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Diverging spatiotemporal responses to COVID-19Â by airports: Evidence from China

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  • Chen, Yuting
  • Fuellhart, Kurt
  • Grubesic, Tony H.
  • Zhang, Shengrun
  • Witlox, Frank

Abstract

The worldwide outbreak of COVID-19 released seismic waves on the airline industry. This paper assesses the responses to COVID-19Â by different airport clusters in China during the four quarters of 2020, comparing the residual percentages between the actual (with the virus) and forecast (without the virus) number of airline seats during the period. Specifically, this study examines (1) differences in the ways in which different categories of airports responded to the pandemic, and (2) the related impacts on seats available to passengers in relation to these actions. ARIMA (Autoregressive Integrated Moving Average model) time-series models were applied to predict seasonal seats at various groups of airports in 2020 using actual seats data from 2014 to 2019. The analysis based on both airport-operations and geographic patterns shows substantial heterogeneity in airport response. As multiple waves of outbreaks persist, post-pandemic management requires learning from the experience of the initial recovery (in 2020) at airports and devising corresponding strategies for negligence. The results provide transport officials and airport managers with information to evaluate the outcomes of COVID-19 while suggesting patterns that may emerge with future disruptions.

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  • Chen, Yuting & Fuellhart, Kurt & Grubesic, Tony H. & Zhang, Shengrun & Witlox, Frank, 2023. "Diverging spatiotemporal responses to COVID-19Â by airports: Evidence from China," Journal of Air Transport Management, Elsevier, vol. 113(C).
    • Handle: RePEc:eee:jaitra:v:113:y:2023:i:c:s0969699723001333
    DOI: 10.1016/j.jairtraman.2023.102490
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    Cited by:

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