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

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  • 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
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    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.
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