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How does Commuting Behavior Change Due to Incentives? An Empirical Study of the Beijing Subway System

Author

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  • Zhang, Zheng
  • Fujii, Hidemichi
  • Managi, Shunsuke

Abstract

This study examines the impact of incentives on commuters’ travel behavior based upon a questionnaire survey conducted on the Beijing Subway System. Overall, we find that giving incentives to commuters, especially fast food restaurant-related services and reduced ticket fares, has a positive influence on morning rush-hour avoidance. Furthermore, using interaction analysis, we discover that the flexible work time schedule has an impact on commuters’ behavior and the efficiency of the subway system. Finally, we recommend two possible policies to maximize the utility of the subway system and to reduce congestion at the peak of morning service: 1) a set of incentives including free wireless internet connection service with a coupon for breakfast and a discount on ticket fares before the morning peak, and 2) the introduction of a flexible work time schedule.

Suggested Citation

  • 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.
    • Handle: RePEc:pra:mprapa:54691
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    2. Menegaki, Angeliki, N. & Olsen, Søren Bøye & Tsagarakis, Konstantinos P., 2016. "Towards a common standard – A reporting checklist for web-based stated preference valuation surveys and a critique for mode surveys," Journal of choice modelling, Elsevier, vol. 18(C), pages 18-50.
    3. Palacios, Saúl, 2021. "Desplazamientos y autoempleo en Francia: diferencias por género [Commuting y self-employment in France: gender differences]," MPRA Paper 106555, University Library of Munich, Germany.
    4. 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.
    5. Haiyan Zhu & Hongzhi Guan & Yan Han & Wanying Li, 2019. "A Study of Tourists’ Holiday Rush-Hour Avoidance Travel Behavior Considering Psychographic Segmentation," Sustainability, MDPI, vol. 11(13), pages 1-20, July.
    6. Yen, Barbara T.H. & Mulley, Corinne & Meza, Gerardo, 2023. "Exploring the attitudes and perceptions influencing user participation in gamification schemes for TDM," Research in Transportation Economics, Elsevier, vol. 99(C).
    7. Li, Changle & Ma, Jiao & Luan, Tom H. & Zhou, Xun & Xiong, Lei, 2018. "An incentive-based optimizing strategy of service frequency for an urban rail transit system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 106-122.
    8. Shoval, Noam & Kahani, Alon & De Cantis, Stefano & Ferrante, Mauro, 2020. "Impact of incentives on tourist activity in space-time," Annals of Tourism Research, Elsevier, vol. 80(C).
    9. Su, Duan & Wang, Yacan & Yang, Nan & Wang, Xianghong, 2020. "Promoting considerate parking behavior in dockless bike-sharing: An experimental study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 153-165.
    10. Ghimire, Ramesh & Lancelin, Colby, 2019. "The relationship between financial incentives provided by employers and commuters' decision to use transit: Results from the Atlanta Regional Household Travel Survey," Transport Policy, Elsevier, vol. 74(C), pages 103-113.
    11. Anupriya, & Graham, Daniel J. & Hörcher, Daniel & Anderson, Richard J. & Bansal, Prateek, 2020. "Quantifying the ex-post causal impact of differential pricing on commuter trip scheduling in Hong Kong," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 16-34.
    12. Wang, Yacan & Geng, Kexin & May, Anthony D. & Zhou, Huiyu, 2022. "The impact of traffic demand management policy mix on commuter travel choices," Transport Policy, Elsevier, vol. 117(C), pages 74-87.
    13. Wang, Bing & Li, Shuai & Wang, Qi & Lin, Zhenhong, 2020. "Understanding travelers’ mobility decisions in response to customer incentives," Transport Policy, Elsevier, vol. 97(C), pages 113-120.
    14. An, Qinhe & Fu, Xiao & Huang, Di & Cheng, Qixiu & Liu, Zhiyuan, 2020. "Analysis of adding-runs strategy for peak-hour regular bus services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    15. 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.
    16. Haiyan Zhu & Hongzhi Guan & Yan Han & Wanying Li, 2020. "Can Road Toll Convince Car Travelers to Adjust Their Departure Times? Accounting for the Effect of Choice Behavior under Long and Short Holidays," Sustainability, MDPI, vol. 12(24), pages 1-29, December.
    17. Shubhendra Singh Parihar & Puneet Rai & Masood Siddiqui, 2021. "A Study of Commuter’s Shift Behaviour Towards New Age Convenient Transport Services," FIIB Business Review, , vol. 10(2), pages 172-180, June.
    18. Wang, Yu & Wang, Yacan & Ettema, Dick & Mao, Zidan & Charlton, Samuel G. & Zhou, Huiyu, 2020. "Commuter value perceptions in peak avoidance behavior: An empirical study in the Beijing subway system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 70-84.
    19. Sun, Jian & Wu, Jiyan & Xiao, Feng & Tian, Ye & Xu, Xiangdong, 2020. "Managing bottleneck congestion with incentives," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 143-166.
    20. Zhiyi Gan & Jinhua Gan & Zhiqing E. Zhou & Hanying Tang, 2024. "Organizational Benefits of Commuting Support: The Impact of Flexible Working Hours on Employees’ OCB through Commuting Control," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 174(1), pages 75-89, August.
    21. Ghafelebashi, Ali & Razaviyayn, Meisam & Dessouky, Maged, 2021. "Congestion Reduction via Personalized Incentives," Institute of Transportation Studies, Working Paper Series qt5b82168n, Institute of Transportation Studies, UC Davis.

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    More about this item

    Keywords

    Behavior; Incentives; Morning Peak; Commute; Beijing Subway System; Flexibility;
    All these keywords.

    JEL classification:

    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General
    • R48 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government Pricing and Policy

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