统计研究

本文在构建数字经济创新合作数据库的基础上，运用社会网络分析方法对数字经济创新合作网络时空演变特征进行分析，并评估其收入分配效应。研究发现：首先，在时间维度，数字经济创新合作经历了波动上行阶段（1985—2000年）、合作高速增长阶段（2001—2015年）和高质量合作阶段（2016年至今），且呈现出高度的空间集聚特征。其次，在空间维度，数字经济产业的创新扩散效应持续增强，城市群之间逐渐形成较为紧密的合作关系。再次，在收入分配维度，参与合作显著提升了本地收入水平，并有效缩小了地区间相对差距。最后，从时空异质性来看，经济高速增长阶段，数字经济创新合作对于地区发展的影响要大于高质量发展阶段，但对于区域不平衡的缓解作用要小于高质量发展阶段；而空间异质性检验显示，数字经济创新合作对于其他城市群发展的促进作用要大于京津冀、长三角和粤港澳大湾区城市群；值得注意的是，数字经济创新合作在缩小其他城市群之间相对差距的同时，也促进了绝对差距的收敛，这可能与其单核心的经济空间布局有较大关系。本文从创新合作视角拓展了数字经济研究的边界，对创新扩散效应的动态考察深化了现有对创新合作网络的研究，并为缓解偏向性技术进步与区域平衡发展的矛盾提供了新的思路。

Based on the construction of a digital economy innovation collaboration database, this study employs social network analysis(SNA) to examine the spatio-temporal evolution characteristics of digital economy innovation collaboration networks and evaluates their income distribution effects. The findings reveal that: First, temporally, digital economy innovation collaboration has evolved through three phases—fluctuating upward phase(1985—2000), rapid growth phase(2001—2015), and high-quality collaboration phase(2016—present), while exhibiting significant spatial agglomeration. Second, spatially, the innovation diffusion effects of the digital economy industry have continuously strengthened, fostering increasingly close cooperation relationships among city clusters. Third, in terms of income distribution, participation in digital economy innovation collaboration significantly enhances local income levels and effectively reduces relative regional disparities. Finally, spatio-temporal heterogeneity analyses indicate that digital economy innovation collaboration during the rapid economic growth phase has a greater impact on regional development than during the high-quality development phase, though its role in mitigating regional imbalance is weaker. Spatial heterogeneity tests show that digital economy innovation collaboration exerts a stronger developmental impetus on non-core city clusters compared to the three major city clusters of Beijing-Tianjin-Hebei, the Yangtze River Delta, and Guangdong-Hong Kong Macao Greater Bay Area. Notably, while narrowing relative disparities among non-core city clusters, digital economy innovation collaboration also promotes convergence in absolute gaps, likely linked to their single-core economic spatial distribution. This study expands the boundaries of digital economy research through the lens of innovation collaboration, deepens existing research on innovation collaboration networks via dynamic analysis of diffusion effects, and offers new insights for reconciling the tension between biased technological progress and balanced regional development.