Understanding population movement and the evolution of urban spatial patterns: An empirical study on social network fusion data

被引:0
|
作者
Cao, Yu [1 ]
Hua, Zesu [1 ]
Chen, Ting [1 ]
Li, Xiaoying [2 ]
Li, Heng [2 ]
Tao, Dingtian [2 ]
机构
[1] Southeast Univ, Sch Econ & Management, Nanjing, Peoples R China
[2] Hong Kong Polytech Univ, Dept Bldg & Real Estate, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Migration network; Social network analysis; Gravity model; Yangtze River Delta; QAP regression; Breakpoint model;
D O I
10.1016/j.lusepol.2022.106454
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Population movement has become one of the main vehicles for information transfer, factor flow, and resource allocation between cities. It is also considered as the main way to form the structure of regional organizational networks. This study analyzes the population movement channels, spatial patterns, and evolutionary mecha-nisms of the Yangtze River Delta with fused data (i.e., long-scale population migration and short-scale 48-hour population movement.), The results show that the population movement presents multipolar and decentralized evolutionary characteristics, and the population movement network in the Yangtze River Delta region has entered a complex network stage, showing a spider web-like convergent nested structure in terms of the pop-ulation movement at a long time scale (2009-2017). The gravity model reveals that cost factors such as Spatio-temporal distance of population migration and boundary effects between urban nodes are complementary to the urban environment constituted by economic dynamics and social environment. Cultural exchange and regional integration are also quietly removing the cost-benefit constraints of population migration, thereby changing the mediating and diluting effects of the region. (1) Shanghai has not shown the great advantage of being the first city in the region; strong population movement mostly occurs within the provinces, with less cross-provincial movement; (2) population movement is more likely to occur between large and small cities, rather than be-tween large or small cities, two cities with similar industrial structures are more likely to attract and connect with each other, (3) the institutional adhesion of administrative boundaries may have been diluted by the substitution effect of high housing prices, and (4) the stability of land property rights due to driving the regional integration process. This paper extends the vision and methodological practice of the gravity model to examine the network influence mechanism and analyze the mechanism of daily inter-city movements in two dimensions to provide policy insights for understanding the integration process in the Yangtze River Delta and the optimization strategy of regional metropolitan area integration.
引用
收藏
页数:16
相关论文
共 6 条
  • [1] Understanding population movement and the evolution of urban spatial patterns: An empirical study on social network fusion data
    Cao, Yu
    Hua, Zesu
    Chen, Ting
    Li, Xiaoying
    Li, Heng
    Tao, Dingtian
    LAND USE POLICY, 2023, 125
  • [2] Spatial movement patterns among intra-destinations using social network analysis
    Han, Hagchin
    Kim, Seongseop
    Otoo, Felix Elvis
    ASIA PACIFIC JOURNAL OF TOURISM RESEARCH, 2018, 23 (08) : 806 - 822
  • [3] Understanding the structural evolution and driving mechanisms of urban network using firm-level big data and TERGM modeling
    Hu, Shuju
    Chen, Guangda
    Miao, Changhong
    CITIES, 2025, 161
  • [4] Evolution and Optimization of Urban Network Spatial Structure: A Case Study of Financial Enterprise Network in Yangtze River Delta, China
    Zhang, Yizhen
    Wang, Tao
    Supriyadi, Agus
    Zhang, Kun
    Tang, Zhi
    ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2020, 9 (10)
  • [5] Spatial-Data Sharing: Applying social-network analysis to study individual and collective behaviour
    Omran, El. E.
    van Etten, J.
    INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE, 2007, 21 (06) : 699 - 714
  • [6] Study on the Spatial and Temporal Evolution Patterns of Green Innovation Efficiency and Driving Factors in Three Major Urban Agglomerations in China-Based on the Perspective of Economic Geography
    Hu, Biao
    Yuan, Kai
    Niu, Tingyun
    Zhang, Liang
    Guan, Yuqiong
    SUSTAINABILITY, 2022, 14 (15)