摘要
区域物流辐射网络特征提取能够为物流规划提供重要依据.本文针对传统物流辐射网络特征提取方法的不足,考虑物流资源分布、物流企业集聚等实际影响因素,基于多源数据从实际和潜在辐射能力的双重视角,引入物流资源辐射因子、HHI指数构建城市物流辐射网络,并与空间运输联系格局进行匹配分析,建立了系统的区域物流辐射网络特征提取方法.以云南省为实例,验证了网络构建方法的有效性,结果表明:大理的核心地位逐渐凸显,与昆明形成"双中心格局";昆明对与其邻近的玉溪、曲靖具有空间剥夺效应;物流资源分布差异对节点辐射能力的影响明显; HHI指数是区域物流辐射网络较为敏感的因素;云南省物流节点的辐射能力差异显著.
Regional logistics radiation network feature can provide important basis for logistics planning. This paper aimed at insufficiency of the characteristics analysis method of traditional logistics radiation network,considering the actual impact factors: the logistics resource distribution and logistics enterprise agglomeration. Based on multi-source data and the introduction of logistics resource radiation factor and HHI index,extraction methods for regional logistics radiation network were proposed from the dual perspectives of actual radiation capability and potential radiation capability,and the transportation linkage pattern was matched analysis. Yunnan province is taken as an example,verifying the efficiency of this paper proposed feature extraction method,and the results show that: the core position of Dali gradually highlights,and forms"double center pattern"with Kunming;Kunming has spatial deprivation effect on Yuxi and Qujing;the difference of logistics resource distribution has obvious influence on the radiation capability of the nodes;HHI index is the regional logistics radiation network is more sensitive factor;the differentiation characteristics are significant in radiation capability of logistics nodes.
作者
戢晓峰
陈肖雨
伍景琼
刘小兰
JI Xiaofeng;CHEN Xiaoyu;WU Jingqiong;LIU Xiaolan(Faculty of Traffic Engineering,Kun mi ng University of Science and Technology,Kunming 650504,China;Yunnan Modem Logistics Engineering Research Center,Kunming University of Science and Technology,Kunming 650504,China)
出处
《昆明理工大学学报（自然科学版）》
CAS
北大核心
2019年第1期113-121,共9页
Journal of Kunming University of Science and Technology(Natural Science)
基金
云南省交通科技创新示范项目(2017A14)
关键词
物流辐射网络
特征提取
多源数据
城市物流
物流资源辐射因子
logistics radiation network
feature extraction
multi-source data
urban logistics
logistics resource radiation factor
