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作 者:吴姗姗 王录仓[1] 刘海洋 WU Shanshan;WANG Lucang;LIU Haiyang(College of Geography and Environmental Science,Northwest Normal University,Lanzhou 730070,Gansu,China)
机构地区:[1]西北师范大学地理与环境科学学院,中国甘肃兰州730070
出 处:《经济地理》2020年第10期202-212,共11页Economic Geography
基 金:国家自然科学基金项目(41261042)。
摘 要:文章以黄河流域68个地级市(州、盟)为研究区域,运用社会网络分析法对旅游流(总量、汽车、火车、飞机)网络结构特征及其分异机制进行了分析。结果表明:①各节点城市的中心性在三种中心度下表现出明显差异,省会城市和典型旅游城市的中心性明显高于一般城市;除飞机路径网络外,其余网络中各节点城市的中心性相对一致。②旅游流网络整体呈"大松散、小聚簇"结构特征,形成以省会城市为核心的旅游流子网,中下游地区子网众多,上游地区的子网相对稀疏,省际接壤区几乎没有成形的子网;核心—边缘特征明显,核心区对边缘区的"涓滴效应"有限。③网络结构洞水平在四种网络中差异显著,西安、郑州等核心城市表现出强大的桥梁纽带作用。④旅游流流量分配的不均衡性、流向的非对称性及其不同网络的连通性差异共同塑造了网络结构。In this paper,68 prefecture-level cities(states and leagues)in the Yellow River Basin are taken as research areas,and the social network analysis method is used to analyze the network structure characteristics and differentiation mechanisms of tourism flows(gross path,car path,train path and airplane path).The results show that 1)the centrality of each node city shows obvious difference under three centrality degrees.The centrality of provincial capitals and typical tourism urban are higher than ordinary cities.In addition to the airplane path network,the centrality of each node city in the other networks is relatively consistent.2)The overall network structure is characterized by"large loose and small clusters",forming sub-networks with provincial capitals as its core.There are many sub-networks in the middle and lower basin,the sub-networks in the upper basin are relatively sparse,and there are almost no formed sub-networks in the interprovincial border areas.The network feature of four paths clearly match the core-edge model,but the"trickle effect"is limited.3)The level of structural holes of each node city shows significant difference among the four networks.Core cities which show strong bridge links are Xi’an,Zhengzhou,et al.4)The network structure is shaped by the uneven distribution of tourism flow,the asymmetry of flow direction and the connectivity difference of different networks.
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