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Private vs. Business and Rail vs. Air Passengers: Willingness to pay for Transport Attributes

Author

Listed:
  • Carlsson, Fredrik

    (Department of Economics, School of Economics and Commercial Law, Göteborg University)

Abstract

Using a stated preference survey on passengers travelling by rail or air between the two largest cities in Sweden, we investigate passenger's willingness to pay for improvements of different attributes of the transport modes. We find that both private and business passengers put a substantial value on improvements of the environmental impact from both rail and air. In general, private passengers have much lower fare equivalents for the attribute, which is explained by the fact that business passengers do not pay for the trips themselves. Further, air passengers have higher fare equivalents than what rail passengers have for both rail and air attributes.

Suggested Citation

  • Carlsson, Fredrik, 1999. "Private vs. Business and Rail vs. Air Passengers: Willingness to pay for Transport Attributes," Working Papers in Economics 14, University of Gothenburg, Department of Economics.
    • Handle: RePEc:hhs:gunwpe:0014
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    Cited by:

    1. Rodrigo Acuna-Agost & Eoin Thomas & Alix Lhéritier, 2021. "Price elasticity estimation for deep learning-based choice models: an application to air itinerary choices," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(3), pages 213-226, June.
    2. Freund-Feinstei, Uzi & Bekhor, Shlomo, 2017. "Airline Itinerary Choice In A Dynamic Supply Environment: Results From A Stated Preference Survey," Journal of Tourism, Sustainability and Well-being, Cinturs - Research Centre for Tourism, Sustainability and Well-being, University of Algarve, vol. 5(4), pages 400-424.
    3. Tobias Binz, 2020. "How do firm and market characteristics affect airports’ Beta risk?," Competition and Regulation in Network Industries, , vol. 21(3), pages 297-312, September.

    More about this item

    Keywords

    Valuation of attributes; Intercity transport; Random parameter logit;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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