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Spatiotemporal Patterns of Population Mobility and Its Determinants in Chinese Cities Based on Travel Big Data

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  • Zhen Yang

    (Innovation Institute for Sustainable Maritime Architecture Research and Technology, Qingdao University of Technology, Qingdao 266033, China
    Faculty of Environmental Engineering, The University of Kitakyushu, Kitakyushu 808-0135, Japan)

  • Weijun Gao

    (Innovation Institute for Sustainable Maritime Architecture Research and Technology, Qingdao University of Technology, Qingdao 266033, China
    Faculty of Environmental Engineering, The University of Kitakyushu, Kitakyushu 808-0135, Japan)

  • Xueyuan Zhao

    (Innovation Institute for Sustainable Maritime Architecture Research and Technology, Qingdao University of Technology, Qingdao 266033, China
    Faculty of Environmental Engineering, The University of Kitakyushu, Kitakyushu 808-0135, Japan)

  • Chibiao Hao

    (College of Architecture and Urban Planning, Qingdao University of Technology, Qingdao 266033, China)

  • Xudong Xie

    (College of Architecture and Urban Planning, Qingdao University of Technology, Qingdao 266033, China)

Abstract

Large-scale population mobility has an important impact on the spatial layout of China’s urban systems. Compared with traditional census data, mobile-phone-based travel big data can describe the mobility patterns of a population in a timely, dynamic, complete, and accurate manner. With the travel big dataset supported by Tencent’s location big data, combined with social network analysis (SNA) and a semiparametric geographically weighted regression (SGWR) model, this paper first analyzed the spatiotemporal patterns and characteristics of mobile-data-based population mobility (MBPM), and then revealed the socioeconomic factors related to population mobility during the Spring Festival of 2019, which is the most important festival in China, equivalent to Thanksgiving Day in United States. During this period, the volume of population mobility exceeded 200 million, which became the largest time node of short-term population mobility in the world. The results showed that population mobility presents a spatial structure dominated by two east–west main axes formed by Chengdu, Nanjing, Wuhan, Shanghai; and three north–south main axes formed by Guangzhou, Shenzhen, Shanghai, Wuhan, and Chengdu. The major cities in the four urban agglomerations in China occupy an absolute core position in the population mobility network hierarchy, and the population mobility network presents typical “small world” features and forms 11 closely related groups. Semiparametric geographically weighted regression model results showed that mobile-data-based population mobility variation is significantly related to the value-added of secondary and tertiary industries, foreign capital, average wage, urbanization rate, and value-added of primary industries. When the spatial heterogeneity and nonstationarity was considered, the socioeconomic factors that affect population mobility showed differences between different regions and cities. The patterns of population mobility and determinants explored in this paper can provide a new reference for the balanced development of regional economy.

Suggested Citation

  • Zhen Yang & Weijun Gao & Xueyuan Zhao & Chibiao Hao & Xudong Xie, 2020. "Spatiotemporal Patterns of Population Mobility and Its Determinants in Chinese Cities Based on Travel Big Data," Sustainability, MDPI, vol. 12(10), pages 1-25, May.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:10:p:4012-:d:357899
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    References listed on IDEAS

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    1. Zhang, Kevin Honglin & Song, Shunfeng, 2003. "Rural-urban migration and urbanization in China: Evidence from time-series and cross-section analyses," China Economic Review, Elsevier, vol. 14(4), pages 386-400.
    2. Jin Yang & Hui Wang & Songqing Jin & Kevin Chen & Jeffrey Riedinger & Chao Peng, 2016. "Migration, local off-farm employment, and agricultural production efficiency: evidence from China," Journal of Productivity Analysis, Springer, vol. 45(3), pages 247-259, June.
    3. Ye Liu & Jianfa Shen, 2014. "Spatial patterns and determinants of skilled internal migration in China, 2000–2005," Papers in Regional Science, Wiley Blackwell, vol. 93(4), pages 749-771, November.
    4. Christopher Bitter & Gordon Mulligan & Sandy Dall’erba, 2007. "Incorporating spatial variation in housing attribute prices: a comparison of geographically weighted regression and the spatial expansion method," Journal of Geographical Systems, Springer, vol. 9(1), pages 7-27, April.
    5. Y.H. Dennis Wei & Xinyue Ye, 2009. "Beyond Convergence: Space, Scale, And Regional Inequality In China," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 100(1), pages 59-80, February.
    6. Mueser Peter R. & Graves Philip E., 1995. "Examining the Role of Economic Opportunity and Amenities in Explaining Population Redistribution," Journal of Urban Economics, Elsevier, vol. 37(2), pages 176-200, March.
    7. Larry A. Sjaastad, 1970. "The Costs and Returns of Human Migration," Palgrave Macmillan Books, in: Harry W. Richardson (ed.), Regional Economics, chapter 9, pages 115-133, Palgrave Macmillan.
    8. Hamparsum Bozdogan, 1987. "Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 345-370, September.
    9. Knapp, Thomas A. & Graves, Philip E., 1989. "On the role of amenities in models of migration and regional development," MPRA Paper 19914, University Library of Munich, Germany.
    10. Jiwei Li & Qingqing Ye & Xuankai Deng & Yaolin Liu & Yanfang Liu, 2016. "Spatial-Temporal Analysis on Spring Festival Travel Rush in China Based on Multisource Big Data," Sustainability, MDPI, vol. 8(11), pages 1-16, November.
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