中国省际创新网络时空格局演变及其脆弱性评价

doi:10.12118/j.issn.1000-6060.2025.713

Abstract

Abstract:

Due to deglobalization and technological restrictions, building a robust and efficient innovation network system is a critical foundation for safeguarding national innovation security. From the perspective of vulnerability, this study constructs an analytical framework of “structural diagnosis-vulnerability assessment-overall optimization” to systematically examine the spatiotemporal pattern evolution and structural risks of China’s interprovincial innovation network from 2018 to 2023. The results reveal the following: (1) The intensity of interprovincial innovation linkages in China continuously increased from 2018 to 2023, and both network connectivity and knowledge diffusion efficiency improved. However, significant spatial disparities remain. The Beijing-Tianjin-Hebei region, the Yangtze River Delta, and the Pearl River Delta have formed stable core innovation hubs, while parts of northeast, northwest, and southwest China are still on the network periphery, resulting in an overall structural pattern characterized by “core strengthening and peripheral polarization”. (2) The community structure of the innovation network remains generally stable. Innovation collaborations have gradually shifted from cross-regional “enclave-type” connections toward geographically proximate or policy-coordinated regions, forming a structure dominated by high-density communities, such as the Yangtze River Delta, while peripheral communities remain insufficiently embedded. (3) Innovation collaboration has strong dependence on a few key nodes. Continuous failures of core nodes may rapidly reduce network efficiency and trigger structural fragmentation. However, as the intermediary roles of secondary nodes strengthen, the network gradually evolves from a single-hub structure toward a polycentric structure, thereby enhancing the system’s resilience to shocks to some extent. This study deepens our understanding of structural risks in regional innovation systems from the perspective of complex networks and provides theoretical support for balancing efficiency, equity, and security in the development of innovation networks.

Key words: innovation network, patent cooperation, spatiotemporal pattern, vulnerability

LIU Yuxuan, JIANG Zizhen, ZHANG Chenghe, LAN Yihong, WANG Meimei. Spatiotemporal pattern evolution and vulnerability assessment of China’s interprovincial innovation network[J].Arid Land Geography, 2026, 49(9): 1877-1889.

Figures/Tables 9

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网络类型	研究方向
交通类型网络	风险控制^[13]、变化方式^[14]、对比评价^[15]、结构评价^[16]等
产业集群网络	结构优化^[17-18]、风险预防^[19]、格局演化^[20]等
知识创新网络	创新绩效^[21]、结构韧性^[22]、间接调控^[23]等

年份	网络直径	图密度	平均路径长度	全局效率
2018—2020	2	0.538	1.462	0.768
2021—2023	2	0.596	1.404	0.798

年份	平均度	平均加权度	聚类系数
2018—2020	16.129	525.806	0.769
2021—2023	17.871	716.258	0.803

省级行政区	2018—2020年	2021—2023年	省级行政区	2018—2020年	2021—2023年
北京	36.25	28.40	辽宁	5.12	6.21
安徽	5.78	3.14	内蒙古	0.14	0.97
福建	3.73	0.39	宁夏	1.52	0.00
甘肃	0.50	0.34	青海	0.08	0.90
广东	28.76	14.60	山东	11.42	8.25
广西	0.00	0.71	山西	1.32	0.38
贵州	0.49	0.91	陕西	7.01	9.64
海南	0.40	0.66	上海	16.79	20.34
河北	5.38	3.62	四川	8.13	12.85
河南	6.78	1.60	天津	3.58	16.46
黑龙江	0.32	0.42	西藏	0.00	0.48
湖北	19.13	10.14	新疆	1.01	0.93
湖南	8.07	5.53	云南	0.20	1.05
吉林	0.00	0.16	浙江	10.40	8.06
江苏	28.03	28.40	重庆	4.07	1.74
江西	0.57	0.71

年份	攻击比例/%	平均聚类系数	全局效率	平均度	最大连通子图比例
2018—2020	0.0	0.769	0.769	16.129	0.170
	25.8	0.517	0.639	7.167	0.170
	38.7	0.316	0.550	4.100	0.170
	54.8	0.000	0.137	1.200	0.053
2021—2023	0.0	0.803	0.798	17.871	0.170
	32.3	0.565	0.596	6.818	0.170
	48.4	0.196	0.331	2.471	0.170
	71.0	0.000	0.133	1.000	0.135

Spatiotemporal pattern evolution and vulnerability assessment of China’s interprovincial innovation network

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