长江经济带绿色创新效率的空间关联网络结构及驱动因素

绿色创新效率作为“绿色发展”和“创新驱动”的融合点，已成为推进长江经济带高质量发展的关键。从社会网络视角，对流域绿色创新效率的空间关联网络结构及驱动因素进行实证分析。研究发现:流域省际间绿色创新效率的相互依赖关系与空间溢出渠道逐年增多，空间关联网络密度逐年提升，各省市皆受到其他地区和整体网络的影响，等级森严的空间结构逐渐被打破，网络结构也日趋稳定，但各地绿色创新效率的协同发展仍有待提升；网络中板块的形成打破了传统行政边界的桎梏，各省市逐渐由离散走向联合，扩散辐射作用使流域省市间形成集群化发展；板块间关联传导机制具有明显的梯度溢出特征，“马太效应”明显；此外，囿于流域间在经济发展模式、绿色创新环境的较大差距，跨地域创新合作的意愿与动力被削弱，绿色创新效率的要素流动受阻，导致省市间存在关联的概率降低。因此，流域省市应依据其在空间关联网络中的角色与作用，从整体上把握绿色创新效率提升的空间传递机制，形成“属性—关系”驱动型发展思路，缩小绿色创新环境差异，促进要素跨地区流动，进而实现全流域经济的绿色协同发展。

Spatial Network Structure and Driving Factors of Green Innovation Efficiency in Yangtze River Economic Zone

As the integration point of “innovation-driven” and “green development”, green innovation efficiency has become the key to promoting high-quality development in Yangtze River Economic Zone (YREZ). This study empirically analyzed the spatial correlation network structure and driving factors of green innovation efficiency from the perspective of social network analysis. The study finds that the overflow channels and mutual relation between provinces increase yearly, so does the density of spatial correlation networks. Green innovation efficiency in all provinces are influenced by other regions and the overall spatial network in this basin, the hierarchical spatial structure is gradually broken down, and the network structure becomes increasingly stable. However, synergistic development of green innovation efficiency in different regions still needs to be improved. The formation of “plates” in the network breaks the traditional administrative boundary, the provinces changed from discrete to united gradually, and the diffusion radiation made the provinces in the basin form a cluster development. The transmission mechanism of correlation network has obvious gradient overflow characteristics, meanwhile, the “Matthew effect” is obvious. In addition, constrained by the large gap between economic development model and green innovation environment in this basin, the willingness and motivation of trans-regional innovation cooperation is weakened, and flow of elements of green innovation efficiency is blocked, resulting in a reduced correlation probability among those provinces and municipalities. Therefore, based on their roles in the spatial correlation network, the provinces and municipalities in this basin should grasp the overall spatial transmission mechanism of the improvement of green innovation efficiency, form an “attribute-relationship”-driven development approach, narrow down the difference in green innovation environment, and promote factors flow across regions to realize the green and coordinated development of the basin’s economy.