中国主要城市旅游要素网络关注空间演化特征  

Evolution characteristics of 24 major cities' network attention degree of six elements of tourism in China

作　　者：汪秋菊[1] 刘宇[1] 李新[1] 张斌儒[1] 张驰[1] WANG Qiu-ju;LIU Yu;LI Xin;ZHANG Bin-ru;ZHANG Chi(Tourism Institute of Beijing Union University, Beijing 100101,China)

机构地区：[1]北京联合大学旅游学院,北京100101

出　　处：《世界地理研究》2017年第1期45-55,共11页World Regional Studies

基　　金：国家自然科学基金项目(71373023);北京市教育委员会面上项目(KM201611417003);北京市属高校高层次引进与培养计划项目(CIT&TCD201404079)

摘　　要：旅游要素发展水平是衡量旅游产业成熟程度的重要标志。通过建立旅游"六要素"搜索关键词选取、搜索数据剥离及合成的技术方法,结合2011-2015年我国24个主要城市旅游要素网络关注度数据,采用变差系数、赫芬达尔系数等指标和标准差椭圆方法,分析城市旅游要素的网络关注指数空间演化特征。结果表明:2011至2015年,"吃、住、行、娱"四要素网络关注指数城市差异呈"V"字趋势波动,"购"要素差异越来越大,"游"要素差异则越来越小;旅游"六要素"网络关注指数的赫芬达尔系数变化不大,各城市度集聚程度低,关注较为分散;旅游"六要素"网络关注指数在空间扩展上具有极大相似性,呈现出东北—西南格局,向正东—正西方向转变的趋势。但"吃、住、行、购"等旅游要素网络关注指数标准差椭圆的中心呈现向西南偏移的趋势,而"游、娱"旅游要素则呈现出向东北偏移的趋势。In this article, search query data of tourism element of 24 major cities in China is processed, using technical methods for keywords of tourism elements selecting, search query data mining and stripping. Entropy method is used to integrate comprehensive index of search query data to analyze network attention-degree of the cities. Combined with Coefficient of Variation,Herfindahl Index, and standard deviation ellipse method, the evolution of the spatial pattern of urban tourism elements be explored from 2011 to 2015. This article draws a conclusion that ‘Meals, lodging, travel, shopping, tour and entertainment’have different degrees of attractiveness. Coefficient of Variation of ‘Meals, lodging, travel, entertainment’ shows fluctuation of “V”shape. Shopping’s is getting larger and larger, but tour’s is getting smaller and smaller. Although the evolution of the spatial pattern has some similarities,the standard deviation ellipse which be acquired by using the search query data of‘Meals, lodging, travel, shopping’offset towards southwest, and of‘travel, entertainment’is showing a shift northeast.

关 键 词：旅游要素 百度指数 熵值法 标准差椭圆 

分 类 号：F592.7[经济管理—旅游管理]