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The Relative Roles of Socioeconomic Factors and Governance Policies in Urban Traffic Congestion: A Global Perspective

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  • Chao Sun

    (Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 211189, China
    Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China
    School of Transportation, Southeast University, Nanjing 211189, China)

  • Jian Lu

    (Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 211189, China
    Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China
    School of Transportation, Southeast University, Nanjing 211189, China)

Abstract

There is still doubt about how to accurately distinguish the objective and subjective factors that affect traffic congestion. This study aims to re-examine the role of socioeconomic factors and governance policies in the variation of urban traffic congestion from a global perspective at the macro-social development level. The heterogeneous characteristics of the traffic congestion index under the influence of changes in governance policies and variations of social–economic factors are distinguished through a residual trend model. Different time scenarios are addressed in the study to assess the respective contribution of socioeconomic factors and governance policies to variations of traffic congestion, which is helpful for identifying the most destructive factors and the most effective combination of governance policies. Taking Beijing City as the case, the results show that the social-economic factors and governance policies jointly drive congestion fluctuations, but the contribution of governance policies is greater. In addition, governance policies play an important role in alleviating traffic congestion, but unfortunately, an unreasonable combination of governance policies is also the chief culprit for the rise of the traffic congestion index in certain periods. The findings presented here can make us understand macro-mechanisms in response to urban traffic congestion and provide evidence for formulating regional development policies.

Suggested Citation

  • Chao Sun & Jian Lu, 2022. "The Relative Roles of Socioeconomic Factors and Governance Policies in Urban Traffic Congestion: A Global Perspective," Land, MDPI, vol. 11(10), pages 1-17, September.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:10:p:1616-:d:921290
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    References listed on IDEAS

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    1. Bull, Alberto & Thomson, Ian, 2002. "Urban traffic congestion: its economic and social causes and consequences," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), April.
    2. Shao, Jing & Yang, Hangjun & Xing, Xiaoqiang & Yang, Liu, 2016. "E-commerce and traffic congestion: An economic and policy analysis," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 91-103.
    3. Amparo Moyano & Marcin Stępniak & Borja Moya-Gómez & Juan Carlos García-Palomares, 2021. "Traffic congestion and economic context: changes of spatiotemporal patterns of traffic travel times during crisis and post-crisis periods," Transportation, Springer, vol. 48(6), pages 3301-3324, December.
    4. Börjesson, Maria & Hamilton, Carl J. & Näsman, Per & Papaix, Claire, 2015. "Factors driving public support for road congestion reduction policies: Congestion charging, free public transport and more roads in Stockholm, Helsinki and Lyon," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 452-462.
    5. Tian, Ye & Li, Yudi & Sun, Jian & Ye, Jianhong, 2021. "Characterizing favored users of incentive-based traffic demand management program," Transport Policy, Elsevier, vol. 105(C), pages 94-102.
    6. Dadashova, Bahar & Li, Xiao & Turner, Shawn & Koeneman, Pete, 2021. "Multivariate time series analysis of traffic congestion measures in urban areas as they relate to socioeconomic indicators," Socio-Economic Planning Sciences, Elsevier, vol. 75(C).
    7. VENCATAYA Lomendra & PUDARUTH Sharmila & DIRPAL Ganess & NARAIN Vandisha, 2018. "Assessing The Causes & Impacts Of Traffic Congestion On The Society, Economy And Individual: A Case Of Mauritius As An Emerging Economy," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 13(3), pages 230-242, December.
    8. Toan, Trinh Dinh & Wong, Y.D., 2021. "Fuzzy logic-based methodology for quantification of traffic congestion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    9. Jun Yang & Avralt-Od Purevjav & Shanjun Li, 2020. "The Marginal Cost of Traffic Congestion and Road Pricing: Evidence from a Natural Experiment in Beijing," American Economic Journal: Economic Policy, American Economic Association, vol. 12(1), pages 418-453, February.
    10. Jin, Jangik & Rafferty, Peter, 2017. "Does congestion negatively affect income growth and employment growth? Empirical evidence from US metropolitan regions," Transport Policy, Elsevier, vol. 55(C), pages 1-8.
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