside Ship (FAS) price, freight transport cost, travel time and lead time, including non-observed heterogeneity in the modelling. As a consequence, the willingness to pay measures that are used for the cost benefit analysis become non-deterministic. To include this effect simulated WTP measurements were included and compared to a deterministic and risk based approach. Two projects were tested and both showed that the deterministic approach gives higher Benefit/Cost ratio. This paper raises the concern that if non-observed heterogeneity is not considered in project evaluation it may provide misleading results and potentially lead to wrong investment priorities for the public sector.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 Elsevier Ltd. All rights reserved. This is an author produced version of an article published in Transportation Research Part A: Policy and Practice. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | MDCEV; Multiple discreteness; Freight choice modelling; Cost benefit analysis |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Economics and Discrete Choice (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 13 Mar 2020 11:27 |
Last Modified: | 07 Feb 2021 01:38 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.tra.2020.01.016 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:158391 |