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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

Author

Listed:
  • Ruochen Yang

    (Graduate School of Horticulture, Chiba University, Chiba 271-8510, Japan)

  • Kun Liu

    (Graduate School of Horticulture, Chiba University, Chiba 271-8510, Japan)

  • Chang Su

    (School of Architecture and Urban Planning, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Shiro Takeda

    (Graduate School of Horticulture, Chiba University, Chiba 271-8510, Japan)

  • Junhua Zhang

    (Graduate School of Horticulture, Chiba University, Chiba 271-8510, Japan)

  • Shuhao Liu

    (Graduate School of Horticulture, Chiba University, Chiba 271-8510, Japan)

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.

Suggested Citation

  • Ruochen Yang & Kun Liu & Chang Su & Shiro Takeda & Junhua Zhang & Shuhao Liu, 2023. "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, MDPI, vol. 12(5), pages 1-25, May.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:5:p:1075-:d:1148527
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    References listed on IDEAS

    as
    1. Noszczyk, Tomasz & Gorzelany, Julia & Kukulska-Kozieł, Anita & Hernik, Józef, 2022. "The impact of the COVID-19 pandemic on the importance of urban green spaces to the public," Land Use Policy, Elsevier, vol. 113(C).
    2. Alicia Orea-Giner & Laura Fuentes-Moraleda & Teresa Villacé-Molinero & Ana Muñoz-Mazón & Jorge Calero-Sanz, 2022. "Does the Implementation of Robots in Hotels Influence the Overall TripAdvisor Rating? A Text Mining Analysis from the Industry 5.0 Approach," Post-Print hal-04039195, HAL.
    3. Bimonte, Salvatore & Faralla, Valeria, 2016. "Does residents' perceived life satisfaction vary with tourist season? A two-step survey in a Mediterranean destination," Tourism Management, Elsevier, vol. 55(C), pages 199-208.
    4. Park, Eunhye & Park, Jinah & Hu, Mingming, 2021. "Tourism demand forecasting with online news data mining," Annals of Tourism Research, Elsevier, vol. 90(C).
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