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Understanding the determinants of travel mode choice of residents and its carbon mitigation potential

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  • Yang, Yuan
  • Wang, Can
  • Liu, Wenling
  • Zhou, Peng

Abstract

Effective low carbon transport policy-making needs to first understand what are the factors influencing residents’ modal choice and how it can be intervened. This study uses a discrete choice model to analyse the factors influencing residents’ mode choice in Beijing. A questionnaire survey was conducted in 2015, with sample data containing 865 respondents and 1704 trips collected. The results suggest that residents’ mode choice is closely related to their characteristics. Moreover, our study has linked residents’ mode choice with travel carbon emissions and estimated the emissions reduction potential of those policy measures aiming to improve public transport. For commuting and education trips, public transport improvements can reduce carbon emissions by 12.3~16.6% on average, but for other trip purposes, the reduction is only 2.9~6.8%. As commuting and education trips account for the largest proportion of urban residents’ daily travels, it suggests that policy should primarily focus on the improvement of public transport and its particular support for major commuting routes.

Suggested Citation

  • Yang, Yuan & Wang, Can & Liu, Wenling & Zhou, Peng, 2018. "Understanding the determinants of travel mode choice of residents and its carbon mitigation potential," Energy Policy, Elsevier, vol. 115(C), pages 486-493.
  • Handle: RePEc:eee:enepol:v:115:y:2018:i:c:p:486-493
    DOI: 10.1016/j.enpol.2018.01.033
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    References listed on IDEAS

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    1. Wang, Lanlan & Xu, Jintao & Qin, Ping, 2014. "Will a driving restriction policy reduce car trips?—The case study of Beijing, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 279-290.
    2. Brand, Christian & Boardman, Brenda, 2008. "Taming of the few--The unequal distribution of greenhouse gas emissions from personal travel in the UK," Energy Policy, Elsevier, vol. 36(1), pages 224-238, January.
    3. Jean-Pierre Nicolas & Damien David, 2009. "Passenger transport and CO2 emissions: What does the French transport survey tell us?," Post-Print halshs-00372439, HAL.
    4. Can Wang & Yuan Yang & Junjie Zhang, 2015. "China's sectoral strategies in energy conservation and carbon mitigation," Climate Policy, Taylor & Francis Journals, vol. 15(sup1), pages 60-80, December.
    5. Vredin Johansson, Maria & Heldt, Tobias & Johansson, Per, 2006. "The effects of attitudes and personality traits on mode choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(6), pages 507-525, July.
    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. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, April.
    8. Gu, Yizhen & Deakin, Elizabeth & Long, Ying, 2017. "The effects of driving restrictions on travel behavior evidence from Beijing," Journal of Urban Economics, Elsevier, vol. 102(C), pages 106-122.
    9. Hoen, Anco & Koetse, Mark J., 2014. "A choice experiment on alternative fuel vehicle preferences of private car owners in the Netherlands," Transportation Research Part A: Policy and Practice, Elsevier, vol. 61(C), pages 199-215.
    10. Sungyop Kim & Gudmundur Ulfarsson, 2008. "Curbing automobile use for sustainable transportation: analysis of mode choice on short home-based trips," Transportation, Springer, vol. 35(6), pages 723-737, November.
    11. Watkins, Kari Edison & Ferris, Brian & Borning, Alan & Rutherford, G. Scott & Layton, David, 2011. "Where Is My Bus? Impact of mobile real-time information on the perceived and actual wait time of transit riders," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(8), pages 839-848, October.
    12. Yang, Yuan & Wang, Can & Liu, Wenling & Zhou, Peng, 2017. "Microsimulation of low carbon urban transport policies in Beijing," Energy Policy, Elsevier, vol. 107(C), pages 561-572.
    13. Salon, Deborah, 2009. "Neighborhoods, cars, and commuting in New York City: A discrete choice approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(2), pages 180-196, February.
    14. O'Fallon, Carolyn & Sullivan, Charles & Hensher, David A, 2004. "Constraints affecting mode choices by morning car commuters," Transport Policy, Elsevier, vol. 11(1), pages 17-29, January.
    15. Hensher, David A. & Rose, John M., 2007. "Development of commuter and non-commuter mode choice models for the assessment of new public transport infrastructure projects: A case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(5), pages 428-443, June.
    16. Brand, Christian & Goodman, Anna & Rutter, Harry & Song, Yena & Ogilvie, David, 2013. "Associations of individual, household and environmental characteristics with carbon dioxide emissions from motorised passenger travel," Applied Energy, Elsevier, vol. 104(C), pages 158-169.
    17. Habibian, Meeghat & Kermanshah, Mohammad, 2013. "Coping with congestion: Understanding the role of simultaneous transportation demand management policies on commuters," Transport Policy, Elsevier, vol. 30(C), pages 229-237.
    18. Yang, Jun & Liu, Ying & Qin, Ping & Liu, Antung A., 2014. "A review of Beijing׳s vehicle registration lottery: Short-term effects on vehicle growth and fuel consumption," Energy Policy, Elsevier, vol. 75(C), pages 157-166.
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    Cited by:

    1. Hao, Jingjing & Zhang, Ling & Ji, Xiaofeng & Tang, Jinjun, 2020. "Modeling and analyzing of family intention for the customized student routes: A case study in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    2. Enhui Chen & Zhirui Ye & Hui Bi, 2019. "Incorporating Smart Card Data in Spatio-Temporal Analysis of Metro Travel Distances," Sustainability, MDPI, Open Access Journal, vol. 11(24), pages 1-22, December.
    3. Rui Zhao & Linchuan Yang & Xinrong Liang & Yuanyuan Guo & Yi Lu & Yixuan Zhang & Xinyun Ren, 2019. "Last-Mile Travel Mode Choice: Data-Mining Hybrid with Multiple Attribute Decision Making," Sustainability, MDPI, Open Access Journal, vol. 11(23), pages 1-15, November.
    4. Jing Li & Yongbo Lv & Jihui Ma & Yuan Ren, 2019. "Factor Analysis of Customized Bus Attraction to Commuters with Different Travel Modes," Sustainability, MDPI, Open Access Journal, vol. 11(24), pages 1-13, December.
    5. Fanying Zheng & Fu Gu & Wujie Zhang & Jianfeng Guo, 2019. "Is Bicycle Sharing an Environmental Practice? Evidence from a Life Cycle Assessment Based on Behavioral Surveys," Sustainability, MDPI, Open Access Journal, vol. 11(6), pages 1-25, March.

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