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Inter-urban rail demand, elasticities and competition in Great Britain: Evidence from direct demand models

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  • Wardman, Mark

Abstract

The aim of this research was to extend direct demand models to analyse elasticity variation in more detail, and in particular to examine the interaction between rail and competing modes. Relatively little is known about the interaction between modes in the inter-urban travel market. We have obtained plausible, precise and reliable estimates of elasticity variation with regard to both the level a variable takes and with respect to the degree of competition from car and coach. These relationships have been freely estimated rather than imposed and would in many instances imply appreciable differences in demand forecasts in comparison with models which do not include competitive effects. As a result of this research, British Rail has amended its forecasting procedures to include competitive effects. We recommend the more widespread use of direct demand models to examine elasticity variation.

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  • Wardman, Mark, 1997. "Inter-urban rail demand, elasticities and competition in Great Britain: Evidence from direct demand models," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 33(1), pages 15-28, March.
    • Handle: RePEc:eee:transe:v:33:y:1997:i:1:p:15-28
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    Cited by:

    1. W. Lythgoe & M. Wardman, 2004. "Modelling passenger demand for parkway rail stations," Transportation, Springer, vol. 31(2), pages 125-151, May.
    2. X. D'Haultfoeuille & P. Fevrier & L. Wilner, 2012. "Demand Estimation in the Presence of Revenue Management," Documents de Travail de l'Insee - INSEE Working Papers g2012-13, Institut National de la Statistique et des Etudes Economiques.
    3. Ahern, Aoife A. & Tapley, Nigel, 2008. "The use of stated preference techniques to model modal choices on interurban trips in Ireland," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(1), pages 15-27, January.
    4. W.F. Lythgoe & M. Wardman, 2002. "Demand for rail travel to and from airports," Transportation, Springer, vol. 29(2), pages 125-143, May.
    5. Wardman, Mark & Lythgoe, William & Whelan, Gerard, 2007. "Rail Passenger Demand Forecasting: Cross-Sectional Models Revisited," Research in Transportation Economics, Elsevier, vol. 20(1), pages 119-152, January.
    6. Robenek, Tomáš & Azadeh, Shadi Sharif & Maknoon, Yousef & de Lapparent, Matthieu & Bierlaire, Michel, 2018. "Train timetable design under elastic passenger demand," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 19-38.
    7. Rian Mehta & Stephen Rice & Deborah Carstens & Ismael Cremer & Korhan Oyman, 2015. "A Brief Intermodal Rail Network (IRN) Scale: Establishing Validity and Reliability," Journal of Sustainable Development, Canadian Center of Science and Education, vol. 8(6), pages 243-243, June.
    8. Jinkyung Choi & Yong Lee & Taewan Kim & Keemin Sohn, 2012. "An analysis of Metro ridership at the station-to-station level in Seoul," Transportation, Springer, vol. 39(3), pages 705-722, May.
    9. Meng, Lingyun & Zhou, Xuesong, 2019. "An integrated train service plan optimization model with variable demand: A team-based scheduling approach with dual cost information in a layered network," Transportation Research Part B: Methodological, Elsevier, vol. 125(C), pages 1-28.
    10. Hu, Xinlei & Wang, Xiaokun (Cara) & Ni, Linglin & Shi, Feng, 2022. "The impact of intercity economic complementarity on HSR volume in the context of megalopolization," Journal of Transport Geography, Elsevier, vol. 98(C).

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