摘要
拓展入境旅游外国市场是我国入境旅游业发展面临的重要任务之一。应用地图法研究了入境外国旅游流网络空间分布特征,应用社会网络分析法和复杂网络理论研究了该网络的性质和结构特征,结果表明:1)入境外国旅游流在中国的空间分布范围大且不均衡,形成了两个"金三角",四个"银三角"和两个集中分布区。2)入境外国旅游流网络是无标度网络,网络中核心节点少,边缘节点多,核心节点的稳定和发展对全国入境旅游业的稳定和发展起重要的支撑和保障作用。3)网络中的节点可分为口岸、枢纽、中转、复合型等四种类型,分别发挥着旅游流出入境口岸、集聚和扩散、中转、多种功能复合等作用。4)入境外国旅游流在少数核心城市间转移和扩散,能大规模吸引和组织入境外国旅游流的目的地数量较少。
It＇s an important mission to expand the inbound foreigner tourism market for China in the future. Based on 2687 questionnaires from 9 hot destination cities in China mainland, the spatial distributional pattern was studied by drawing tourist flows maps. The rules and roles of the destination cities in China inbound foreigner tourist flow network composed with 116 destination cities was researched using the Social Network Analysis and Complex Network Theory. Four conclusions are put forward ： ①The distribution scope of inbound foreigner tourist flows is big but uneven because the inbound foreigner tourist flows are concentrated in two gold triangles, four Argentine triangles and two concentration regions.②The inbound foreigner tourist flow network is scale - free network with few core nodes that play crucial roles in sustainable and stable development of China inbound tourism industry and many edge nodes.③The nodes can be classified into four types ： Gateway, Hub, Stopover, and Multiple functions. The inbound foreigner tourist flow entering or departing China from the Gateway Nodes, centralizing and diffusing in or from the Hub Nodes, transferring from one destination to another by the Stopover Nodes, some nodes play as Gateway, Hub, or Stopover together. ④The centralizing and diffusing of the inbound China foreigner tourism flows only happened in several core destination cities. The number of destination nodes that can concentrate a large amount of tourist flows are fewer.
出处
《干旱区资源与环境》
CSSCI
CSCD
北大核心
2014年第7期177-182,共6页
Journal of Arid Land Resources and Environment
基金
国家自然科学基金项目(编号:41071090)
新世纪优秀人才支持计划(编号:NCET 110673)资助
关键词
入境外国旅游流
旅游流网络
社会网络分析法
复杂网络理论
inbound foreigner tourist flow
tourist flow network
social network analysis
complex network theory
