检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:汪增洋[1] 孙晓宇 WANG Zeng-yang;SUN Xiao-yu(School of Economics,Anhui University of Finance and Economics,Bengbu,Anhui,233030,China)
出 处:《新疆师范大学学报(自然科学版)》2023年第2期1-8,17,共9页Journal of Xinjiang Normal University(Natural Sciences Edition)
基 金:国家社会科学基金项目(22BJL066);安徽省高校科学研究项目(SK2020A0001);安徽省社科规划项目(AHSKY2020D35);安徽财经大学研究生科研创新基金项目(ACYC2022421)。
摘 要:文章基于合肥都市圈企业微观大数据,从乡镇尺度分析2005—2019年制造业与生产性服务业企业时空分布演变,探究二者的空间关联特征。研究发现:(1)制造业与生产性服务业空间分布表现为“多核+多点”和“单核+小据点”的空间特征;(2)制造业与生产性服务业呈现出显著的集聚特征,但集聚水平有所不同;(3)制造业与生产性服务业企业分布存在空间关联性,与传统生产性服务业空间关联度较高,与高端生产性服务业空间关联度相对较低。Based on the micro big data of enterprises in Hefei metropolitan area,the spatial and temporal distribution evolution of manufacturing and productive service enterprises from 2005 to 2019 was analyzed from the township scale,and the spatial correlation characteristics of them were explored.It is found that:(1)The spatial distribution of manufacturing and productive service industries is characterized by the spatial characteristics of"multi-core+multi-point"and"single-core+small base".(2)Manufacturing and productive service industries show significant agglomeration characteristics,but the agglomeration level is different.(3)There is a spatial correlation between the distribution of manufacturing and productive service industries,which is relatively high in spatial correlation with traditional productive service industries and relatively low with high-end productive service industries.
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.147