主管单位:中国科学技术协会
主办单位:中国地理学会
承办单位:华东师范大学

世界地理研究 ›› 2017, Vol. 26 ›› Issue (6): 165-174.

• 文化与社会 • 上一篇    

福建省自驾入游流市场及网络结构特征研究

赵伟,李蕊蕊,闫景丽   

  1. 泉州师范学院
  • 收稿日期:2017-04-03 修回日期:2017-08-18 出版日期:2017-12-15 发布日期:2017-12-13
  • 通讯作者: 李蕊蕊
  • 基金资助:

    福建省教育厅2016年度中青年项目;泉州市社科联项目

The Geographical Distribution and Network Structure of Self-driving Tourist Flow in Fujian Province

  • Received:2017-04-03 Revised:2017-08-18 Online:2017-12-15 Published:2017-12-13

摘要: 以网络游记数据挖掘为基础,综合运用社会网络分析方法、GIS制图和数理统计技术,揭示福建省自驾入游流市场及网络结构特征。市场特征为:出游高峰期与低谷期年内交替四次,呈现明显的双“M”型,高峰期与我国“长假”时间高度吻合;结伴方式以夫妻、亲子、带父母的家庭出游方式为主(占60.1%),其次为亲朋好友(占27.1%);88.18%的自驾游客在福建省内停留时间不超过6天,其中逗留3天(占23.15%)的比例最高;自驾游省外客源市场结构呈现明显的近地域性和沿海发达省份和城市的高度集中性;自驾游单程公路里程空间使用曲线具有较为典型的Boltzman曲线特点,一、二级客源市场范围单程公路里程分别为0-800km和800-1400km,1400km以外为三级客源市场。网络结构特征为:网络节点地位呈现较强的不均衡性,两级分化明显,核心节点之间的互动频率远高于边缘节点;整体上看,福建省自驾入游流空间等级序列明显,核心区和重要区域所占比例偏小,空间分布呈现“整体分散、局部集中”的格局,旅游流集中于思明区、南靖县、鼓楼区、永定县、武夷山市等高级别景区所在的区域。

Abstract: Using social network analysis method, the paper studies the geographical distribution and network structure of self-driving tourist flow in Fujian province. It can be concluded as follows from the market characteristic. (1) Peak and trough of tourist season alternate four times in a year, showing M model, especially peak seasons achieve a high level compliance with Chinses long holiday. (2) The travel models mainly between couples , parent-child and parents account for 60.1%,secondly relatives and friends accounting for 27.1%. (3)88.18% self-driving tourists stay in Fujian province less than 6 days, of which 3 days accounting for 23.15%. (4) Self-driving tourist market present an adjacent character, a clear character for eastbound development and the character concentrated on the cities.(5) The tourism special use curve of self-driving is consistent with curves of Boltzman. The number of tourists increase with distance and peaks at 800km, then the number of tourist shows a rapid decrease. On the whole, its gravity field concentrates on the scope of 1400km, and the accumulation percentage of tourists reaches 87%. Spatial characteristic of self-driving tourist network into Fujian province are shown in the following: (1) The status of network node present the inequality, the polarization between core nodes and periphery ones has been clear. (2) The spatial distribution of nodes is featured by weak concentration and strong dispersion, while the nodes of core region and primary region account for less. (3)On the whole, it is quite clear of the self-driving tourist flow hierarchical order , the self-driving tourist flow concentrates on higher scenic which located such as Siming District, Nanjing County, and Gulou District etc.

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