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

Xiaohua Wang, Tianyu Wan, Qing Yang, Mengli Zhang and Yingnan Sun
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Xiaohua Wang: School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan 430070, China
Tianyu Wan: School of Management, Wuhan University of Technology, Wuhan 430070, China
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

Sustainability, 2021, vol. 13, issue 17, 1-21

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.

Keywords: regional innovation; urban agglomeration; Theil index; neural network (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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