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The impact of fare complexity on rail demand

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  • Anciaes, Paulo
  • Metcalfe, Paul
  • Heywood, Chris
  • Sheldon, Rob

Abstract

The current rail fare structure in the UK is widely considered to be complex. It offers flexibility by including many different types of tickets but it can also cause confusion, which may lead some to a negative view towards rail travel and thereby potentially inhibit demand, in comparison to a simpler fare regime. This study used an innovative stated preference survey to quantify the demand effects of fare complexity, focusing on Advance tickets (those that are restricted to a particular train service). The choice experiment was designed to mirror very closely the actual booking experience when buying tickets online, in all its complexity. Participants could choose among up to 531 different ticket type combinations for the outward and return legs of a trip and from up to 25 possible train services for each leg. The key design attribute was complexity, defined as the range of different Advance tickets on offer. The survey was applied to a sample of 1027 users and 179 non-users of the rail network on the London-Leeds route. The modelling of the choices with a nested mixed logit model suggested that, all else equal, reducing complexity by removing Advance tickets would lead to a substantial reduction of demand (11 to 45%, depending on route segment). Equalizing the price of Advance tickets for all train services was predicted to cause a smaller reduction (3–6%). By contrast, increasing complexity by adding new Flexible Advance tickets (valid on the services immediately before or after the chosen service) would increase demand by 4–15%. These findings run counter to the hypothesis that simplifying the fare structure would lead to increases in demand for rail travel.

Suggested Citation

  • Anciaes, Paulo & Metcalfe, Paul & Heywood, Chris & Sheldon, Rob, 2019. "The impact of fare complexity on rail demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 120(C), pages 224-238.
  • Handle: RePEc:eee:transa:v:120:y:2019:i:c:p:224-238
    DOI: 10.1016/j.tra.2018.12.020
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    1. Julia Bird & Yue Li & Hossain Zillur Rahman & Martin Rama & Anthony J. Venables, 2018. "Toward Great Dhaka," World Bank Publications - Books, The World Bank Group, number 29925, December.
    2. John M. Rose & Michiel C.J. Bliemer, 2014. "Stated choice experimental design theory: the who, the what and the why," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 7, pages 152-177, Edward Elgar Publishing.
    3. Paha, Johannes & Rompf, Dirk & Warnecke, Christiane, 2013. "Customer choice patterns in passenger rail competition," Transportation Research Part A: Policy and Practice, Elsevier, vol. 50(C), pages 209-227.
    4. de Jong, Gerard & Daly, Andrew & Pieters, Marits & van der Hoorn, Toon, 2007. "The logsum as an evaluation measure: Review of the literature and new results," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(9), pages 874-889, November.
    5. Swait, Joffre & Adamowicz, Wiktor, 2001. "The Influence of Task Complexity on Consumer Choice: A Latent Class Model of Decision Strategy Switching," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 28(1), pages 135-148, June.
    6. Abrate, Graziano & Piacenza, Massimiliano & Vannoni, Davide, 2009. "The impact of Integrated Tariff Systems on public transport demand: Evidence from Italy," Regional Science and Urban Economics, Elsevier, vol. 39(2), pages 120-127, March.
    7. Whelan, Gerard & Batley, Richard & Shires, Jeremy & Wardman, Mark, 2008. "Optimal fares regulation for Britain's railways," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 44(5), pages 807-819, September.
    8. Luís Cabral, 2019. "Towards a theory of platform dynamics," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 28(1), pages 60-72, January.
    9. Preston, John, 2008. "Competition in transit markets," Research in Transportation Economics, Elsevier, vol. 23(1), pages 75-84, January.
    10. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    11. World Bank Group, 2018. "Toward Water Security for Palestinians," World Bank Publications - Reports 30316, The World Bank Group.
    12. Daniel Ellsberg, 1961. "Risk, Ambiguity, and the Savage Axioms," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 75(4), pages 643-669.
    13. Garbarino, Ellen C & Edell, Julie A, 1997. "Cognitive Effort, Affect, and Choice," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 24(2), pages 147-158, September.
    14. José I. Castillo-Manzano & Antonio Sánchez-Braza, 2011. "An Evaluation of the Establishment of a Taxi Flat Rate from City to Airport: The Case of Seville," Urban Studies, Urban Studies Journal Limited, vol. 48(9), pages 1909-1924, July.
    15. World Bank Group, 2018. "Towards Equal? Women in Central America," World Bank Publications - Reports 30398, The World Bank Group.
    16. Sharaby, Nir & Shiftan, Yoram, 2012. "The impact of fare integration on travel behavior and transit ridership," Transport Policy, Elsevier, vol. 21(C), pages 63-70.
    17. Ariely, Dan, 2000. "Controlling the Information Flow: Effects on Consumers' Decision Making and Preferences," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 27(2), pages 233-248, September.
    18. World Bank Group & People's Bank of China, 2018. "Toward Universal Financial Inclusion in China," World Bank Publications - Reports 29336, The World Bank Group.
    19. Mark Wardman, 2014. "Price Elasticities of Surface Travel Demand A Meta-analysis of UK Evidence," Journal of Transport Economics and Policy, University of Bath, vol. 48(3), pages 367-384, September.
    20. Bonsall, Peter & Shires, Jeremy & Maule, John & Matthews, Bryan & Beale, Jo, 2007. "Responses to complex pricing signals: Theory, evidence and implications for road pricing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(7), pages 672-683, August.
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