Quantitative Analysis of Seasonality and the Impact of COVID-19 on Tourists' Use of Urban Green Space in Okinawa: An ARIMA Modeling Approach Using Web Review Data
Land
; 12(5), 2023.
Article
Dans Anglais
| Web of Science | ID: covidwho-20244995
ABSTRACT
We employed publicly available user-generated content (UGC) data from the website Tripadvisor and developed an autoregressive integrated moving average (ARIMA) model using the R language to analyze the seasonality of the use of urban green space (UGS) in Okinawa under normal conditions and during the COVID-19 pandemic. The seasonality of the use of ocean-area UGS is primarily influenced by climatic factors, with the peak season occurring from April to October and the off-peak season from November to March. Conversely, the seasonality of the use of non-ocean-area UGS remains fairly stable throughout the year, with a relatively high number of visitors in January and May. The outbreak of the COVID-19 pandemic greatly impacted visitor enthusiasm for travel, resulting in significantly fewer actual postings compared with predictions. During the outbreak, use of ocean-area UGS was severely restricted, resulting in even fewer postings and a negative correlation with the number of new cases. In contrast, for non-ocean-area UGS, a positive correlation was observed between the change in postings and the number of new cases. We offer several suggestions to develop UGS management in Okinawa, considering the opportunity for a period of recovery for the tourism industry.
Texte intégral:
Disponible
Collection:
Bases de données des oragnisations internationales
Base de données:
Web of Science
Type d'étude:
Études expérimentales
/
Étude pronostique
langue:
Anglais
Revue:
Land
Année:
2023
Type de document:
Article
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