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An airport level framework for examining the impact of COVID-19 on airline demand

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  • Dey Tirtha, Sudipta
  • Bhowmik, Tanmoy
  • Eluru, Naveen
Abstract
In this study, we examine the influence of Coronavirus disease 2019 (COVID-19) on airline demand at the disaggregate resolution of airport. The primary focus of our proposed research effort is to develop a framework that provides a blueprint for airline demand recovery as COVID-19 cases evolve over time. Airline monthly demand data is sourced from Bureau of Transportation Statistics for 380 airports for 24 months from January 2019 through December 2020. The demand data is augmented with a host of independent variables including COVID-19 related factors, demographic characteristics and built environment characteristics at the county level, airport specific factors, spatial factors, temporal factors, and adjoining county attributes. The effect of COVID-19 related factors is identified by considering global and local COVID-19 transmission, temporal indicators of pandemic start and progress, and interactions of airline demand predictors with global and local COVID-19 indicators. Finally, we present a blueprint for airline demand recovery where we consider three hypothetical scenarios of COVID-19 transmission rates – expected, pessimistic and optimistic. The results at the airport level from these scenarios are aggregated at the state or regional level by adding the demand from all airports in the corresponding state or region. These trends are presented by State and Region to illustrate potential differences across various scenarios. The results highlight a potentially slow path to airline demand recovery until COVID-19 cases subside.

Suggested Citation

  • Dey Tirtha, Sudipta & Bhowmik, Tanmoy & Eluru, Naveen, 2022. "An airport level framework for examining the impact of COVID-19 on airline demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 169-181.
    • Handle: RePEc:eee:transa:v:159:y:2022:i:c:p:169-181
    DOI: 10.1016/j.tra.2022.03.014
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    Cited by:

    1. Li, Siping & Xu, Gangyan & Zhou, Yaoming, 2023. "How air transport networks respond to long-lasting disruptive events like COVID-19: The first step toward long-term resilience," Transportation Research Part A: Policy and Practice, Elsevier, vol. 177(C).
    2. Bing Zhao & Hao Wu, 2022. "A System Dynamics Model of Multi-Airport Logistics System under the Impact of COVID-19: A Case of Jing-Jin-Ji Multi-Airport System in China," Sustainability, MDPI, vol. 14(19), pages 1-19, October.
    3. Tirtha, Sudipta Dey & Bhowmik, Tanmoy & Eluru, Naveen, 2024. "Accommodating spatio-temporal dependency in airline demand modeling," Journal of Air Transport Management, Elsevier, vol. 116(C).
    4. Tirtha, Sudipta Dey & Bhowmik, Tanmoy & Eluru, Naveen, 2023. "Understanding the factors affecting airport level demand (arrivals and departures) using a novel modeling approach," Journal of Air Transport Management, Elsevier, vol. 106(C).
    5. Borsati, Mattia & Fageda, Xavier, 2024. "Airline price responses in the face of demand shocks: European lessons from the COVID-19 pandemic," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).

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