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Recovery preparedness of global air transport influenced by COVID-19 pandemic: Policy intervention analysis

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  • Zhu, Chunli
  • Wu, Jianping
  • Liu, Mingyu
  • Wang, Linyang
  • Li, Duowei
  • Kouvelas, Anastasios

Abstract

The outbreak of COVID-19 constitutes an unprecedented disruption globally, in which risk management framework is on top priority in many countries. Travel restriction and home/office quarantine are some frequently utilized non-pharmaceutical interventions, which bring the worst crisis of airline industry compared with other transport modes. Therefore, the post-recovery of global air transport is extremely important, which is full of uncertainty but rare to be studied. The explicit/implicit interacted factors generate difficulties in drawing insights into the complicated relationship and policy intervention assessment. In this paper, a Causal Bayesian Network (CBN) is utilized for the modelling of the post-recovery behaviour, in which parameters are synthesized from expert knowledge, open-source information and interviews from travellers. The tendency of public policy in reaction to COVID-19 is analyzed, whilst sensitivity analysis and forward/backward belief propagation analysis are conducted. Results show the feasibility and scalability of this model. On condition that no effective health intervention method (vaccine, medicine) will be available soon, it is predicted that nearly 120 days from May 22, 2020, would be spent for the number of commercial flights to recover back to 58.52%–60.39% on different interventions. This intervention analysis framework is of high potential in the decision making of recovery preparedness and risk management for building the new normal of global air transport.

Suggested Citation

  • Zhu, Chunli & Wu, Jianping & Liu, Mingyu & Wang, Linyang & Li, Duowei & Kouvelas, Anastasios, 2021. "Recovery preparedness of global air transport influenced by COVID-19 pandemic: Policy intervention analysis," Transport Policy, Elsevier, vol. 106(C), pages 54-63.
    • Handle: RePEc:eee:trapol:v:106:y:2021:i:c:p:54-63
    DOI: 10.1016/j.tranpol.2021.03.009
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    Cited by:

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    2. Anne Graham & David Warnock-Smith & John F. O’Connell & Marina Efthymiou & Xingwu Zheng, 2023. "Market Developments on Chinese International Air Passenger Markets in Light of COVID-19 Policy Measures," Sustainability, MDPI, vol. 15(2), pages 1-24, January.
    3. Yiu, Cho Yin & Ng, Kam K.H. & Yu, Simon C.M. & Yu, Chun Wah, 2022. "Sustaining aviation workforce after the pandemic: Evidence from Hong Kong aviation students toward skills, specialised training, and career prospects through a mixed-method approach," Transport Policy, Elsevier, vol. 128(C), pages 179-192.
    4. Betarelli Junior, Admir Antonio & Faria, Weslem Rodrigues & Proque, Andressa Lemes & Perobelli, Fernando Salgueiro & de Almeida Vale, Vinicius, 2021. "COVID-19, public agglomerations and economic effects: Assessing the recovery time of passenger transport services in Brazil," Transport Policy, Elsevier, vol. 110(C), pages 254-272.
    5. Li, Siping & Zhou, Yaoming & Kundu, Tanmoy & Sheu, Jiuh-Biing, 2021. "Spatiotemporal variation of the worldwide air transportation network induced by COVID-19 pandemic in 2020," Transport Policy, Elsevier, vol. 111(C), pages 168-184.
    6. Weiwei Guo & Yan Feng & Wenxiu Luo & Yilong Ren & Jiyuan Tan & Xiaobei Jiang & Qingwan Xue, 2022. "The Impacts of COVID-19 and Policies on Spatial and Temporal Distribution Characteristics of Traffic: Two Examples in Beijing," Sustainability, MDPI, vol. 14(3), pages 1-17, February.
    7. Sun, Xiaoqian & Wandelt, Sebastian & Zhang, Anming, 2022. "Ghostbusters: Hunting abnormal flights in Europe during COVID-19," Transport Policy, Elsevier, vol. 127(C), pages 203-217.

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