地理学报 ›› 2007, Vol. 62 ›› Issue (6): 609-620.doi: 10.11821/xb200706006

• 旅游地理 • 上一篇    下一篇

南京市旅游流网络结构构建

杨兴柱1,3, 顾朝林2, 王群3   

  1. 1. 南京大学城市与区域规划系, 南京210093;
    2. 清华大学建筑学院城市规划系, 北京100084;
    3. 安徽师范大学旅游学院, 芜湖241000
  • 收稿日期:2006-07-17 修回日期:2006-12-29 出版日期:2007-06-25 发布日期:2010-08-04
  • 作者简介:杨兴柱(1977-), 男, 安徽六安人, 博士生。主要从事旅游地理与旅游规划研究。E-mail: yxzlv@163.com
  • 基金资助:

    国家自然科学基金重点项目(40435013);安徽省高校青年教师科研资助计划项目(2006jql053)

Urban Tour ism Flow Network Structure Construction in Nanjing

YANG Xingzhu1,3, GU Chaolin2, WANG Qun3   

  1. 1. Department of Urban and Resources Sciences, Nanjing University, Nanjing 210093, China;
    2. Department of City Planning, School of Architecture, Tsinghua University, Beijing 100084, China;
    3. College of Tourism, Anhui Normal University, Wuhu 241000, China
  • Received:2006-07-17 Revised:2006-12-29 Online:2007-06-25 Published:2010-08-04
  • Supported by:

    Key Project of National Natural Science Foundation of China, No.40435013; Youth Teacher Sponsored Scheme Foundation of Anhui Province, No.2006jql053

摘要:

借助社会网络理论和方法, 研究了城市旅游流网络结构特征、城市旅游流网络结构评价指标体系, 并对南京市旅游流网络结构进行了实证分析。南京市旅游空间网络中, 所选取 的16 个旅游节点中平均每个旅游节点与5.19 个其他节点存在着旅游流集聚与辐射联系; 平均每个旅游节点充当旅游流中介者次数为6.07, 旅游节点之间距离相互联系比较紧密。但各旅游节点之间分布不十分均衡, 夫子庙秦淮风光带、钟山风景区、新街口、总统府、侵华日军南京大屠杀纪念馆等处于核心点, 旅游网络中集聚和辐射功能都很强, 且结构洞水平较高, 拥有更多的竞争机会和非替代性区位优势, 但可能会造成严重的旅游流瓶颈问题。南京市旅游空间网络密度不是很高(0.35), 旅游空间网络中存在着明显的结构分层, 其中共有7 个旅游节点成为核心区的成员, 核心区内部成员间联结密度达0.81, 形成了强中心线型结构。同时, 根据Dianne Dredge 提出的旅游目的地3 种空间结构模型, 结合南京市旅游空间网络结构特征, 判定了南京市城市旅游空间发展阶段及布局模式为发展阶段的多节点布局模式。最后, 指出了旅游流网络结构构建和评价中存在的问题以及在城市旅游可持续发展研究中的应用前景。

关键词: 城市旅游, 社会网络理论, 旅游流网络结构, 南京市

Abstract:

This study presents a quantitative method for investigating the network characteristics of urban tourism by the network analysis, which offers numerous techniques and indicators through measuring the links among nodes to demonstrate the structural patterns of connected systems. The indicators measuring network analysis include centrality, structural holes, size, density, centralization, diameter of tourism network and core-periphery model. Then, this article empirically tested a sample of urban tourists taken from 16 tourism nodes in Nanjing city. For every tourism node, there is tourist centralization and decentralization link with 5.19 other nodes in average. Averagely, every tourism node acts as intermediary number of times being 6.07. Mutual connection is comparatively intense between the tourism nodes. But, distribution is somewhat uneven between every tourism node. Qinhuai Scenic Zones, Zhongshan Hill Scenic Area, Xinjiekou tourism district, Presidential Palace Scenic Area, the Memorial Hall of the Vicitims in Nanjing Massacre by Japanese invaders lie in core. These nodes have high level of structural holes, which are situated in non-substitutable locations with connections spanning different sub-groups of nodes and with opportunities to broker the flow of tourists among other nodes. However, they are likely to cause a severe bottleneck of tourist flows. In all, density of tourism network is not very high (0.35), there being obvious stratified structure. Density between tourism nodes in the inside of the core area has reached 0.81, having formed the strong centre-line-type structure. Based on the structural characteristics relating to its network position on various touring routes, this article suggests the appropriate tourist facilities and services of each particular destination. Finally, according to Dianne Dredge's (1999) tourism location theory, Nanjing urban tourism structure belongs to multi-nodes location modeling and development stage.

Key words: urban tourism, tourism flow network, social network, Nanjing city