IDEAS home Printed from https://ideas.repec.org/a/eee/jaitra/v11y2005i2p59-68.html
   My bibliography  Save this article

Mixed logit modelling of airport choice in multi-airport regions

Author

Listed:
  • Hess, Stephane
  • Polak, John W.

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.

Suggested Citation

  • Hess, Stephane & Polak, John W., 2005. "Mixed logit modelling of airport choice in multi-airport regions," Journal of Air Transport Management, Elsevier, vol. 11(2), pages 59-68.
    • Handle: RePEc:eee:jaitra:v:11:y:2005:i:2:p:59-68
    DOI: 10.1016/j.jairtraman.2004.09.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0969699704000560
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jairtraman.2004.09.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, September.
    2. 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.
    3. 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.
    4. 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.
    5. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Birolini, Sebastian & Malighetti, Paolo & Redondi, Renato & Deforza, Paolo, 2019. "Access mode choice to low-cost airports: Evaluation of new direct rail services at Milan-Bergamo airport," Transport Policy, Elsevier, vol. 73(C), pages 113-124.
    2. 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.
    3. Jianhua Wang & Jiaye Ge & Yuting Ma, 2018. "Urban Chinese Consumers’ Willingness to Pay for Pork with Certified Labels: A Discrete Choice Experiment," Sustainability, MDPI, vol. 10(3), pages 1-14, February.
    4. Scaccia, Luisa & Marcucci, Edoardo & Gatta, Valerio, 2023. "Prediction and confidence intervals of willingness-to-pay for mixed logit models," Transportation Research Part B: Methodological, Elsevier, vol. 167(C), pages 54-78.
    5. Frick, Bernd & Barros, Carlos Pestana & Prinz, Joachim, 2010. "Analysing head coach dismissals in the German "Bundesliga" with a mixed logit approach," European Journal of Operational Research, Elsevier, vol. 200(1), pages 151-159, January.
    6. Meredith Fowlie, 2010. "Emissions Trading, Electricity Restructuring, and Investment in Pollution Abatement," American Economic Review, American Economic Association, vol. 100(3), pages 837-869, June.
    7. Cho, Woohyun & Windle, Robert J. & Dresner, Martin E., 2017. "The impact of operational exposure and value-of-time on customer choice: Evidence from the airline industry," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 455-471.
    8. de Ayala, Amaia & Hoyos, David & Mariel, Petr, 2015. "Suitability of discrete choice experiments for landscape management under the European Landscape Convention," Journal of Forest Economics, Elsevier, vol. 21(2), pages 79-96.
    9. Barros, Carlos Pestana & Ferreira, Candida & Williams, Jonathan, 2007. "Analysing the determinants of performance of best and worst European banks: A mixed logit approach," Journal of Banking & Finance, Elsevier, vol. 31(7), pages 2189-2203, July.
    10. Martínez-Pardo, Ana & Orro, Alfonso & Garcia-Alonso, Lorena, 2020. "Analysis of port choice: A methodological proposal adjusted with public data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 136(C), pages 178-193.
    11. Bernard Fortin & Nicolas Jacquemet & Bruce Shearer, 2008. "Policy Analysis in Health-Services Market: Accounting for Quality and Quantity," Annals of Economics and Statistics, GENES, issue 91-92, pages 293-319.
    12. Juan Carlos Martín & Concepción Román & Cira Mendoza, 2018. "Determinants for sun-and-beach self-catering accommodation selection," Tourism Economics, , vol. 24(3), pages 319-336, May.
    13. Deka, Devajyoti & Carnegie, Jon, 2021. "Predicting transit mode choice of New Jersey workers commuting to New York City from a stated preference survey," Journal of Transport Geography, Elsevier, vol. 91(C).
    14. Thai, Thao & Lancsar, Emily & Spinks, Jean & Freeman, Christopher & Chen, Gang, 2024. "Understanding Australian pharmacy degree holders’ job preferences through the lens of motivation-hygiene theory," Social Science & Medicine, Elsevier, vol. 348(C).
    15. Czajkowski, Mikołaj & Bartczak, Anna & Giergiczny, Marek & Navrud, Stale & Żylicz, Tomasz, 2014. "Providing preference-based support for forest ecosystem service management," Forest Policy and Economics, Elsevier, vol. 39(C), pages 1-12.
    16. Michael P. Keane & Nada Wasi, 2013. "The Structure of Consumer Taste Heterogeneity in Revealed vs. Stated Preference Data," Economics Papers 2013-W10, Economics Group, Nuffield College, University of Oxford.
    17. Gillespie Rob & Kragt Marit E., 2012. "Accounting for Nonmarket Impacts in a Benefit-Cost Analysis of Underground Coal Mining in New South Wales, Australia," Journal of Benefit-Cost Analysis, De Gruyter, vol. 3(2), pages 1-29, May.
    18. John V. Colias & Stella Park & Elizabeth Horn, 2021. "Optimizing B2B product offers with machine learning, mixed logit, and nonlinear programming," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(3), pages 157-172, September.
    19. Isler, Cassiano Augusto & Blumenfeld, Marcelo & Caldeira, Gabriel Pereira & Roberts, Clive, 2024. "Long-Distance railway mode choice in Brazil: Evidence from a discrete choice experiment," Research in Transportation Economics, Elsevier, vol. 104(C).
    20. Siikamaki, Juha & Layton, David F., 2007. "Discrete choice survey experiments: A comparison using flexible methods," Journal of Environmental Economics and Management, Elsevier, vol. 53(1), pages 122-139, January.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jaitra:v:11:y:2005:i:2:p:59-68. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/journal-of-air-transport-management/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.