Beijing, the capital city of China, currently experiences serious traffic congestion and extreme air pollution. To mitigate these issues, Beijing Municipality is currently considering implementing a congestion charging system that requires drivers to pay for entering congested areas. A stated preference survey of 5,468 Beijing residents was conducted mid-May 2016 to investigate public attitudes toward the proposal. This research analyzed the survey data using a multinomial logit (MNL) model and a cluster analysis to identify relationships between residents’ characteristics (including the basic socioeconomic and demographic attributes; and their workday travel characteristics) and their attitudes toward Beijing congestion charging. Women are more likely to remain neutral toward congestion pricing. Among employment categories, students are most likely to support, the retired/unemployed are most likely to oppose, and the employed tend to fall between students and the retired/unemployed when it comes to acceptability of congesting pricing. Travelers who use public transit, bicycle, or walk to work are more likely to support congestion charging than car commuters. Income and car ownership have nonlinear relationships with acceptability. High- and low-income commuters are more likely to support congestion charging than middle-income commuters. Residents with no access to cars, with access to one car, or to more than two cars are more likely to support congestion charging than people with access to two cars. There is also a nonlinear relationship between the monetary amount people are willing to pay for the charge and their acceptance of congestion pricing, which merits additional research. The perceived effectiveness of congestion charging strongly influences their acceptance, and so does a traveler’s familiarity with the general congestion charging concept and the specific plan to be implemented in Beijing.


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    Title :

    Understanding Public Acceptability of Congestion Charging in Beijing


    Contributors:
    Li, Xin (author) / Yuan, Yun (author) / Wang, Haoran (author) / Hu, Jia (author)


    Publication date :

    2020-06-10




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




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