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

  • Yacan Wang
  • , Kexin Geng
  • , Anthony D. May
  • , Huiyu Zhou*
  • *Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

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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.
Original languageEnglish
Pages (from-to)74-87
Number of pages14
JournalTransport Policy
Volume117
Early online date12 Jan 2022
DOIs
Publication statusPublished - Mar 2022

Funding

This study is supported by Chinese National Natural Science Foundation (72071017), the joint project of the National Natural Science Foundation of China and the Joint Programming Initiative Urban Europe (NSFC – JPI UE), China part (‘U-PASS’ 71961137005). Beijing Municipal Philosophy Social Science Foundation (20GLA006, 21GLB033). The Fundamental Research Funds for the Central Universities (2019JBW008). This study is supported by Chinese National Natural Science Foundation ( 72071017 ), the joint project of the National Natural Science Foundation of China and the Joint Programming Initiative Urban Europe (NSFC – JPI UE), China part (‘U-PASS’ 71961137005 ). Beijing Municipal Philosophy Social Science Foundation ( 20GLA006 , 21GLB033 ). The Fundamental Research Funds for the Central Universities ( 2019JBW008 ).

FundersFunder number
Joint Programming Initiative Urban Europe
Beijing Municipal Social Science Foundation20GLA006, 21GLB033
National Natural Science Foundation of China72071017, U-PASS’ 71961137005
Fundamental Research Funds for the Central Universities2019JBW008

    Keywords

    • Traffic demand management policy
    • Commuter behavior
    • SP Experiment
    • MNL Model
    • Policy mix

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