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    Causes of Spatial Patterns of Livability in Chinese Cities: MGWRL Analysis Based on Didi's Big Data

    Source: Journal of Urban Planning and Development:;2021:;Volume ( 147 ):;issue: 003::page 04021025-1
    Author:
    Jingjun Hao
    ,
    Peng Zhang
    ,
    Wei Yu
    ,
    Xiaoqing Mou
    DOI: 10.1061/(ASCE)UP.1943-5444.0000711
    Publisher: ASCE
    Abstract: Continuous expansion results in urban problems such as congestion, pollution, and crime that seriously threaten the sustainable development of Chinese cities. How to promote the development of efficient and livable cities in China is of great significance in easing the pressure of urban development and promoting healthy urban development. Based on Didi's “urban development index,” this study explores the spatial distribution and spatial driving factors of urban livability in China through Theil index decomposition, standard deviation ellipse analysis, global and local spatial autocorrelation analysis, and multiscale geographically weighted regression with lagged dependent variables (MGWRL) model analysis. The results reveal the following three points. First, China's urban livability presents a spatial pattern of “east-west-middle” decreasing, with large spatial distribution differences and significant spatial dependence. Second, the effects of urban livability influencing factors have spatial scale differences. The impact of global variables such as human capital, fixed assets investment, medical level, and greening degree on urban livability is consistent at the global level. Local variables such as finance, urbanization, advanced industrial structure, and foreign trade only have consistent impacts on urban livability in local regions, and the scope of these regions varies with different variables. Third, it is further found that the effects of some local variables on urban livability have spatial heterogeneity. The effects of finance on urban livability shows a decreasing trend from east to west and from north to south in space; the effects of advanced industrial structure on urban livability are spatially characterized by outward radiation attenuation along the Yellow River and the middle reaches of the Yangtze River; only less than one-third of the local regression coefficients of variables such as spatial lag, urbanization, and foreign trade passed the significance test. Relevant government departments should pay full attention to the spatial pattern and spatial dependence of urban livability in China, and make overall planning and improvement strategies; attention should be paid to the spatial scale difference and the spatial heterogeneity of influencing factors in policy formulation, and the differentiated development policy of livable cities should be put forward according to local conditions.
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      Causes of Spatial Patterns of Livability in Chinese Cities: MGWRL Analysis Based on Didi's Big Data

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4270545
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    contributor authorJingjun Hao
    contributor authorPeng Zhang
    contributor authorWei Yu
    contributor authorXiaoqing Mou
    date accessioned2022-01-31T23:53:51Z
    date available2022-01-31T23:53:51Z
    date issued9/1/2021
    identifier other%28ASCE%29UP.1943-5444.0000711.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4270545
    description abstractContinuous expansion results in urban problems such as congestion, pollution, and crime that seriously threaten the sustainable development of Chinese cities. How to promote the development of efficient and livable cities in China is of great significance in easing the pressure of urban development and promoting healthy urban development. Based on Didi's “urban development index,” this study explores the spatial distribution and spatial driving factors of urban livability in China through Theil index decomposition, standard deviation ellipse analysis, global and local spatial autocorrelation analysis, and multiscale geographically weighted regression with lagged dependent variables (MGWRL) model analysis. The results reveal the following three points. First, China's urban livability presents a spatial pattern of “east-west-middle” decreasing, with large spatial distribution differences and significant spatial dependence. Second, the effects of urban livability influencing factors have spatial scale differences. The impact of global variables such as human capital, fixed assets investment, medical level, and greening degree on urban livability is consistent at the global level. Local variables such as finance, urbanization, advanced industrial structure, and foreign trade only have consistent impacts on urban livability in local regions, and the scope of these regions varies with different variables. Third, it is further found that the effects of some local variables on urban livability have spatial heterogeneity. The effects of finance on urban livability shows a decreasing trend from east to west and from north to south in space; the effects of advanced industrial structure on urban livability are spatially characterized by outward radiation attenuation along the Yellow River and the middle reaches of the Yangtze River; only less than one-third of the local regression coefficients of variables such as spatial lag, urbanization, and foreign trade passed the significance test. Relevant government departments should pay full attention to the spatial pattern and spatial dependence of urban livability in China, and make overall planning and improvement strategies; attention should be paid to the spatial scale difference and the spatial heterogeneity of influencing factors in policy formulation, and the differentiated development policy of livable cities should be put forward according to local conditions.
    publisherASCE
    titleCauses of Spatial Patterns of Livability in Chinese Cities: MGWRL Analysis Based on Didi's Big Data
    typeJournal Paper
    journal volume147
    journal issue3
    journal titleJournal of Urban Planning and Development
    identifier doi10.1061/(ASCE)UP.1943-5444.0000711
    journal fristpage04021025-1
    journal lastpage04021025-13
    page13
    treeJournal of Urban Planning and Development:;2021:;Volume ( 147 ):;issue: 003
    contenttypeFulltext
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