京津冀孵化产业空间关联网络结构特征与影响因素

Structural Characteristics and Influencing Factors of Spatial Correlation Network of Beijing-Tianjin-Hebei Incubation Industry

摘要:

为进一步深入揭示京津冀孵化产业空间关联的溢出路径和形成机制，以京津冀地区13个城市为样本，运用修正的引力模型构建孵化产业空间关联网络，从整体网络、个体网络、板块划分等视角剖析网络结构特征与空间聚类现象，并借助二次指派程序（QAP）回归方法考察其空间关联形成的影响因素。结果表明：京津冀地区的核心城市与次级城市的空间联动潜力纵向逐年递增、横向梯度递减，并且在网络结构中的地位和作用存在明显的不均衡特征；网络结构形成了净收益、净溢出、经纪人不同功能板块；地理邻近性、经济发展、人才投入、科技水平等因素影响了网络空间关联关系的形成。因此，京津冀地方政府要深刻把握京津冀区域内核心功能区孵化产业显著强于河北省边缘地带的不平衡发展格局，根据空间关联网络各个板块功能特征因地制宜实行差异化的孵化产业发展模式。

Abstract:

In order to further and deeply reveal the spillover path and formation mechanism of the spatial correlation of the Beijing-Tianjin-Hebei incubation industry, this paper takes 13 cities in the Beijing-Tianjin-Hebei region as samples, and uses the modified gravity model to construct the spatial correlation network of the incubation industry. The characteristics of network structure and spatial clustering are analyzed from the perspectives of overall network, individual network, and block division, and the influencing factors of the formation of spatial associations are investigated with the help of QAP regression method. The results show that the spatial linkage potential of core cities and secondary cities in the Beijing-Tianjin-Hebei region increases year by year, and decreases in gradient, there is an obvious imbalance in the status and function of the network structure, and the network structure forms net income, net spillover, and different functional sections of brokers; factors such as geographical proximity, economic development, talent investment, and technological level have affected the formation of spatial correlations. Therefore, local government of the Beijing-Tianjin-Hebei region should deeply grasp the unbalanced development pattern of that the core functional area incubation industry in the Beijing-Tianjin-Hebei region is significantly stronger than in the marginal areas of Hebei, implement differentiated development mode of incubation industry according to local conditions based on the functional characteristics of each plate of the spatial correlation network.