地理与地理信息科学

科学认识并积极探索中国式创新之路，是加快发展新质生产力、推进中国式现代化的重要议题。本文在阐释新时期中国式创新内涵边界与典型特征的基础上，构建指标体系测度2012—2021年30个省域中国式创新综合指数及各子系统指数，并综合运用莫兰指数、修正引力模型和社会网络分析方法考察其事实格局及空间关联网络演化规律。研究发现：(1)中国式创新水平呈现“东高西低”的区域梯度特征，各子系统趋于协同发展，省际创新水平表现出高值与低值聚类并存的空间集聚模式，空间关联格局逐渐向“多核心”演化；(2)中国式创新空间关联网络由稀疏向稠密、由集中向均衡演进，网络密度稳步提升，跨区域创新联系持续增强，整体结构日益复杂稳定；(3)省际创新溢出能力普遍提升，创新要素流动更顺畅，网络对核心节点的依赖程度下降；(4)创新网络可划分为四大板块，各板块内部联系紧密，板块间存在显著空间溢出效应。研究结论可为优化创新资源配置、完善跨区域协同创新机制提供参考。

Scientific understanding and active exploring the road of Chinese-style innovation is an important issue for accelerating the development of new-quality productive forces and solidly promoting Chinese-style modernization in the new period.Based on an interpretation of the connotative boundaries and typical characteristics of Chinese-style innovation in the new era,this study constructs a measurement indicator system to evaluate the comprehensive index and subsystem indices of Chinese-style innovation across 30 provincial-level regions in China from 2012 to 2021.It further employs Moran's I,the modified gravity model,and social network analysis to examine the factual pattern and evolution of the spatial association network of Chinese-style innovation.The results are shown as follows.(1)Chinese-style innovation exhibits a regional gradient characterized by "higher levels in the east and lower levels in the west";;its subsystems tend to develop in a more coordinated manner,while provincial innovation levels show a spatial agglomeration pattern in which high-value and low-value clusters coexist,and the spatial association pattern is gradually evolving toward a "multi-core" structure.(2)The spatial association network of Chinese-style innovation evolves from sparse to dense and from concentrated to balanced;;network density steadily increases,cross-regional innovation linkages continue to strengthen,spatial interactions become increasingly intensive,and the overall structure becomes more complex and stable.(3)From the perspective of individual network characteristics,interprovincial innovation spillover capacity generally improves,the flow of innovation factors becomes smoother,and the network's dependence on core nodes declines.(4)According to the transmission mechanism of innovation associations,the innovation network can be divided into four major blocks,with close internal linkages within each block and significant spatial spillover effects among blocks.The findings provide useful references for optimizing the allocation of innovation resources and improving cross-regional collaborative innovation mechanisms.