城市群创新联系网络结构与创新效率研究

doi:10.13249/j.cnki.sgs.2020.11.008

摘要/Abstract

摘要：

引入修正引力模型、社会网络分析方法、DEA模型以及Tobit模型，探讨2001—2015年京津冀、长三角、珠三角三大城市群的创新联系网络结构对创新效率的影响。研究表明：① 创新联系格局方面，京津冀城市群呈现以“京津”为核心的放射状发展特征，长三角城市群呈现以“Z”字形为主轴的类钻石型空间格局，珠三角城市群形成了以珠江口两侧城市为核心、其他城市为重要节点的空间格局；② 在创新联系网络结构特征方面，京津冀城市群呈极核式发展，群内创新联系高度依赖于核心城市，长三角和珠三角城市群由单中心驱动转变为多中心驱动，呈均衡发展特征，京津冀和珠三角城市群创新联系网络具有“小世界”网络特征；③ Tobit模型回归结果显示，三大城市群中，城市节点在城市群创新联系网络中的中心位置、中介地位、对结构洞的运用能力和集聚程度对其创新效率的影响存在差异。

关键词: 创新联系网络, 网络结构, 创新效率, 城市群

Abstract:

Based on the modified Gravity Model, SNA method, DEA (Data Envelopment Analysis) model and Tobit model, this article analyzes the effect of spatial structure of the innovation linkage network on the innovation efficiency in cities. The main findings of this study are drawn as follows: 1) The innovation linkage showed a radial expansion with the core of Beijing-Tianjin in the Beijing-Tianjin-Hebei (BTH), and a diamond-shaped structure in the Yangtze River Delta (YRD), and in the Pearl River Delta (PRD), the innovation linkage presented a spatial pattern with the cities on both sides of the Pearl River estuary as the core and other cities as important nodes. 2) The innovation linkage network had a polar core development and the innovation linkage highly depended on the core cities in the BTH, but in the YRD and the PRD, the innovation linkage network showed the balanced development from single-center driving to multi-center driving. In addition, the innovation linkage networks in the BTH and PRD were characterized by the ‘small world’. 3) Tobit regression results showed that the central position, betweenness position, occupying capacity of structural holes and agglomeration had different effects on the innovation efficiency in the three urban agglomerations.

Key words: innovation linkage network, network structure, innovation efficiency, urban agglomeration

中图分类号:

K902

盛彦文, 苟倩, 宋金平. 城市群创新联系网络结构与创新效率研究[J]. 地理科学, 2020, 40(11): 1831-1839.

Sheng Yanwen, Gou Qian, Song Jinping. Innovation Linkage Network Structure and Innovation Efficiency in Urban Agglomeration: A Case of the Beijing-Tianjin-Hebei, the Yangtze River Delta and the Pearl River Delta[J]. SCIENTIA GEOGRAPHICA SINICA, 2020, 40(11): 1831-1839.

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	PC		WPC		BC		CD		CC		CC²
	Coef.	t	Coef.	t	Coef.	t	Coef.	t	Coef.	t	Coef.	t
注：括号内为t 值； ^*、^、^分别表示1%，5%，10%的显著性水平；Coef.为回归系数；空白为无内容；PC为选取点度中心性；WPC*为加权中心性；BC为中间中心性；CD为限制度；CC为聚类系数；CC²为聚类系数二次方。限于篇幅省略控制变量回归结果。
京津冀城市群	0.524	（2.830）^***	0.393	（0.930）	0.996	（3.020）^***	?0.085	（?2.410）^**	?0.002	（?0.060）
									0.742	（2.190）^*	?0.007	（?2.220）^**
长三角城市群	0.445	（4.35）^***	1.231	（4.02）^***	3.446	（5.390）^***	0.062	（1.210）	?0.067	（?0.870）
									1.342	（0.780）	?0.014	（?0.830）
珠三角城市群	0.383	（3.730）^***	?0.378	（?0.790）	0.808	（2.320）^**	0.301	（2.750）^***	0.073	（1.030）
									0.983	（3.320）^***	?0.009	（?3.16）^***