IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v9y2017i5p689-d96956.html
   My bibliography  Save this article

The Impact of Beijing Subway’s New Fare Policy on Riders’ Attitude, Travel Pattern and Demand

Author

Listed:
  • Jiechao Zhang

    (MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China)

  • Xuedong Yan

    (MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China)

  • Meiwu An

    (Saint Louis County Department of Transportation and Public Works, 1050 N. Lindbergh, St. Louis, MO 63132, USA)

  • Li Sun

    (School of Architecture and Urban Planning, Beijing University of Civil Engineering and Achitecture, Beijing 100044, China)

Abstract

On 28 December 2014, the Beijing subway’s fare policy was changed from “Two Yuan” per trip to the era of Logging Ticket Price, charging users by travel mileage. This paper aims at investigating the effects of Beijing subway’s new fare policy on the riders’ attitude, travel pattern and demand. A survey analysis was conducted to identify the effects of the new fare policy for Beijing subway on riders’ satisfaction degree and travel pattern associated with the potential influencing factors using Hierarchical Tree-based Regression (HTBR) models. The model results show that income, travel distance and month of travel have significant impacts on the subway riders’ satisfaction degree, while trip purpose, car ownership and travel frequency significantly influence the riders’ stated travel pattern. Overall, the degree of satisfaction could not be effectively recovered within five months after the new fare policy, but the negative public attitude did not depress the subway demand continuously. Based on the further time sequence analyses of the passenger flow volume data for two years, it is concluded that the new policy made the ridership decrease sharply in the first month but gradually came back to the previous level four months later, and then the passenger flow volume kept steady again. The findings in this study indicate that the new fare policy realized the purpose of lowering the government’s financial pressure but did not reduce the subway ridership in a long term perspective.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:5:p:689-:d:96956
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/9/5/689/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/9/5/689/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Delbosc, Alexa & Currie, Graham, 2011. "Using Lorenz curves to assess public transport equity," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1252-1259.
    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. Chang, Zheng, 2014. "Financing new metros—The Beijing metro financing sustainability study," Transport Policy, Elsevier, vol. 32(C), pages 148-155.
    4. Zhang, Zheng & Fujii, Hidemichi & Managi, Shunsuke, 2014. "How does Commuting Behavior Change Due to Incentives? An Empirical Study of the Beijing Subway System," MPRA Paper 54691, University Library of Munich, Germany.
    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. Shen, Weiwei & Xiao, Weizhou & Wang, Xin, 2016. "Passenger satisfaction evaluation model for Urban rail transit: A structural equation modeling based on partial least squares," Transport Policy, Elsevier, vol. 46(C), pages 20-31.
    7. Nuworsoo, Cornelius & Golub, Aaron & Deakin, Elizabeth, 2009. "Analyzing equity impacts of transit fare changes: Case study of Alameda-Contra Costa Transit, California," Evaluation and Program Planning, Elsevier, vol. 32(4), pages 360-368, November.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. Tyrinopoulos, Yannis & Antoniou, Constantinos, 2008. "Public transit user satisfaction: Variability and policy implications," Transport Policy, Elsevier, vol. 15(4), pages 260-272, July.
    13. Chen, Ching-Fu, 2008. "Investigating structural relationships between service quality, perceived value, satisfaction, and behavioral intentions for air passengers: Evidence from Taiwan," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(4), pages 709-717, May.
    14. 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.
    15. William Jen & Kai-Chieh Hu, 2003. "Application of perceived value model to identify factors affecting passengers' repurchase intentions on city bus: A case of the Taipei metropolitan area," Transportation, Springer, vol. 30(3), pages 307-327, August.
    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. Hao Li & Xiaohui Yang & Xiao Zhang & Yuyan Liu & Kebin Zhang, 2018. "Estimation of Rural Households’ Willingness to Accept Two PES Programs and Their Service Valuation in the Miyun Reservoir Catchment, China," Sustainability, MDPI, vol. 10(1), pages 1-19, January.
    2. Jeongwoo Lee & Marlon Boarnet & Douglas Houston & Hilary Nixon & Steven Spears, 2017. "Changes in Service and Associated Ridership Impacts near a New Light Rail Transit Line," Sustainability, MDPI, vol. 9(10), pages 1-27, October.
    3. 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.
    4. 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.
    5. Hainan Huang & Yi Lin & Jiancheng Weng & Jian Rong & Xiaoming Liu, 2018. "Identification of Inelastic Subway Trips Based on Weekly Station Sequence Data: An Example from the Beijing Subway," Sustainability, MDPI, vol. 10(12), pages 1-15, December.

    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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Juan de Oña & Rocio de Oña, 2015. "Quality of Service in Public Transport Based on Customer Satisfaction Surveys: A Review and Assessment of Methodological Approaches," Transportation Science, INFORMS, vol. 49(3), pages 605-622, August.
    8. 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.
    9. Zhang, Chunqin & Juan, Zhicai & Lu, Weite & Xiao, Guangnian, 2016. "Do the organizational forms affect passenger satisfaction? Evidence from Chinese public transport service," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 129-148.
    10. Xiaoshu Cao & Huiling Chen & Feiwen Liang & Wulin Wang, 2018. "Measurement and Spatial Differentiation Characteristics of Transit Equity: A Case Study of Guangzhou, China," Sustainability, MDPI, vol. 10(4), pages 1-17, April.
    11. Mandhani, Jyoti & Nayak, Jogendra Kumar & Parida, Manoranjan, 2020. "Interrelationships among service quality factors of Metro Rail Transit System: An integrated Bayesian networks and PLS-SEM approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 320-336.
    12. Ni, Anning & Zhang, Chunqin & Hu, Yuting & Lu, Weite & Li, Hongwei, 2020. "Influence mechanism of the corporate image on passenger satisfaction with public transport in China," Transport Policy, Elsevier, vol. 94(C), pages 54-65.
    13. Puteri Paramita & Zuduo Zheng & Md Mazharul Haque & Simon Washington & Paul Hyland, 2018. "User satisfaction with train fares: A comparative analysis in five Australian cities," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-26, June.
    14. Chee, Pei Nen Esther & Susilo, Yusak O. & Wong, Yiik Diew, 2020. "Determinants of intention-to-use first-/last-mile automated bus service," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 350-375.
    15. Hörcher, Daniel & Tirachini, Alejandro, 2021. "A review of public transport economics," Economics of Transportation, Elsevier, vol. 25(C).
    16. Matas, Anna & Raymond, Josep-Lluis & Ruiz, Adriana, 2020. "Economic and distributional effects of different fare schemes: Evidence from the Metropolitan Region of Barcelona," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 1-14.
    17. Anjali R. Virkar & Prita D. Mallya, 2018. "A Review of Dimensions of Tourism Transport Affecting Tourist Satisfaction," Indian Journal of Commerce and Management Studies, Educational Research Multimedia & Publications,India, vol. 9(1), pages 72-80, January.
    18. 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.
    19. Sun, Fan & Jin, Minjie & Zhang, Tao & Huang, Wencheng, 2022. "Satisfaction differences in bus traveling among low-income individuals before and after COVID-19," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 311-332.
    20. Fu, Xuemei & Juan, Zhicai, 2017. "Exploring the psychosocial factors associated with public transportation usage and examining the “gendered” difference," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 70-82.

    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:gam:jsusta:v:9:y:2017:i:5:p:689-:d:96956. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.