SCIENTIA GEOGRAPHICA SINICA ›› 2022, Vol. 42 ›› Issue (11): 1889-1899.doi: 10.13249/j.cnki.sgs.2022.11.004

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Characteristics and Influencing Factors of Daily Population Flow Among Cities in China

Shi Xiang1(), Wang Shijun2(), Wang Dongyan3, Hao Feilong2, Li Zhuowei2   

  1. 1. Northeast Asian Research Center, Jilin University, Changchun 130012, Jilin, China
    2. School of Geographical Sciences, Northeast Normal University, Changchun 130024, Jilin, China
    3. College of Earth Sciences, Jilin University, Changchun 130061, Jilin, China
  • Received:2021-04-15 Revised:2022-01-09 Online:2022-11-30 Published:2022-11-20
  • Contact: Wang Shijun E-mail:shixiang@jlu.edu.cn;wangsj@nenu.edu.cn

Abstract:

Using Tencent location big data, this study analyzes the spatial pattern of population flow among 368 cities in China and identifies the influencing factors related to population inflow and outflow based on an exponential random graph model (ERGM). 1) From 2015 to 2018, the spatial distribution pattern of population flow was relatively stable, forming a rhombic spatial structure with Beijing, Shenzhen, Shanghai, Guangzhou, Chengdu, and Dongguan as the ‘center’. The densely populated nodes and channels are mainly concentrated to the east of the Hu Huanyong Line. The significance of this study lies in further determining the core cities and main pillars in the population flow network. 2) The urban subgroup structure obtained by community division shows obvious geographical proximity and inter-provincial differentiation among communities, which form not only small urban subgroups with the provincial capital city forming the core and bordered by the provincial boundary, but also large urban subgroups with a multi-center structure spanning provincial administrative boundaries. However, for most cities, the provincial boundary delimits the main flow circle, and population flow within the same province is more frequent. 3) The influencing factors of the population inflow and outflow networks determined by the ERGM model are consistent with the predictions of neoclassical economics. Market and economic factors such as population scale, urbanization level, time cost, and economic cost still play a leading role in population flow. 4) The attraction of a city to the floating population depends on its individual attributes, while the urban population outflow depends more on the external-network-related elements of the city. To a certain extent, this study verifies the predominance of the urban “pull” in the push-pull theory and the comprehensive effect of various distance factors.

Key words: population flow, Tencent location big data, ERGM, migrant

CLC Number: 

  • C912.81