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The impact of traffic demand management policy mix on commuter travel choices

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  • Wang, Yacan
  • Geng, Kexin
  • May, Anthony D.
  • Zhou, Huiyu

Abstract

The experience of traffic demand management policy in many cities shows that a single policy instrument has limited effect and may have side effects on other contemporaneous policies; therefore, formulating a policy mix is a more effective way to solve urban traffic problems. However, the bulk of previous literature has focused on the impact of single policy instruments, neglecting the growing interest in understanding the role played by the different combinations of policy instruments. Therefore, using a 6*3 matrix typology, this paper provides an empirical impact analysis of selected policy mixes in inducing sustainable travel behavior and reducing private car use. This study also designs orthogonal experiments and adopts stated preference questionnaires to analyze the main effects and full combined effects of packages of policy instruments through multinomial logit models. The results show that the effect of a policy mix is often not better than that of a single policy and demonstrate the need for careful systemic design. A balanced-designed policy mix can facilitate public transportation and help reduce traffic gridlock using a balanced combination of push, pull and systemic TDM policy instruments.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:trapol:v:117:y:2022:i:c:p:74-87
    DOI: 10.1016/j.tranpol.2022.01.002
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    as
    1. Braun, Lindsay M. & Rodriguez, Daniel A. & Cole-Hunter, Tom & Ambros, Albert & Donaire-Gonzalez, David & Jerrett, Michael & Mendez, Michelle A. & Nieuwenhuijsen, Mark J. & de Nazelle, Audrey, 2016. "Short-term planning and policy interventions to promote cycling in urban centers: Findings from a commute mode choice analysis in Barcelona, Spain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 89(C), pages 164-183.
    2. Wang, Ning & Tang, Linhao & Pan, Huizhong, 2017. "Effectiveness of policy incentives on electric vehicle acceptance in China: A discrete choice analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 105(C), pages 210-218.
    3. Agarwal, Sumit & Diao, Mi & Keppo, Jussi & Sing, Tien Foo, 2020. "Preferences of public transit commuters: Evidence from smart card data in Singapore," Journal of Urban Economics, Elsevier, vol. 120(C).
    4. Hounsell, Nick & Shrestha, Birendra & Piao, Jinan, 2011. "Enhancing Park and Ride with access control: A case study of Southampton," Transport Policy, Elsevier, vol. 18(1), pages 194-203, January.
    5. 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.
    6. Börjesson, Maria & Kristoffersson, Ida, 2018. "The Swedish congestion charges: Ten years on," Transportation Research Part A: Policy and Practice, Elsevier, vol. 107(C), pages 35-51.
    7. 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.
    8. Rotaris, Lucia & Danielis, Romeo, 2015. "Commuting to college: The effectiveness and social efficiency of transportation demand management policies," Transport Policy, Elsevier, vol. 44(C), pages 158-168.
    9. Chinh Ho & Corinne Mulley & Chi-Hong Tsai & Stephen Ison & Sue Wiblin, 2017. "Area-wide travel plans—targeting strategies for greater participation in green travel initiatives: a case study of Rouse Hill Town Centre, NSW Australia," Transportation, Springer, vol. 44(2), pages 325-352, March.
    10. Laura Eboli & Gabriella Mazzulla, 2008. "A Stated Preference Experiment for Measuring Service Quality in Public Transport," Transportation Planning and Technology, Taylor & Francis Journals, vol. 31(5), pages 509-523, February.
    11. May, Anthony D. & Kelly, Charlotte & Shepherd, Simon, 2006. "The principles of integration in urban transport strategies," Transport Policy, Elsevier, vol. 13(4), pages 319-327, July.
    12. Paul Pfaffenbichler & Günter Emberger & Simon Shepherd, 2008. "The Integrated Dynamic Land Use and Transport Model MARS," Networks and Spatial Economics, Springer, vol. 8(2), pages 183-200, September.
    13. Zhang, Linling & Long, Ruyin & Chen, Hong, 2019. "Do car restriction policies effectively promote the development of public transport?," World Development, Elsevier, vol. 119(C), pages 100-110.
    14. May, Anthony D. & Kelly, Charlotte & Shepherd, Simon & Jopson, Ann, 2012. "An option generation tool for potential urban transport policy packages," Transport Policy, Elsevier, vol. 20(C), pages 162-173.
    15. 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.
    16. Junyi Shen, 2009. "Latent class model or mixed logit model? A comparison by transport mode choice data," Applied Economics, Taylor & Francis Journals, vol. 41(22), pages 2915-2924.
    17. Thorhauge, Mikkel & Cherchi, Elisabetta & Rich, Jeppe, 2016. "How flexible is flexible? Accounting for the effect of rescheduling possibilities in choice of departure time for work trips," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 177-193.
    18. Deka, Devajyoti & Carnegie, Jon, 2021. "Predicting transit mode choice of New Jersey workers commuting to New York City from a stated preference survey," Journal of Transport Geography, Elsevier, vol. 91(C).
    19. Cao, Xinyu & Mokhtarian, Patricia L., 2005. "How do individuals adapt their personal travel? Objective and subjective influences on the consideration of travel-related strategies for San Francisco Bay Area commuters," Transport Policy, Elsevier, vol. 12(4), pages 291-302, July.
    20. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    21. Cools, Mario & Brijs, Kris & Tormans, Hans & De Laender, Jessie & Wets, Geert, 2012. "Optimizing the implementation of policy measures through social acceptance segmentation," Transport Policy, Elsevier, vol. 22(C), pages 80-87.
    22. Hooi Ling Khoo & Ghim Ping Ong & Wooi Chen Khoo, 2012. "Short-term impact analysis of fuel price policy change on travel demand in Malaysian cities," Transportation Planning and Technology, Taylor & Francis Journals, vol. 35(7), pages 715-736, May.
    23. Jean-Michel Cusset, 2004. "Transport-Environment Issues and Countermeasures in Various Metropolises: Hanoï," Post-Print halshs-00080640, HAL.
    24. Bueno, Paola Carolina & Gomez, Juan & Peters, Jonathan R. & Vassallo, Jose Manuel, 2017. "Understanding the effects of transit benefits on employees’ travel behavior: Evidence from the New York-New Jersey region," Transportation Research Part A: Policy and Practice, Elsevier, vol. 99(C), pages 1-13.
    25. Santos, Georgina & Behrendt, Hannah & Teytelboym, Alexander, 2010. "Part II: Policy instruments for sustainable road transport," Research in Transportation Economics, Elsevier, vol. 28(1), pages 46-91.
    26. Eriksson, Louise & Garvill, Jörgen & Nordlund, Annika M., 2008. "Acceptability of single and combined transport policy measures: The importance of environmental and policy specific beliefs," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(8), pages 1117-1128, October.
    27. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    28. Yanyong Guo & Jibiao Zhou & Yao Wu & Zhibin Li, 2017. "Identifying the factors affecting bike-sharing usage and degree of satisfaction in Ningbo, China," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-19, September.
    29. Rotaris, Lucia & Danielis, Romeo, 2014. "The impact of transportation demand management policies on commuting to college facilities: A case study at the University of Trieste, Italy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 127-140.
    30. Ricchiute, David N., 1997. "Effects of Judgment on Memory: Experiments in Recognition Bias and Process Dissociation in a Professional Judgment Task," Organizational Behavior and Human Decision Processes, Elsevier, vol. 70(1), pages 27-39, April.
    31. Rogge, Karoline S. & Reichardt, Kristin, 2016. "Policy mixes for sustainability transitions: An extended concept and framework for analysis," Research Policy, Elsevier, vol. 45(8), pages 1620-1635.
    32. Florian Kern & Michael Howlett, 2009. "Implementing transition management as policy reforms: a case study of the Dutch energy sector," Policy Sciences, Springer;Society of Policy Sciences, vol. 42(4), pages 391-408, November.
    33. Jean-Michel Cusset, 2004. "Transport-Environment Issues and Countermeasures in Various Metropolises: Bogotà," Post-Print halshs-00080633, HAL.
    34. Justen, Andreas & Schippl, Jens & Lenz, Barbara & Fleischer, Torsten, 2014. "Assessment of policies and detection of unintended effects: Guiding principles for the consideration of methods and tools in policy-packaging," Transportation Research Part A: Policy and Practice, Elsevier, vol. 60(C), pages 19-30.
    35. Sovacool, Benjamin K., 2009. "The importance of comprehensiveness in renewable electricity and energy-efficiency policy," Energy Policy, Elsevier, vol. 37(4), pages 1529-1541, April.
    36. Stradling, S. G. & Meadows, M. L. & Beatty, S., 2000. "Helping drivers out of their cars Integrating transport policy and social psychology for sustainable change," Transport Policy, Elsevier, vol. 7(3), pages 207-215, July.
    37. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
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