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Passengers’ response to transit fare change: an ex post appraisal using smart card data

Author

Listed:
  • Zi-jia Wang

    (Beijing Jiaotong University)

  • Feng Chen

    (Beijing Jiaotong University
    Beijing Engineering and Technology Research Center of Rail Transit Line Safety and Disaster Prevention)

  • Bo Wang

    (Beijing Transportation Information Center)

  • Jian-ling Huang

    (Beijing Transportation Information Center)

Abstract

Fare change is an effective tool for public transit demand management. An automatic fare collection system not only allows the implementation of complex fare policies, but also provides abundant data for impact analysis of fare change. This study proposes an assessment approach for analyzing the influence when substituting a flat-fare policy with a distance-based fare policy, using smart card data. The method can be used to analyze the impact of fare change on demand, riding distances, as well as price elasticity of demand at different time and distance intervals. Taking the fare change of Beijing Metro implemented in 2014 as a case study, we analyze the change of network demand at various levels, riding distances, and demand elasticity of different distances on weekdays and weekends, using the method established and the smart card data a week before and after the fare change. The policy implication of the fare change was also addressed. The results suggest that the fare change had a significant impact on overall demand, but not so much on riding distances. The greatest sensitivity to fare change is shown by weekend passengers, followed by passengers in the evening weekday peak time, while the morning weekday peak time passengers show little sensitivity. A great variety of passengers’ responses to fare change exists at station level because stations serve different types of land usage or generate trips with distinct purposes at different times. Rising fares can greatly increase revenue, and can shift trips to cycling and walking to a certain extent, but not so much as to mitigate overcrowding at morning peak times. The results are compared with those of the ex ante evaluation that used a stated preference survey, and the comparison illustrates that the price elasticity of demand extracted from the stated preference survey significantly exaggerates passengers’ responses to fare increase.

Suggested Citation

  • Zi-jia Wang & Feng Chen & Bo Wang & Jian-ling Huang, 2018. "Passengers’ response to transit fare change: an ex post appraisal using smart card data," Transportation, Springer, vol. 45(5), pages 1559-1578, September.
  • Handle: RePEc:kap:transp:v:45:y:2018:i:5:d:10.1007_s11116-017-9775-1
    DOI: 10.1007/s11116-017-9775-1
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    References listed on IDEAS

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    1. Joyce M. Dargay & Mark Hanly, 2002. "The Demand for Local Bus Services in England," Journal of Transport Economics and Policy, University of Bath, vol. 36(1), pages 73-91, January.
    2. Farber, Steven & Bartholomew, Keith & Li, Xiao & Páez, Antonio & Nurul Habib, Khandker M., 2014. "Assessing social equity in distance based transit fares using a model of travel behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 291-303.
    3. de Grange, Louis & González, Felipe & Muñoz, Juan Carlos & Troncoso, Rodrigo, 2013. "Aggregate estimation of the price elasticity of demand for public transport in integrated fare systems: The case of Transantiago," Transport Policy, Elsevier, vol. 29(C), pages 178-185.
    4. Paulley, Neil & Balcombe, Richard & Mackett, Roger & Titheridge, Helena & Preston, John & Wardman, Mark & Shires, Jeremy & White, Peter, 2006. "The demand for public transport: The effects of fares, quality of service, income and car ownership," Transport Policy, Elsevier, vol. 13(4), pages 295-306, July.
    5. 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.
    6. Hensher, David A., 2008. "Assessing systematic sources of variation in public transport elasticities: Some comparative warnings," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(7), pages 1031-1042, August.
    7. 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.
    8. Bresson, Georges & Dargay, Joyce & Madre, Jean-Loup & Pirotte, Alain, 2003. "The main determinants of the demand for public transport: a comparative analysis of England and France using shrinkage estimators," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(7), pages 605-627, August.
    9. Wang, Zi-jia & Li, Xiao-hong & Chen, Feng, 2015. "Impact evaluation of a mass transit fare change on demand and revenue utilizing smart card data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 213-224.
    10. Gkritza, Konstantina & Karlaftis, Matthew G. & Mannering, Fred L., 2011. "Estimating multimodal transit ridership with a varying fare structure," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(2), pages 148-160, February.
    11. Holmgren, Johan, 2007. "Meta-analysis of public transport demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(10), pages 1021-1035, December.
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