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Airport Choice Modeling: Empirical Evidence from a Non‐Hub Airport

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  • Leon, Steve

Abstract

A comprehensive review of airport choice modeling studies is presented in this paper, highlighting the key determinants of passenger preferences. Empirical research presented which models using binary logistic regression in the likelihood that airline travelers in the Fargo-Moorhead Metropolitan Statistical Area will not use the local airport, but instead use the competing major hub airport in Minneapolis-St. Paul, located 250 miles away as a viable origin airport. Moreover, this study investigates whether collecting empirical data from local travel agents may perhaps allow airport planners and airport managers to identify important passenger choice behaviors without incurring the added time and expense of administering formal passenger surveys. This study found that it is possible to obtain useful data from travel agents at significantly less time and effort. The significant factors obtained from the regression analysis were trip purpose, trip duration, number of connections, and airline.

Suggested Citation

  • Leon, Steve, 2011. "Airport Choice Modeling: Empirical Evidence from a Non‐Hub Airport," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 50(2).
    • Handle: RePEc:ags:ndjtrf:207293
    DOI: 10.22004/ag.econ.207293
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    References listed on IDEAS

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    1. 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.
    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. 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.
    4. Basar, Gözen & Bhat, Chandra, 2004. "A parameterized consideration set model for airport choice: an application to the San Francisco Bay Area," Transportation Research Part B: Methodological, Elsevier, vol. 38(10), pages 889-904, December.
    5. Ishii, Jun & Jun, Sunyoung & Van Dender, Kurt, 2009. "Air travel choices in multi-airport markets," Journal of Urban Economics, Elsevier, vol. 65(2), pages 216-227, March.
    6. Hess, Stephane & Polak, John W., 2006. "Exploring the potential for cross-nesting structures in airport-choice analysis: A case-study of the Greater London area," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 42(2), pages 63-81, March.
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    Cited by:

    1. Pagoni, Ioanna & Psaraki-Kalouptsidi, Voula, 2016. "The impact of carbon emission fees on passenger demand and air fares: A game theoretic approach," Journal of Air Transport Management, Elsevier, vol. 55(C), pages 41-51.
    2. Liu, Shuli & Wan, Yulai & Zhang, Anming, 2021. "Does high-speed rail development affect airport productivity? Evidence from China and Japan," Transport Policy, Elsevier, vol. 110(C), pages 1-15.
    3. Hatziioannidu, Fani & Polydoropoulou, Amalia, 2022. "Identifying passenger preferences for alternative ferry transport hubs," Research in Transportation Economics, Elsevier, vol. 96(C).
    4. Gudmundsson, Sveinn & Paleari, Stefano & Redondi, Renato, 2014. "Spillover effects of the development constraints in London Heathrow Airport," Journal of Transport Geography, Elsevier, vol. 35(C), pages 64-74.
    5. Leon, Steven & Uddin, Nizam, 2017. "Airline Ancillary Services: An Investigation into Passenger Purchase Behavior," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 56(1), April.

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