Study On Urban Commuting Efficiency And Its Improving Countermeasures In China

Commuting is an important part of urban residents travel behaviors. It is closely related to urban traffic jam and other problems. With the rapid development of urban economy and expansion of the urban scale, urban residents’ travel behaviors become increasingly complex. It is urgent to seek measures to improve the urban residents’ commuting efficiency for urban government managers. This paper builds a commuting efficiency model and analyzes the evolution law of urban residents’ travel behavior. Then the paper analyzes the social differentiation of commuting burden and influencing factors of commuting mode choice based on the questionnaire survey with an effective sample size of about 3000 was conducted during February-March 2015, in which all the six urban districts in Tianjin are included. Finally, the paper proposes implications to improve the urban residents’ commuting efficiency. The main contents of this paper are the following seven parts.(1) Determining the main study object methods and structure of this paper and the literature review on commuting efficiency, commuting cost and work-housing balance is put in the first part.(2) Building a commuting efficiency model under the perspective of avoiding loss of commuter’s time value. Firstly, this paper discusses a concept unifying the time-space dimensions of commuting behaviors which is named “time distance”. Then put forward the “time-cost” choice under the perspective of avoiding time value loss, and the non-uniform time model about the whole commuting process. Secondly, it solves the dynamic programming model of commuting efficiency that objective function is maximizing the commuting time distance under the “time-cost” constraint. Finally, this paper analyzes the relationship between commuting efficiency, time value, commuting burden and commuting mode choice.(3) Through summarizing practical experiences of the developed country urban residents travel characteristics and transport development, based on different stages of urbanization, analysis the urban residents travel characteristics and the motivation factors, predict the future development of urban transportation. Proposing the intelligent transportation system, rail transit, “internet & transport” and slow transport to increase the travelling efficiency of residents and the urban transportation management can become fine, informative and scientific.(4) Based on the survey data of Tianjin residents’ commuting characteristics in 2015, this paper systematically analyzes the sample data. The results are as follows: gender, age, occupation and other personal attributes have a great impact on the characteristics of commuting. The slow transport and mass transit lag behind. The efficiency of the whole process of commuting needs to be improved. The jobs-housing mismatch is a serious problem.(5) Building two commuting burden models, this paper analyzes commuting burden among different social groups. The empirical results are as follows: the group from the Party and government organs or public institutions take lower commuting burden comparatively, both age and education are negatively correlated with commuting burden, the group commuting by private cars and the group without local Hukou bear heavier commuting burden relatively, there is a serious jobs-housing mismatch among the low-income group and the group without local Hukou. Urban transportation policy maker not only should focus on commuting efficiency, but also should pay attention to the difference of urban residents’ commuting burden.(6) Based on the survey of residents commuting characteristics in Tianjin city, considering the effect of the intelligent mobile phone information and constructing the structure equation model(SEM) to analyze the deep factors influencing the choice of urban residents’ commuting mode. The empirical results show that: the household registration, housing types, whether students need to send to school and other factors on residents commuting mode was significant; the sharing rate of the subway is low, and the public transport lines and the site coverage are insufficient; smart phones have a significant impact on residents commuting time, route choice, and for public transport mode, the information effect is more significant.(7) Proposing effective measures and corresponding policy implications to improve the commuting efficiency include improving the structure of urban transport, strengthening transport fine management, optimizing urban spatial structure and paying attention to transport fairness.