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Factors Aggregating Ability and the Regional Differences among China’s Urban Agglomerations

Author

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  • Chengliang Liu

    (School of Urban and Regional Sciences, East China Normal University, Shanghai 200062, China
    Institute for Global Innovation and Development, East China Normal University, Shanghai 200062, China
    Institute of Eco-Chongming, East China Normal University, Shanghai 200062, China
    These authors contributed equally to this work.)

  • Tao Wang

    (School of Urban and Regional Sciences, East China Normal University, Shanghai 200062, China)

  • Qingbin Guo

    (School of Economics and Management, Hainan University, Haikou 570228, China
    These authors contributed equally to this work.)

Abstract

Continuous aggregation of socioeconomic factors is the key issue of sustainable development in urban agglomerations. To date, more attention has been paid to single urban agglomeration than to multiple agglomerations. In this paper, China’s 19 urban agglomerations were selected as the case study and their spatial differences in factors aggregating ability were portrayed comparatively. Firstly, the spatial pattern of urban factors aggregating ability is relatively well distributed in all China’s cases, most noticeably in the Yangtze River Delta urban agglomeration, closely followed by the Beijing-Tianjin-Hebei and the Pearl River Delta urban agglomerations. However, more significant differences on factors aggregating ability are noticeably seen between cities than among urban agglomerations. Meanwhile, the rank-size structure distribution of factors aggregating ability in China’s 19 cases is in line with the Zipf’s law of their urban systems, and divided into three types: Optimized, balanced, and discrete. Furthermore, the urban factors aggregation ability in one urban agglomeration is roughly negatively correlated with its primacy ratio of factors aggregating ability distribution. Lastly, urban agglomerations with higher average values of factors aggregating ability are concentrated on the three major urban agglomerations: The Yangtze River Delta, the Beijing-Tianjin-Hebei and the Pearl River Delta. Otherwise, high-high clusters in the three urban agglomerations are distinctly observed as well.

Suggested Citation

  • Chengliang Liu & Tao Wang & Qingbin Guo, 2018. "Factors Aggregating Ability and the Regional Differences among China’s Urban Agglomerations," Sustainability, MDPI, vol. 10(11), pages 1-20, November.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:11:p:4179-:d:182518
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    1. Kristian Giesen & Jens Südekum, 2011. "Zipf's law for cities in the regions and the country," Journal of Economic Geography, Oxford University Press, vol. 11(4), pages 667-686, July.
    2. Alfaro, Laura & Chen, Maggie Xiaoyang, 2014. "The global agglomeration of multinational firms," Journal of International Economics, Elsevier, vol. 94(2), pages 263-276.
    3. Chang, Chia-Lin & Oxley, Les, 2009. "Industrial agglomeration, geographic innovation and total factor productivity: The case of Taiwan," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(9), pages 2787-2796.
    4. Russo, Francesco & Musolino, Giuseppe, 2012. "A unifying modelling framework to simulate the Spatial Economic Transport Interaction process at urban and national scales," Journal of Transport Geography, Elsevier, vol. 24(C), pages 189-197.
    5. Luca Papi & Emma Sarno & Alberto Zazzaro, 2017. "The geographical network of bank organizations: issues and evidence for Italy," Chapters, in: Ron Martin & Jane Pollard (ed.), Handbook on the Geographies of Money and Finance, chapter 8, pages 156-196, Edward Elgar Publishing.
    6. Hochman, Oded, 2011. "Efficient agglomeration of spatial clubs," Journal of Urban Economics, Elsevier, vol. 69(1), pages 118-135, January.
    7. Michael E. Porter, 2000. "Location, Competition, and Economic Development: Local Clusters in a Global Economy," Economic Development Quarterly, , vol. 14(1), pages 15-34, February.
    8. Michaela Trippl & Markus Grillitsch & Arne Isaksen & Tanja Sinozic, 2015. "Perspectives on Cluster Evolution: Critical Review and Future Research Issues," European Planning Studies, Taylor & Francis Journals, vol. 23(10), pages 2028-2044, October.
    9. Yang, Chih-Hai & Lin, Hui-Lin & Li, Hsiao-Yun, 2013. "Influences of production and R&D agglomeration on productivity: Evidence from Chinese electronics firms," China Economic Review, Elsevier, vol. 27(C), pages 162-178.
    10. Catini, Roberto & Karamshuk, Dmytro & Penner, Orion & Riccaboni, Massimo, 2015. "Identifying geographic clusters: A network analytic approach," Research Policy, Elsevier, vol. 44(9), pages 1749-1762.
    11. Arshad, Sidra & Hu, Shougeng & Ashraf, Badar Nadeem, 2018. "Zipf’s law and city size distribution: A survey of the literature and future research agenda," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 75-92.
    12. Boris A. Portnov & Moshe Schwartz, 2009. "Urban Clusters As Growth Foci," Journal of Regional Science, Wiley Blackwell, vol. 49(2), pages 287-310, May.
    13. Fu, Yuming & Gabriel, Stuart A., 2012. "Labor migration, human capital agglomeration and regional development in China," Regional Science and Urban Economics, Elsevier, vol. 42(3), pages 473-484.
    14. Nils-Bastian Heidenreich & Anja Schindler & Stefan Sperlich, 2013. "Bandwidth selection for kernel density estimation: a review of fully automatic selectors," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(4), pages 403-433, October.
    15. Oskenbayev, Yessengali & Yilmaz, Mesut & Abdulla, Kanat, 2013. "Resource concentration, institutional quality and the natural resource curse," Economic Systems, Elsevier, vol. 37(2), pages 254-270.
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