Bergantino, AS, Capurso, M and Hess, S orcid.org/0000-0002-3650-2518 (2020) Modelling regional accessibility to airports using discrete choice models: An application to a system of regional airports. Transportation Research Part A: Policy and Practice, 132. pp. 855-871. ISSN 0965-8564
Abstract
In this paper, we analyse residents' decisions regarding airport access mode in Apulia, a relatively peripheral multi-airport region in Italy. Both revealed and stated preferences data are used to estimate probabilistic demand models. The results are employed to calculate the relevant elasticities, separately for airport users and non-users, with respect to dedicated existing and planned/potential public transport services. We measure the effectiveness of specific policies/actions aimed at generating a shift from private modes (car and taxi) towards public transport, rationalising mobility towards the existing airports. Accessibility is one of the key factors in airports' provision, and an efficient public transport system might represent both an alternative to opening “local” – often costly and inefficient – airports in the same catchment area and a means to exploit economies of scale aggregating demand for existing airports.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 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: | Airports; Regional accessibility; Revealed and stated preferences |
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: Choice Modelling |
Funding Information: | Funder Grant number EU - European Union 615596 |
Depositing User: | Symplectic Publications |
Date Deposited: | 22 May 2020 12:36 |
Last Modified: | 14 Jan 2021 01:38 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.tra.2019.12.012 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:161101 |