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Regional Innovation

Can Urban Polycentric Spatial Structure Enhance the Level of  Artificial Intelligence? 

Huang Qinghua1, 2 , He Siyu1 

(1.School of Economics and Management, Southwest University, Chongqing 400715, China; 2.Chongqing Re⁃ search Center for Design-Driven Enterprises, Southwest University, Chongqing 400715, China)

Abstract: Artificial intelligence (AI) is becoming a core engine driving high-quality eco⁃ nomic development. Yet the development level of urban artificial intelligence in China exhibits  significant spatial imbalance. Meanwhile, urban spatial patterns are shifting from monocentric  agglomeration to polycentric diffusion, as the construction of sub-centers and specialized nodes  has become a key strategy to alleviate over⁃concentration. Whether and how urban spatial struc⁃ ture, especially polycentric spatial organization, affects the development of artificial intelligence  remains an important and timely question. This paper utilizes panel data from 271 prefecturelevel and above cities in China from 2008 to 2023, and employs a two-way fixed effects panel  model to systematically examine the effect, transmission mechanisms, and heterogeneous condi⁃ tions of polycentric spatial structure on urban artificial intelligence levels. The findings are as  follows: ①Polycentric spatial structure significantly enhances the level of urban artificial intelli⁃ gence. For every 0.1 increase in the degree of polycentricity, the number of AI firms increases by  approximately 3.1%. This conclusion remains robust after a series of robustness tests, including  variable substitution, instrumental variable methods, and exclusion of abnormal samples. ② Mechanism analysis indicates that polycentric spatial structure indirectly promotes AI develop⁃ ment through two pathways: enhancing the development level of the digital economy, which pro⁃ vides essential data resources, computing power, and application ecosystems for AI, and expand⁃ ing the scale of information technology talent, which facilitates knowledge spillovers and innova⁃ tion synergy effects. ③Heterogeneity analysis reveals that the positive effect of polycentric spa⁃ tial structure on AI development is significant in the eastern, central, and northeast regions, but  not in the western region. Moreover, this effect is more pronounced in cities with higher levels of  openness and higher urbanization rates. Finally, based on the above conclusions, targeted devel⁃ opment and improvement suggestions are proposed from five aspects: ①Promote polycentric de⁃ velopment tailored to local conditions—the eastern/central/northeast should plan sub-centers, while the west should first strengthen its main urban core. ②Strengthen cross-center digital in⁃ frastructure to bridge the digital divide. ③Expand the IT talent pool through improved recruit⁃ ment and retention policies. ④Implement differentiated spatial planning—coastal cities encour⁃ age polycentric collaboration, while inland cities should cultivate core clusters. ⑤Improve intracity governance mechanisms and transport networks to ensure functional coordination. 

Key words: polycentric spatial structure; artificial intelligence level; digital economy; urban  development; innovation synergy; industrial agglomeration; knowledge spillover; technological in⁃ novation