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Research on Innovation Non-Equilibrium of Chinese Urban Agglomeration Based on SOM Neural Network

Author

Listed:
  • Xiaohua Wang

    (School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan 430070, China
    These authors contributed equally to this work.)

  • Tianyu Wan

    (School of Management, Wuhan University of Technology, Wuhan 430070, China
    These authors contributed equally to this work.)

  • Qing Yang

    (School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan 430070, China)

  • Mengli Zhang

    (School of Mathematics and Statistics, Central South University, Changsha 410083, China)

  • Yingnan Sun

    (School of Economics and Trade, Henan University of Technology, Zhengzhou 450001, China)

Abstract

Different indicators, such as the number of patent applications, the number of grants, and the patent conversion rate, were proposed in this study to analyze the issue of innovation imbalance within and between urban agglomerations from a new perspective. First, a preliminary analysis of the current state of innovation and development of China’s nine urban agglomerations was conducted. Then the Theil index, widely used in equilibrium research, was employed to measure the overall innovation gap of China’s urban agglomerations. The study innovatively used the self-organizing feature map to identify the correlation characteristics of the innovation and development within China’s urban agglomerations and visualize them through Geographic Information Science. The research findings show that the hierarchical differentiation of the innovation and development of China’s urban agglomerations is becoming increasingly clear, and that the imbalance in regional innovation development is pronounced. The imbalance in innovation development within urban agglomerations is more significant than the imbalance in innovation development among urban agglomerations. The analysis indicated that a possible cause is the crowding effect and administrative standard effect of the central city. The key to addressing this problem is promoting innovative and coordinated development between regions.

Suggested Citation

  • Xiaohua Wang & Tianyu Wan & Qing Yang & Mengli Zhang & Yingnan Sun, 2021. "Research on Innovation Non-Equilibrium of Chinese Urban Agglomeration Based on SOM Neural Network," Sustainability, MDPI, vol. 13(17), pages 1-21, August.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:17:p:9506-:d:620615
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    References listed on IDEAS

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    Cited by:

    1. Li Liu & Jin Luo & Xin Xiao & Bisong Hu & Shuhua Qi & Hui Lin & Xiaofang Zu, 2022. "Spatio-Temporal Evolution of Urban Innovation Networks: A Case Study of the Urban Agglomeration in the Middle Reaches of the Yangtze River, China," Land, MDPI, vol. 11(5), pages 1-21, April.

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