摘要
以2013—2022年我国30个省份的面板数据为研究对象,基于熵值法测度并运用核密度估计、修正引力模型、社会网络分析方法、QAP模型探究数字物流空间关联的网络结构特征及驱动因素。研究结果表明,我国各省份均存在于整个空间关联网络中,展现出稳定且复杂的空间关联关系,但整体的空间关联性较低,省份间数字物流的交流协作仍有很大发展空间;数字物流空间关联网络的“马太效应”显现,东部地区省份充分发挥着领头作用和中介作用,中西部地区省份处于关联网络的边缘位置;数字物流空间关联网络形成4大板块,各板块内部“俱乐部”效应明显;地理距离、财政支持水平、科技创新水平、对外开放程度差异矩阵对数字物流空间关联网络的形成有显著影响,而经济发展水平和社会消费水平差异矩阵对网络的形成效果甚微。
Taking the panel data of 30 Chinese provinces as research objects and based on the entropy method,this paper examined the characteristics of network structures associated with digital logistics space and its driving factors using kernel density estimation,modified gravity model,social network analysis,and QAP model.The results show that all Chinese provinces exist in the whole spatial correlation network,showing stable and complex spatial correlation relationships.However,the overall spatial correlation is low,and there is still a lot of room for the development of communication and collaboration in digital logistics among provinces.The spatial correlation network of digital logistics exhibits a significant“Matthew effect”,with the eastern provinces playing a prominent and intermediary role and central and western provinces in a peripheral situation.The digital logistics spatial association network involves four major segments,with an obvious“club”effect existing in each segment.The matrices of geographic distance,financial support,scientific and technological innovation,and openness to the outside world strongly affect the formation of digital logistics spatial correlation networks.However,the matrices of economic development and social consumption have little effect on the formation of these networks.
作者
李元豪
钱昭英
LI Yuanhao;QIAN Zhaoying(School of Management Science and Engineering,Guizhou University of Finance and Economics,Guiyang 550025,Guizhou,China;School of Economics,Guizhou University of Finance and Economics,Guiyang 550025,Guizhou,China)
出处
《铁道运输与经济》
北大核心
2025年第2期35-44,67,共11页
Railway Transport and Economy
基金
贵州省哲学社会科学规划课题(22GZYB19)。
关键词
数字物流
空间关联网络
修正引力模型
社会网络分析
驱动因素
Digital Logistics
Spatial Association Network
Modified Gravity Model
Social Network Analysis
Driving Factor
作者简介
通信作者:钱昭英(1984-),女,四川遂宁人,贵州财经大学经济学院副教授。
