Приграничный туризм на российско-китайской границе в 2014 – 2019 гг.

Елена Викторовна Михайлова
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Abstract

The article examines the dynamics of cross-border tourism and developments in the tourism industry in the Russian-Chinese borderland after 2014. Using Blagoveshchensk and Heihe and Khabarovsk and Fuyuan as case studies, the article shows that due to the change in tourist flow structure after the 2014-ruble depreciation, Russian and Chinese border cities have customized their service industry to accommodate Chinese tourists. Mapping of the service sector openness of border cities conducted based on fieldwork data and media materials demonstrates that central districts of border towns concentrate the majority of businesses catering to clients from the neighboring state. This conclusion confirms the role of central districts of border towns as thermometers of cross-border dynamics as they react first to fluctuations in exchange rates and tourist flows. The article provides an overview of the impact of the COVID-19 pandemic on cross-border flows and the tourism industry in the Russian-Chinese borderland and concludes that the earlier reorientation towards domestic tourists allowed Heihe and Fuyuan to be better prepared for a new external shock. The tourism industry in Blagoveshchensk and Khabarovsk, on the contrary, suffered significant losses and found itself in a situation of high uncertainty, where it is hardly possible to predict when Chinese tourists will return. © 2021 The authors.
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2014年至2019年,中俄边境旅游业。
本文考察了2014年后中俄边境地区跨境旅游的动态和旅游业的发展。本文以布拉戈维申斯克和黑河、哈巴罗夫斯克和抚远为例,发现2014年卢布贬值后,由于旅游流结构的变化,俄罗斯和中国边境城市的服务业都进行了定制,以适应中国游客。根据实地调查数据和媒体资料绘制的边境城市服务业开放度地图显示,边境城镇中心区集中了大部分面向邻国客户的企业。这一结论证实了边境城镇中心区作为跨境动态温度计的作用,因为它们首先对汇率波动和游客流量作出反应。文章概述了COVID-19大流行对中俄边境跨境流动和旅游业的影响,并得出结论认为,较早的国内游客重新定位使黑河和抚远能够更好地应对新的外部冲击。相反,布拉戈维申斯克和哈巴罗夫斯克的旅游业遭受了重大损失,并发现自己处于高度不确定性的境地,几乎无法预测中国游客何时会回来。©2021作者。
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来源期刊
Izvestiya Rossiiskoi Akademii Nauk. Seriya Geograficheskaya
Izvestiya Rossiiskoi Akademii Nauk. Seriya Geograficheskaya Social Sciences-Geography, Planning and Development
CiteScore
1.10
自引率
0.00%
发文量
11
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