Identifying Tourism Patterns in Post-Pandemic South Korea : Insights from Social Network Analysis

This study aims to analyze the typical characteristics of regions preferred as tourism destinations in the post-pandemic era and examine the effects of the pandemic on people’s tourism behavior. Utilizing the origin-destination (O-D) data captured by South Korea’s toll collection system (TCS) betwee...

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Vydáno v:Journal of Korea Planning Association Ročník 59; číslo 2; s. 19 - 29
Hlavní autoři: Park, Mir, Seo, Ducksu
Médium: Journal Article
Jazyk:angličtina
Vydáno: 대한국토·도시계획학회 30.04.2024
Témata:
공학일반
Social Network Analysis
Tourism
Pandemic
South Korea
OD Data
ISSN:1226-7147, 2383-9171
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Abstract This study aims to analyze the typical characteristics of regions preferred as tourism destinations in the post-pandemic era and examine the effects of the pandemic on people’s tourism behavior. Utilizing the origin-destination (O-D) data captured by South Korea’s toll collection system (TCS) between 2019 and 2021, the research explores differences in tourism behavior before and after the COVID-19 pandemic. Social network analysis, specifically, degree and eigenvector centrality, serves as the employed research method. The findings reveal three significant characteristics of post-pandemic tourism patterns. First, an increase in the popularity of local provinces as tourist destinations is noted, and this is accompanied by a decrease in the tour centrality of the Seoul metropolitan area. However, the centrality of the Seoul metropolitan area is being revitalized as the post-pandemic era progresses. Second, there was a noticeable decrease in the centrality of numerous tollgates between 2019 and 2020, indicating an elevated level of public concern regarding infection prevention measures. However, between 2020 and 2021, many tollgate centralities increased, suggesting a shift in people’s attitude towards the infection. Third, driven by people’s demand for natural tour spots with limited human contact, the post-pandemic era has witnessed the emergence of new tour sites. These findings are significant, as they enable the prediction of future changes in tourism behavior amid recurring pandemics, potentially informing government policies on urban development. Thus, this study underscores the essential role of tourism research in shaping future urban policy. KCI Citation Count: 0
AbstractList This study aims to analyze the typical characteristics of regions preferred as tourism destinations in the post-pandemic era and examine the effects of the pandemic on people’s tourism behavior. Utilizing the origin-destination (O-D) data captured by South Korea’s toll collection system (TCS) between 2019 and 2021, the research explores differences in tourism behavior before and after the COVID-19 pandemic. Social network analysis, specifically, degree and eigenvector centrality, serves as the employed research method. The findings reveal three significant characteristics of post-pandemic tourism patterns. First, an increase in the popularity of local provinces as tourist destinations is noted, and this is accompanied by a decrease in the tour centrality of the Seoul metropolitan area. However, the centrality of the Seoul metropolitan area is being revitalized as the post-pandemic era progresses. Second, there was a noticeable decrease in the centrality of numerous tollgates between 2019 and 2020, indicating an elevated level of public concern regarding infection prevention measures. However, between 2020 and 2021, many tollgate centralities increased, suggesting a shift in people’s attitude towards the infection. Third, driven by people’s demand for natural tour spots with limited human contact, the post-pandemic era has witnessed the emergence of new tour sites. These findings are significant, as they enable the prediction of future changes in tourism behavior amid recurring pandemics, potentially informing government policies on urban development. Thus, this study underscores the essential role of tourism research in shaping future urban policy. KCI Citation Count: 0
Author Park, Mir
Seo, Ducksu
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