中国城市群高质量发展的空间差异及驱动因素

Spatial Difference and Driving Factor of China Urban Agglomeration’s High-quality Development

城市群高质量发展作为“十四五”规划的重要内容,揭示其差异规律及驱动因素对新时代中国区域协调发展具有重要意义。基于城市群高质量发展的科学内涵构建评价指标体系,运用熵权法测度中国城市群高质量发展水平,利用Dagum基尼系数从总体、城市群内、城市群间视角考察其空间差异及来源,通过地理探测器进一步探究城市群高质量发展差异的驱动因素。研究发现:城市群高质量发展水平呈明显上升趋势,且存在显著的空间非均衡性,其中珠三角城市群水平最高;在样本期内,我国城市群高质量发展总体差异和城市群间差异呈平稳下降趋势,城市群内差异保持稳定,且城市群间差异贡献远大于城市群内差异贡献;总体、城市群内和城市群间的主要单驱动因素均为创新性、协调性和共享性,各交互驱动因素的作用强度普遍较高,与强单因素相关联的交互影响因子尤为突出。

The high-quality development of urban agglomerations is an important part of the“14th Five Year Plan”,and revealing its difference law and driving factors is of great significance for the coordinated regional development in China in the new era.Based on the scientific connotation of urban agglomerations’high-quality development,this study constructs an evaluation index system,measures the level of China urban agglomerations’high-quality development by adopting Entropy weight method,examines the spatial differences and their sources from the perspective of overall,intra-urban agglomerations and inter urban agglomerations by using Dagum Gini coefficient,and further explores the driving factors for the differences in urban agglomerations’high-quality development through geographic detector.It is found that the high-quality development level of urban agglomerations is showing a significant upward trend and there exists a significant spatial imbalance with the Pearl River Delta urban agglomerations having the highest level;during the sample period,the overall difference in high-quality development of China urban agglomerations and the differences between urban agglomerations show a steady downward trend,while the differences within urban agglomerations remain stable and the contribution of inter urban agglomeration difference is much greater than that of intra-urban agglomeration difference;and that the main single driving factors of overall,intra-urban agglomerations and inter urban agglomerations are all innovation,coordination and sharing,the effect intensity of each interactive driving factor is generally high,and the interactive influencing factors associated with strong single factors are particularly prominent.