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外向在线旅游信息流与入境旅游流的耦合分析——以美加入境旅游流为例 被引量:43

A Couple Analysis of the Extraversion Online Tourism Information and Inbound Tourist Flow:A Case of the American and Canadian Inbound Tourist Flow
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摘要 随着互联网在旅游中的应用不断增多,很多旅游目的地逐渐重视网络营销,以期吸引更多的游客。为了探讨区域旅游流对在线旅游信息的响应,文章提出了外向在线旅游信息流概念,并以美国和加拿大的15大旅游网站作为研究样本,通过文本挖掘方法,测度出了中国城市的外向在线旅游信息指数。通过统计数据分析美加来华游客入境旅游流偏好值,探讨我国城市外向在线旅游信息流与入境旅游流之间的耦合关系。研究发现,外向在线旅游信息流指数较高的中国城市在国际上都有较高的知名度,且旅游资源禀赋高;美加来华旅游者主要集中前往中国东部地区;我国城市外向在线旅游信息流与入境旅游流之间的耦合关系表现出4种形态。结果表明,由于经济发展水平、对外开放程度等因素的影响,外向在线旅游信息流与入境旅游流之间并非直接的对应关系。 The lnternet is increasingly being used in the tourism industry. Many tourist destinations pay attention to the Internet marketing so as to attract more tourists. In order to explore the regional tourism flow responding to the Internet information, this study proposes the concept of extraversion online tourism information flow, which means that the tourism information provided by the online tourism websites and relates to the specific destinations or areas is transmitted and exchanged between one website and other websites or among the information receivers. Taking 15 American and Canadian tourism websites as research samples, this study measured the index of extraversion online tourism information of Chinese cities using text mining method. Besides, we also measured the preferred value of inbound tourism flow from America and Canada by using the data from the Year Book of China Tourism Statistics. Finally, we analyzed the coupling relationship about the extraversion online tourism information and the inbound tourist Flow. We came to the following American and Canadian tourism conclusions. (1) The cities with websites were mainly those which more comprehensive information on enjoyed high popularity in the world, and had better natural endowment on the tourist resources, such as Beijing, Shanghai, Shenzhen, Qingdao, Tianjin or Xiamen in the eastern region and Guilin, Guiyang, and Xi'an in western region. (2) The inbound tourists from America and Canada mainly concentrated on the eastern region of China. The number of tourist arrivals of Shanghai, Beijing, Guangzhou and Shenzhen accounts for more than half of the whole number. The reason may be that the eastern region of China not only has a strong economic base, but also has a close trade relationship with the America and Canada. (3) It was found that there are four forms of the coupling relationship about the extraversion online tourism information and the inbound tourist flow shows: high - coupled (Beijing, Shanghai and Wuhan) , middle - coupled (Guangzhou, Taiyuan, Shenzhen, Lanzhou, Lhasa, Hangzhou, Suzhou, and Urumqi) , low - coupled (Dalian, Zhengzhou, Guiyang, Harbin, Yinchuan, Datong, Xining, Huangshan, and Kunming) and the in - consistent type (Chongqing, Qingdao, Xiamen, Chengdu, Guilin, Tianjin, Xi' an and Nanjing). (4) According to the study of the urban spatial distribution of different coupling types, we found that: high - coupled region include Beijing (the capital city of China), Wuhan that is located in the central China as well as Shanghai, the economic center of China ; middle - coupled region consists of both economically developed and economically developing regions; the distribution of low - coupled region is scattered relatively; the in - consistent type region contains Chongqing and Chengdu in the southwest China, Xi' an in the northwest China, Nanjing in the east China, Tianjin, Qingdao in the northern China and Xiamen, Guilin in the southern China. In a word, the relationship between the extraversion online tourism information and the inbound tourist flow is not simply one to one correspondence due to the difference of the economic development, the level of opening and so on. Therefore, each city should pay attention to the international propaganda so as to take some share in the international tourism market.
作者 冯娜 李君轶
出处 《旅游学刊》 CSSCI 2014年第4期79-86,共8页 Tourism Tribune
基金 国家自然科学基金项目(41001077) 中国博士后科学基金特别资助项目(2012T50794)、中国博士后科学基金面上项目(2011M501429) 旅游业青年专家培养计划 陕西师范大学研究生培养创新基金(2013CXS015)联合资助~~
关键词 在线旅游信息 外向在线旅游信息指数 入境旅游流 偏好值 耦合 online tourist information extraversion online tourism information index inbound tourist flow preferences value couple analysis
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