An investigation of international tourist flow modelling during the pandemic

Lina Zhong, Sunny Sun, Rob Law and Baolin Deng

Current Issues in Tourism, 2022, vol. 25, issue 12, 1910-1919

Abstract: Infectious disease normally largely affects international tourist flow. For example, the novel coronavirus (COVID-19) outbreak has greatly affected global tourism, and its effect is expected to extend further. As the first country in the world to detect the pandemic, how the international tourist flow to Mainland China (hereafter known as China) changes along with the COVID-19 outbreak is still underexplored. To bridge this research gap, this study identifies the changes in the international tourist flows to China by categorizing international tourists to seven regions of the world and examines the degree of sensitivity among five clustered groups through Python modelling. Findings show that the international tourist flows from Europe, Asia Pacific and North America to China were largely affected by the COVID-19 outbreak. In addition, different sensitivity levels of the five identified clusters among the 193 countries affected by infectious disease ranged from ‘least sensitive’ to ‘most sensitive’. Practical implications are further discussed.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/13683500.2021.1972941 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:rcitxx:v:25:y:2022:i:12:p:1910-1919

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/rcit20

DOI: 10.1080/13683500.2021.1972941

Access Statistics for this article

Current Issues in Tourism is currently edited by Jennifer Tunstall

More articles in Current Issues in Tourism from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().