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Mixed logit modelling of airport choice in multi-airport regions

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  • Hess, Stephane
  • Polak, John W.
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    Abstract

    This paper presents an analysis of the choice of airport by air travellers departing from the San Francisco Bay (SF-B) area. The analysis uses the mixed multinomial logit model, which allows for a random distribution of tastes across decision makers. To our knowledge, this is the first application using this model form in the analysis of airport choice. The results indicate that there is significant heterogeneity in tastes, especially with respect to the sensitivity to access time, characterised by deterministic variations between groups of travellers (business/leisure, residents/visitors) as well as random variations within groups of travellers. The analysis reinforces earlier findings showing that business travellers are far less sensitive to fare increases than leisure travellers, and are willing to pay a higher price for decreases in access time (and generally also increases in frequency) than is the case for leisure travellers. Finally, the results show that the random variation between business travellers in terms of sensitivity to access time is more pronounced than that between leisure travellers, as is the case for visitors when compared to residents.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0969699704000560
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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Air Transport Management.

    Volume (Year): 11 (2005)
    Issue (Month): 2 ()
    Pages: 59-68

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    Handle: RePEc:eee:jaitra:v:11:y:2005:i:2:p:59-68

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    Web page: http://www.journals.elsevier.com/journal-of-air-transport-management/

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    References

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    1. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    2. Furuichi, Masahiko & Koppelman, Frank S., 1994. "An analysis of air travelers' departure airport and destination choice behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 28(3), pages 187-195, May.
    3. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, October.
    4. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    5. Pels, Eric & Nijkamp, Peter & Rietveld, Piet, 2003. "Access to and competition between airports: a case study for the San Francisco Bay area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(1), pages 71-83, January.
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    Cited by:
    1. Fabio Carlucci & Andrea Cirà, 2011. "Sostenibilità istituzionale nelle scelte infrastrutturali per il trasporto aereo: il caso degli aeroporti minori," Working Papers 1102, SIET Società Italiana di Economia dei Trasporti e della Logistica.
    2. Fay Dunkerley & Andre de Palma & Stef Proost, 2009. "Spatial Asymmetric Duopoly With An Application To Brussels' Airports," Journal of Regional Science, Wiley Blackwell, vol. 49(3), pages 529-553.
    3. Edoardo Marcucci & Valerio Gatta, 2011. "Dissecting Preference Heterogeneity In Consumer Stated Choices," Working Papers 0311, CREI Università degli Studi Roma Tre, revised 2011.
    4. Stephane Hess & Denis Bolduc & John Polak, 2010. "Random covariance heterogeneity in discrete choice models," Transportation, Springer, vol. 37(3), pages 391-411, May.
    5. Fosgerau, Mogens & Bierlaire, Michel, 2007. "A practical test for the choice of mixing distribution in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 784-794, August.
    6. Balcombe, Kelvin & Fraser, Iain & Harris, Liam, 2009. "Consumer willingness to pay for in-flight service and comfort levels: A choice experiment," Journal of Air Transport Management, Elsevier, vol. 15(5), pages 221-226.
    7. Hsiao, Chieh-Yu & Hansen, Mark, 2011. "A passenger demand model for air transportation in a hub-and-spoke network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 1112-1125.
    8. Escobari, Diego & Mellado, Cristhian, 2013. "The Choice of Airport, Airline, and Departure Date and Time: Estimating the Demand for Flights," MPRA Paper 47943, University Library of Munich, Germany.
    9. Stephane Hess, 2005. "Analysing air-travel choice behaviour in the Greater London area," ERSA conference papers ersa05p736, European Regional Science Association.
    10. Zhang, Yunlong & Xie, Yuanchang, 2005. "Small community airport choice behavior analysis: A case study of GTR," Journal of Air Transport Management, Elsevier, vol. 11(6), pages 442-447.
    11. Johnson, Daniel & Hess, Stephane & Matthews, Bryan, 2014. "Understanding air travellers' trade-offs between connecting flights and surface access characteristics," Journal of Air Transport Management, Elsevier, vol. 34(C), pages 70-77.
    12. Martínez-Garcia, Esther & Ferrer-Rosell, Berta & Coenders, Germà , 2012. "Profile of business and leisure travelers on low cost carriers in Europe," Journal of Air Transport Management, Elsevier, vol. 20(C), pages 12-14.
    13. Hess, Stephane, 2007. "Posterior analysis of random taste coefficients in air travel behaviour modelling," Journal of Air Transport Management, Elsevier, vol. 13(4), pages 203-212.
    14. Elwakil, Omar S. & Dresner, Martin, 2013. "Low-cost carriers and Canadian traffic generation at US border airports," Journal of Air Transport Management, Elsevier, vol. 33(C), pages 68-72.
    15. Daniel Strobach, 2006. "Competition between airports with an application to the state of Baden-Württemberg," Diskussionspapiere aus dem Institut für Volkswirtschaftslehre der Universität Hohenheim 272/2006, Department of Economics, University of Hohenheim, Germany.

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