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Spatial and Temporal Evolution of the Chinese Artificial Intelligence Innovation Network

Author

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  • Menger Tu

    (School of Economics, Shanghai University, Shanghai 200444, China
    Regional Economics Applications Laboratory (REAL), University of Illinois at Urbana–Champaign, Urbana, IL 61801, USA)

  • Sandy Dall'erba

    (Regional Economics Applications Laboratory (REAL), University of Illinois at Urbana–Champaign, Urbana, IL 61801, USA
    Department of Agricultural and Consumer Economics, University of Illinois at Urbana–Champaign, Urbana, IL 61801, USA)

  • Mingque Ye

    (School of Economics, Shanghai University, Shanghai 200444, China)

Abstract

Sustainable development has become a concern of all countries globally, and Artificial Intelligence technology emerges at this historic moment. However, few researchers have studied the innovation activities of the Artificial Intelligence industry from the macro-level. This paper focuses on the topological structure and the spatial pattern of the AI patent citation network in China over from 2000–2016. Our main research results are as follows: The network has experienced a striking growth in terms of the size and the number of linkages since 2000, but it has also developed unequally across regions. In the later stages, the network has formed a scale-free network that exhibits small-world property. The network nodes have shown an assortative trait property while weighted preferential attachment has not been significant. In addition, the high values of centrality and numerous linkages between nodes concentrate in the eastern part of China, especially in the Yangtze River Delta, Pearl River Delta, and Bohai Rim. Our results suggest that the AI innovation policies should expand the targets of technological exchange and cultivate more nodes as intermediaries of local knowledge transmission necessary to expand the network and develop the AI industry.

Suggested Citation

  • Menger Tu & Sandy Dall'erba & Mingque Ye, 2022. "Spatial and Temporal Evolution of the Chinese Artificial Intelligence Innovation Network," Sustainability, MDPI, vol. 14(9), pages 1-17, April.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5448-:d:807030
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    1. Guiqiong Xu & Chen Dong & Lei Meng, 2022. "Research on the Collaborative Innovation Relationship of Artificial Intelligence Technology in Yangtze River Delta of China: A Complex Network Perspective," Sustainability, MDPI, vol. 14(21), pages 1-19, October.
    2. Jonggu Jeong, 2022. "Introduction of the First AI Impact Assessment and Future Tasks: South Korea Discussion," Laws, MDPI, vol. 11(5), pages 1-11, September.
    3. Xuandi Gong & Jinluan Ren & Xinyan Wang & Li Zeng, 2022. "Technical Trends and Competitive Situation in Respect of Metahuman—From Product Modules and Technical Topics to Patent Data," Sustainability, MDPI, vol. 15(1), pages 1-23, December.

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