IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v14y2024i5p655-d1381528.html
   My bibliography  Save this article

Spatial Analysis of Intercity Migration Patterns of China’s Rural Population: Based on the Network Perspective

Author

Listed:
  • Yihu Zhou

    (College of Public Administration, Nanjing Agricultural University, Nanjing 210095, China)

  • Huiguang Chen

    (College of Public Administration, Nanjing Agricultural University, Nanjing 210095, China)

  • Tingting Fang

    (Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China)

Abstract

Since entering the 21st century, many developing countries around the world have begun to enter a stage of rapid urbanization; large-scale “rural-urban” population migration has become a typical social phenomenon in these countries. Against this backdrop, this paper aims to elucidate the spatial migration characteristics of rural populations and to discuss future rural–urban development strategies. For this purpose, this paper takes China as a case and employs methods such as spatial autocorrelation analysis, hotspot analysis, and network analysis to construct an intercity migration network of rural migrants and analyze its spatial characteristics and internal structure. The results indicate that the migration pattern of the rural population exhibits notable spatial clustering features. Cities in the eastern and central regions are, respectively, hotspots for the inflow and outflow of rural populations, with internal migration dominating in western cities and relatively inactive rural population movements in northeastern cities. Municipalities directly under the central government, sub-provincial cities, and provincial capitals show a significant tendency to attract rural populations, while prefecture-level and county-level cities mainly radiate rural populations outward. Cities nationwide form seven major clusters in the migration network, and these clusters exhibit distinct structural characteristics. Rural population migration is influenced by various factors. In the future, considerations should focus on the county as the primary unit, attracting rural populations for local employment, and promoting rural revitalization and agriculture development. The findings of this paper are of reference significance not only to China but also to many developing countries with similar national conditions in the world.

Suggested Citation

  • Yihu Zhou & Huiguang Chen & Tingting Fang, 2024. "Spatial Analysis of Intercity Migration Patterns of China’s Rural Population: Based on the Network Perspective," Agriculture, MDPI, vol. 14(5), pages 1-24, April.
  • Handle: RePEc:gam:jagris:v:14:y:2024:i:5:p:655-:d:1381528
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/14/5/655/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/14/5/655/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Phan, Diep & Coxhead, Ian, 2010. "Inter-provincial migration and inequality during Vietnam's transition," Journal of Development Economics, Elsevier, vol. 91(1), pages 100-112, January.
    2. Duncan J. Watts & Steven H. Strogatz, 1998. "Collective dynamics of ‘small-world’ networks," Nature, Nature, vol. 393(6684), pages 440-442, June.
    3. Litwack, John M. & Qian, Yingyi, 1998. "Balanced or Unbalanced Development: Special Economic Zones as Catalysts for Transition," Journal of Comparative Economics, Elsevier, vol. 26(1), pages 117-141, March.
    4. Barabási, Albert-László & Albert, Réka & Jeong, Hawoong, 1999. "Mean-field theory for scale-free random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 272(1), pages 173-187.
    5. Vladimir Balaz & Allan M. Williams, 2011. "Risk attitudes and migration experience," Journal of Risk Research, Taylor & Francis Journals, vol. 14(5), pages 583-596, May.
    6. Hafner-Burton, Emilie M. & Kahler, Miles & Montgomery, Alexander H., 2009. "Network Analysis for International Relations," International Organization, Cambridge University Press, vol. 63(3), pages 559-592, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xiaoxuan Zhang & John Gibson, 2024. "How well do gridded population estimates proxy for actual population changes? Evidence from four gridded data products and three censuses for China," Working Papers in Economics 24/07, University of Waikato.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pongou, Roland & Tchuente, Guy & Tondji, Jean-Baptiste, 2021. "Optimally Targeting Interventions in Networks during a Pandemic: Theory and Evidence from the Networks of Nursing Homes in the United States," GLO Discussion Paper Series 957, Global Labor Organization (GLO).
    2. Roland Pongou & Guy Tchuente & Jean-Baptiste Tondji, 2021. "Optimally Targeting Interventions in Networks during a Pandemic: Theory and Evidence from the Networks of Nursing Homes in the United States," Papers 2110.10230, arXiv.org.
    3. Yutaka Okabe & Akira Shudo, 2021. "Microscopic Numerical Simulations of Epidemic Models on Networks," Mathematics, MDPI, vol. 9(9), pages 1-19, April.
    4. Jacob Wood & Gohar Feroz Khan, 2015. "International trade negotiation analysis: network and semantic knowledge infrastructure," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(1), pages 537-556, October.
    5. Eliane El Badaoui & Eric Strobl & Frank Walsh, 2014. "The Impact of Internal Migration on Local Labour Markets in Thailand," Working Papers hal-04141356, HAL.
    6. Mohamed Amara & Hatem Jemmali, 2018. "Deciphering the Relationship Between Internal Migration and Regional Disparities in Tunisia," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 313-331, January.
    7. Tatiane Menezes & R. Silveira-Neto & Carlos Azzoni, 2012. "Demography and evolution of regional inequality," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 49(3), pages 643-655, December.
    8. Huan Wang & Chuang Ma & Han-Shuang Chen & Ying-Cheng Lai & Hai-Feng Zhang, 2022. "Full reconstruction of simplicial complexes from binary contagion and Ising data," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    9. Liang, Wei & Shi, Yuming & Huang, Qiuling, 2014. "Modeling the Chinese language as an evolving network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 268-276.
    10. Vinayak, & Raghuvanshi, Adarsh & kshitij, Avinash, 2023. "Signatures of capacity development through research collaborations in artificial intelligence and machine learning," Journal of Informetrics, Elsevier, vol. 17(1).
    11. Supriya Tiwari & Pallavi Basu, 2024. "Quasi-randomization tests for network interference," Papers 2403.16673, arXiv.org, revised Oct 2024.
    12. Anzhi Sheng & Qi Su & Aming Li & Long Wang & Joshua B. Plotkin, 2023. "Constructing temporal networks with bursty activity patterns," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    13. Tobias Böhmelt & Jürg Vollenweider, 2015. "Information flows and social capital through linkages: the effectiveness of the CLRTAP network," International Environmental Agreements: Politics, Law and Economics, Springer, vol. 15(2), pages 105-123, May.
    14. Samrachana Adhikari & Beau Dabbs, 2018. "Social Network Analysis in R: A Software Review," Journal of Educational and Behavioral Statistics, , vol. 43(2), pages 225-253, April.
    15. Cynthia Couette, 2024. "Epistemic competition in global governance: The case of pharmaceutical patents," Global Policy, London School of Economics and Political Science, vol. 15(3), pages 516-527, June.
    16. Keigo Nishida, 2014. "Agricultural productivity differences and credit market imperfections," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 23(8), pages 1262-1276, December.
    17. Wang, Xiaojie & Slamu, Wushour & Guo, Wenqiang & Wang, Sixiu & Ren, Yan, 2022. "A novel semi local measure of identifying influential nodes in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    18. Michael Kenney & Stephen Coulthart & Dominick Wright, 2017. "Structure and Performance in a Violent Extremist Network," Journal of Conflict Resolution, Peace Science Society (International), vol. 61(10), pages 2208-2234, November.
    19. Yan Qiang & Bo Pei & Weili Wu & Juanjuan Zhao & Xiaolong Zhang & Yue Li & Lidong Wu, 2014. "Improvement of path analysis algorithm in social networks based on HBase," Journal of Combinatorial Optimization, Springer, vol. 28(3), pages 588-599, October.
    20. Lin, Dan & Wu, Jiajing & Xuan, Qi & Tse, Chi K., 2022. "Ethereum transaction tracking: Inferring evolution of transaction networks via link prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:14:y:2024:i:5:p:655-:d:1381528. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.