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人文地理  2013, Vol. 28 Issue (3): 142-147    DOI: 10.13959/j.issn.1003-2398.2013.03.021
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中国重点城市入境旅游空间关联网络特征及优化
王永明1,2, 马耀峰3, 王美霞2
1. 吉首大学 生态旅游湖南省重点实验室, 吉首 416000;
2. 吉首大学 商学院, 吉首 416000;
3. 陕西师范大学 旅游与环境学院, 西安 710062
STUDY ON STRUCTURE AND OPTIMIZATION OF INBOUND TOURISM NETWORK OF KEY CITIES IN CHINA
WANG Yong-ming1,2, MA Yao-feng3, WANG Mei-xia2
1. Eco-tourism Key laboratory of Jishou University, Jishou 416000, China;
2. Business School of Jishou University, Jishou 416000, China;
3. College of Tourism and Environment, Shaanxi Normal University, Xi'an 710062, China

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摘要 基于社会网络分析方法论视角,研究了中国12个重点城市入境旅游空间网络的节点结构特征和整体结构特征,并提出了旅游空间网络结构优化相关策略。结果发现:(1)重点城市入境旅游网络节点间共有46对旅游流联系,每个节点平均与其它3.83个节点存在着旅游流集聚和扩散联系,且充当旅游网络中介者角色的平均次数为8.25次;(2)北京和上海在入境旅游空间网络中居核心地位,西安、广州和杭州居次核心,其余城市的网络地位较低;(3)重点城市入境旅游的整体网络密度较低,不均衡性较明显。最后,提出优化重点城市入境旅游网络结构的相关策略。
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关键词 旅游网络空间结构社会网络分析重点城市    
Abstract:Inbound tourism is an important component of tourism industry, which plays an import role in whole tourism development in China. Inbound tourists have different travel characteristics from domestic tourists, one of which is that inbound tourists often travel for a long haul to different key cities in destination country. These key cities are always famous for their scenic resorts, human heritage sites, or convenient transport conditions. This network structure has a significant effect on inbound tourism industry development of key cites, even on their background areas. In addition, significantly different from network based on transport relation, network structure based on inbound tourist flows can objectively reflect spatial relation between key cities and behavior feature of inbound tourists. But there are very few literatures searching on network structure of key cities and its optimization strategies. Based on development level and spatial pattern of inbound tourism industry of different cities in China, this paper firstly selects out twelve key cities in China, then studies network structure feature of inbound tourism of key cities, including node structure feature and whole network structure feature using indexes of centrality, centralization, density and structure hole of social network analysis. The results imply that tourism network of China's key city nodes have a total 46 pairs of tourism flow relations. Each node has relationship of tourist flow concentration and diffusion with other 3.83 nodes, and the number of being an agent in the tourism network is 8.25.
Key wordstourism network    spatial structure    SNA    key cities   
收稿日期: 2011-12-29     
基金资助:

国家自然科学基金项目(40771058;41271158);湖南省哲学社会科学基金项目(11JL09;12YBA261);吉首大学生态旅游湖南省重点实验室开放基金资助项目(JDSTLY201210)

作者简介: 王永明(1984-),男,安徽阜阳人,硕士,助教,主要研究方向为旅游者行为和旅游影响。E-mail:wym85727@163.com。
引用本文:   
王永明, 马耀峰, 王美霞. 中国重点城市入境旅游空间关联网络特征及优化[J]. 人文地理, 2013, 28(3): 142-147. WANG Yong-ming, MA Yao-feng, WANG Mei-xia. STUDY ON STRUCTURE AND OPTIMIZATION OF INBOUND TOURISM NETWORK OF KEY CITIES IN CHINA. HUMAN GEOGRAPHY, 2013, 28(3): 142-147.
链接本文:  
http://rwdl.xisu.edu.cn/CN/10.13959/j.issn.1003-2398.2013.03.021      或     http://rwdl.xisu.edu.cn/CN/Y2013/V28/I3/142
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