热带地理

热带地理 ›› 2018, Vol. 38 ›› Issue (6): 771-778.doi: 10.13284/j.cnki.rddl.003086

• 论文 • 上一篇    下一篇

大数据视角下中国城市旅游交通满意度的空间分异特征及影响因素

曹小曙，刘 丹   

  1. （中山大学 地理科学与规划学院，广州 510275）
  • 出版日期:2018-11-30 发布日期:2018-11-30
  • 通讯作者: 刘丹（1994—），女，河南人，硕士研究生，主要研究方向为旅游交通与旅游减贫，（E-mail）liud69@mail2.sysu.edu.cn。
  • 作者简介:曹小曙（1970—），男，甘肃人，教授，博导，博士，主要从事地理与规划研究，（E-mail）caoxsh@mail.sysu.edu.cn；
  • 基金资助:
    国家自然科学基金项目（41671160）

Spatial Differentiation of Urban Tourism Satisfaction in China Based on Tourism Big Data

CAO Xiaoshu, LIU Dan   

  1. ( School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China)
  • Online:2018-11-30 Published:2018-11-30

PDF (PC)

329

赞

摘要： 抓取网络旅游评论，运用文本分析技术判断每条评论的情感倾向，计算每个城市的旅游交通游客满意度。通过地理探测器及相关分析，探究城市旅游交通满意度的空间分异特征及其影响因素。研究表明：1）我国大陆地区城市旅游交通的游客满意度，在区域尺度上差异不显著，省域及市域尺度则差异显著。2）市域旅游交通满意度的空间差异主要受交通发展水平的影响。3）城市旅游交通满意度与城市拥堵指数呈负相关，与城市道路密度呈正相关，与有无地铁、高铁和民航机场等因素无明显相关关系。因此，受城市交通拥堵的影响，往往大城市、特大城市的游客交通满意度不高。4）根据城市旅游交通满意度和交通发展水平，将全国城市分为4个类别：A类为双指标中水平均衡发展区，B类为双指标低水平均衡发展区，C类为旅游交通满意度优先发展区，D类为旅游交通满意度滞后发展区。

关键词: 旅游交通, 满意度, 大数据, 地理探测器, 空间分异

Abstract: The unique nature of tourism activities determines that tourism cannot leave traffic alone, especially urban tourism, and the choice of more ways of transportation makes it possible for urban self-help tourism. Tourism traffic is also important for the sustainable development of urban tourism. Satisfaction of tourism traffic is an important factor to determine the overall satisfaction of the destination, and can significantly affect the willingness of tourists to revisit. Investigation and research to that can guide the construction and improvement of urban tourism traffic, and promote the development of urban tourism. Compared with the traditional questionnaire data, the use of large tourist data to study tourist traffic satisfaction can solve the problems of small research area and inaccurate sampling of data. This method can reflect the satisfaction of tourism traffic in a large area, and the difference in the small area, which is of great significance for the planning and development of tourism traffic. This paper, through the screening of the captured network tourism reviews, uses text analysis techniques such as word matching and emotion discrimination to judge the emotional tendency of each comment, and constructs the emotional index of each city to represent its non-negative rating through the model, which is the tourist satisfaction. Finally, we use geodetector and correlation analysis to explore the spatial differentiation of urban tourism traffic satisfaction and the mechanism that influences its differentiation. The research shows that: 1) The tourist satisfaction degree of urban tourism traffic in mainland China has little difference in the region, and the difference is significant between provinces and cities. 2) The spatial difference of urban tourism traffic evaluation is mainly affected by the level of transport development. 3) There is a negative correlation between urban tourism traffic satisfaction and urban congestion index, and there is a positive correlation with urban road density, and there is no significant correlation with the factors such as the subway and the civil aviation airport. Therefore, due to the impact of urban traffic congestion, the traffic satisfaction of big cities and megacities is not high. 4) According to the satisfaction of urban tourism traffic and the level of traffic development, the national cities are divided into 4 categories: the A category is double index medium level Balanced Development Zone, the B category is double index low level Balanced Development Zone, the C category is the priority development zone of tourist traffic satisfaction, and the D category is the lagging development zone of tourist traffic satisfaction.

Key words: tourist traffic, satisfaction, tourism big data, Geodetector, spatial differentiation