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| Urban Collaborative Innovation Network and Its Influencing Factors of the AI Field in the Yangtze River Delta Region |
| Wang Yuefen1,2, Zhou Hongyu2, Cen Yonghua1 |
1.Institute for Big Data Science, Tianjin Normal University, Tianjin 300074
2.School of Economics & Management, Nanjing University of Science & Technology, Nanjing 210094 |
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Abstract This study explores the mechanism and influencing factors of urban collaborative innovation, and promotes the development of science & technology innovation between regions and multiple subjects. It collects patent data in artificial intelligence (AI) in the Yangtze River Delta region from 2016 to 2021, combining cities and patented technology knowledge to build a collaborative innovation network based on 27 cities. It analyzes the network's centrality, cohesive subgroup, and structural hole using social network analysis. Additionally, exponential random graph models (ERGM) is used to analyze the influencing factors of urban collaborative innovation by combining the historical statistical indicators, city level, subordinate province, and historical experience network. We find that the urban collaborative innovation network in AI in the Yangtze River Delta region has increased in scale and stability over time, and has become balanced. Regarding the influencing factors of the network, the nodes' main effect plays an obvious role in promoting development and education expenditure at the industrialization level. Moreover, a homogeneous tie that affects the subordinate province and administrative level has different effects on network development. Additionally, the network has a relatively obvious path-dependence trend, and the actual network of the preceding year has an important impact on the network formation in the following year.
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Received: 12 August 2023
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