Abstract:

Based on the data of 201 cities in 19 Chinese urban agglomerations mentioned in the outline of the 14th Five-Year Plan, this paper analyzed the spatial and temporal characteristics of the level of industrial collaborative agglomeration in urban agglomerations from 2006 to 2018 using ArcGIS spatial analysis model, spatial error model and other methods, and analyzed its influencing factors. The results show that: ①The level of coordinated agglomeration of the secondary and tertiary industries in Chinese urban agglomerations shows a trend of fluctuation and decline, in which the location entropy of the secondary industry decreases first and then increases, while the location entropy of the tertiary industry continues to decline slowly. ②The spatial pattern of collaborative agglomeration of the secondary and tertiary industries in China's urban agglomerations remained relatively stable. The urban agglomerations with a high level of industrial collaborative agglomeration are still mainly distributed in western China and coastal areas, while the level of industrial collaborative agglomeration in central China is relatively backward. ③There is a significant positive spatial correlation between the collaborative agglomeration level of the secondary and tertiary industries in Chinese urban agglomerations, and the overall trend of fluctuation decreases. The trend of industrial agglomeration in urban agglomerations gradually weakens, and the internal differences in urban agglomerations gradually increase. ④Based on the spatial error model, it is found that the urbanization level, government regulation and foreign investment intensity have a significant impact on the spatial distribution of the secondary and tertiary industries in Chinese urban agglomerations, while the intensity of science and technology expenditure has no significant impact. ⑤The development of industrial collaborative agglomeration needs to take measures according to local conditions. The urban agglomeration in eastern China should play a good role of government regulation to promote the coordinated division of labor within the urban agglomeration. The urban agglomeration in central and northeast China should promote the tertiary industry and ensure that the supporting service industry can adapt to the development of the secondary industry. Urban agglomeration in western China should try to raise its urbanization and improve the development of service industry.

Key words: industrial co-agglomeration, spatio-temporal characteristics, Spatial Econometric Model, urban agglomeration, location entropy

摘要：

以十四五规划纲要中提及的19个中国城市群共201个城市数据为样本，运用ArcGIS空间分析模型、空间误差模型等方法对城市群2006—2018年产业协同集聚水平的时空特征进行分析，并剖析其影响因素。结果表明：①中国城市群第二、三产业协同集聚水平总体呈现波动下降的态势，其中第二产业区位熵呈先降后升的趋势，第三产业区位熵则持续缓慢下降。②中国城市群第二、三产业协同集聚空间格局保持相对稳定，城市群产业协同集聚水平较高的城市群依旧主要分布于西部地区和沿海地区，而中部地区的产业协同集聚水平相对较为落后。③中国城市群第二、三产业协同集聚水平存在显著的空间正相关性，总体呈现波动下降趋势，集聚态势逐渐减弱、内部差异逐渐增大。④运用空间误差模型进行影响因素分析，发现城镇化、政府调控和外商投资强度对中国城市群第二、三产业协同集聚水平的空间布局影响较为显著，而科技支出强度的影响不显著。⑤产业协同集聚发展需因地制宜，东部地区城市群应发挥好政府的调控作用推动城市群内部的协调分工；中部和东北地区城市群应加快提升第三产业，确保其配套服务业能适应第二产业发展；西部城市群则应加强自身城镇化建设水平，保持产业协同集聚水平稳定上升。

关键词: 产业协同集聚, 时空特征, 空间计量模型, 城市群, 区位熵