IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v77y2015icp213-224.html
   My bibliography  Save this article

Impact evaluation of a mass transit fare change on demand and revenue utilizing smart card data

Author

Listed:
  • Wang, Zi-jia
  • Li, Xiao-hong
  • Chen, Feng

Abstract

Transit fares are an effective tool for demand management. Transit agencies can raise revenue or relieve overcrowding via fare increases, but they are always confronted with the possibility of heavy ridership losses. Therefore, the outcome of fare changes should be evaluated before implementation. In this work, a methodology was formulated based on elasticity and exhaustive transit card data, and a network approach was proposed to assess the influence of distance-based fare increases on ridership and revenue. The approach was applied to a fare change plan for Beijing Metro. The price elasticities of demand for Beijing Metro at various fare levels and trip distances were tabulated from a stated preference survey. Trip data recorded by an automatic fare collection system was used alongside the topology of the Beijing Metro system to calculate the shortest path lengths between all station pairs, the origin–destination matrix, and trip lengths. Finally, three fare increase alternatives (high, medium, and low) were evaluated in terms of their impact on ridership and revenue. The results demonstrated that smart card data have great potential with regard to fare change evaluation. According to smart card data for a large transit network, the statistical frequency of trip lengths is more highly concentrated than that of the shortest path length. Moreover, the majority of the total trips have a length of around 15km, and these are the most sensitive to fare increases. Specific attention should be paid to this characteristic when developing fare change plans to manage demand or raise revenue.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:transa:v:77:y:2015:i:c:p:213-224
    DOI: 10.1016/j.tra.2015.04.018
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856415001044
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tra.2015.04.018?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Latora, Vito & Marchiori, Massimo, 2002. "Is the Boston subway a small-world network?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 314(1), pages 109-113.
    4. Morency, Catherine & Trépanier, Martin & Agard, Bruno, 2007. "Measuring transit use variability with smart-card data," Transport Policy, Elsevier, vol. 14(3), pages 193-203, May.
    5. 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.
    6. Angeloudis, Panagiotis & Fisk, David, 2006. "Large subway systems as complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 553-558.
    7. Kremers, Hans & Nijkamp, Peter & Rietveld, Piet, 2002. "A meta-analysis of price elasticities of transport demand in a general equilibrium framework," Economic Modelling, Elsevier, vol. 19(3), pages 463-485, May.
    8. Holmgren, Johan, 2007. "Meta-analysis of public transport demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(10), pages 1021-1035, December.
    9. 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.
    10. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hiroaki Nishiuchi & Yasuyuki Kobayashi & Tomoyuki Todoroki & Tomoya Kawasaki, 2018. "Impact analysis of reductions in tram services in rural areas in Japan using smart card data," Public Transport, Springer, vol. 10(2), pages 291-309, August.
    2. Liu, Yan & Wang, Siqin & Xie, Bin, 2019. "Evaluating the effects of public transport fare policy change together with built and non-built environment features on ridership: The case in South East Queensland, Australia," Transport Policy, Elsevier, vol. 76(C), pages 78-89.
    3. Yang, Hongtai & Ping, An & Wei, Hongmin & Zhai, Guocong, 2023. "Unique in the metro system: The likelihood to re-identify a metro user with limited trajectory points," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).
    4. Filip Covic & Stefan Voß, 2019. "Interoperable smart card data management in public mass transit," Public Transport, Springer, vol. 11(3), pages 523-548, October.
    5. Verbich, David & El-Geneidy, Ahmed, 2017. "Public transit fare structure and social vulnerability in Montreal, Canada," Transportation Research Part A: Policy and Practice, Elsevier, vol. 96(C), pages 43-53.
    6. Xu, Shu-Xian & Liu, Tian-Liang & Huang, Hai-Jun & Liu, Ronghui, 2018. "Mode choice and railway subsidy in a congested monocentric city with endogenous population distribution," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 413-433.
    7. Kholodov, Yaroslav & Jenelius, Erik & Cats, Oded & van Oort, Niels & Mouter, Niek & Cebecauer, Matej & Vermeulen, Alex, 2021. "Public transport fare elasticities from smartcard data: Evidence from a natural experiment," Transport Policy, Elsevier, vol. 105(C), pages 35-43.
    8. Chen, Ruoyu & Zhou, Jiangping, 2022. "Fare adjustment’s impacts on travel patterns and farebox revenue: An empirical study based on longitudinal smartcard data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 164(C), pages 111-133.
    9. Anne Halvorsen & Haris N. Koutsopoulos & Zhenliang Ma & Jinhua Zhao, 2020. "Demand management of congested public transport systems: a conceptual framework and application using smart card data," Transportation, Springer, vol. 47(5), pages 2337-2365, October.
    10. 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.
    11. Jiechao Zhang & Xuedong Yan & Meiwu An & Li Sun, 2017. "The Impact of Beijing Subway’s New Fare Policy on Riders’ Attitude, Travel Pattern and Demand," Sustainability, MDPI, vol. 9(5), pages 1-21, April.
    12. Luis A. Guzman & Santiago Gomez & Carlos Alberto Moncada, 2020. "Short run fare elasticities for Bogotá’s BRT system: ridership responses to fare increases," Transportation, Springer, vol. 47(5), pages 2581-2599, October.
    13. Zhao, Pengjun & Zhang, Yixue, 2019. "The effects of metro fare increase on transport equity: New evidence from Beijing," Transport Policy, Elsevier, vol. 74(C), pages 73-83.
    14. Kuo, Yong-Hong & Leung, Janny M.Y. & Yan, Yimo, 2023. "Public transport for smart cities: Recent innovations and future challenges," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1001-1026.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Guzman, Luis A. & Beltran, Carlos & Bonilla, Jorge & Gomez Cardona, Santiago, 2021. "BRT fare elasticities from smartcard data: Spatial and time-of-the-day differences," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 335-348.
    3. Liu, Yan & Wang, Siqin & Xie, Bin, 2019. "Evaluating the effects of public transport fare policy change together with built and non-built environment features on ridership: The case in South East Queensland, Australia," Transport Policy, Elsevier, vol. 76(C), pages 78-89.
    4. Jiechao Zhang & Xuedong Yan & Meiwu An & Li Sun, 2017. "The Impact of Beijing Subway’s New Fare Policy on Riders’ Attitude, Travel Pattern and Demand," Sustainability, MDPI, vol. 9(5), pages 1-21, April.
    5. Souche, Stéphanie, 2010. "Measuring the structural determinants of urban travel demand," Transport Policy, Elsevier, vol. 17(3), pages 127-134, May.
    6. Albalate, Daniel & Bel, Germà, 2010. "What shapes local public transportation in Europe? Economics, mobility, institutions, and geography," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(5), pages 775-790, September.
    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. Yaman, Firat & Offiaeli, Kingsley, 2022. "Is the price elasticity of demand asymmetric? Evidence from public transport demand," Journal of Economic Behavior & Organization, Elsevier, vol. 203(C), pages 318-335.
    9. Luis A. Guzman & Santiago Gomez & Carlos Alberto Moncada, 2020. "Short run fare elasticities for Bogotá’s BRT system: ridership responses to fare increases," Transportation, Springer, vol. 47(5), pages 2581-2599, October.
    10. Thommen, Christoph & Hintermann, Beat, 2023. "Price versus Commitment: Managing the demand for off-peak train tickets in a field experiment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).
    11. Drevs, Florian & Tscheulin, Dieter K. & Lindenmeier, Jörg & Renner, Simone, 2014. "Crowding-in or crowding out: An empirical analysis on the effect of subsidies on individual willingness-to-pay for public transportation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 250-261.
    12. Redman, Lauren & Friman, Margareta & Gärling, Tommy & Hartig, Terry, 2013. "Quality attributes of public transport that attract car users: A research review," Transport Policy, Elsevier, vol. 25(C), pages 119-127.
    13. Souche, Stéphanie, 2009. "Un exemple d’estimation de la demande de transport urbain," Revue d'économie régionale et urbaine, Editions NecPlus, vol. 2009(04), pages 759-779, December.
    14. Li, Zheng & Hensher, David A. & Rose, John M., 2011. "Identifying sources of systematic variation in direct price elasticities from revealed preference studies of inter-city freight demand," Transport Policy, Elsevier, vol. 18(5), pages 727-734, September.
    15. Oded Cats & Yusak O. Susilo & Triin Reimal, 2017. "The prospects of fare-free public transport: evidence from Tallinn," Transportation, Springer, vol. 44(5), pages 1083-1104, September.
    16. Merkel, Axel & Holmgren, Johan, 2017. "Dredging the depths of knowledge: Efficiency analysis in the maritime port sector," Transport Policy, Elsevier, vol. 60(C), pages 63-74.
    17. Holmgren, Johan, 2007. "Meta-analysis of public transport demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(10), pages 1021-1035, December.
    18. Wardman, Mark & Toner, Jeremy & Fearnley, Nils & Flügel, Stefan & Killi, Marit, 2018. "Review and meta-analysis of inter-modal cross-elasticity evidence," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 662-681.
    19. Holmgren, Johan, 2010. "Putting our money to good use: Can we attract more passengers without increasing subsidies?," Research in Transportation Economics, Elsevier, vol. 29(1), pages 256-260.
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transa:v:77:y:2015:i:c:p:213-224. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.