Hiney, Noel ORCID: 0000-0002-2116-7999, Efthymiou, Marina
ORCID: 0000-0001-8611-5973 and Morgenroth, Edgar L.W.
ORCID: 0000-0002-9442-0561
(2025)
Adapting to uncertainty: Black swans, VUCA challenges and airport
resilience strategies.
Journal of the Air Transport Research Society (JATRS), 4
.
pp. 668-675.
ISSN 2941-198X
Abstract
Over the past 50 years, air travel and airport passenger numbers have consistently grown, despite setbacks from crises like oil shocks, terrorism and the COVID-19 pandemic. Post-pandemic passenger trends demonstrated the resilience of aviation and airports when recovering from the effects of major crises, notwithstanding the increased future uncertainty caused by geopolitical events since then. Through a combination of airport passenger performance analysis from 2019 to 2023, an airport manager survey undertaken in 2022 and an
assessment of events and trends during this period, as reported in the literature and contemporaneously through news and information channels, this paper assesses factors affecting airports during volatile, uncertain, complex and ambiguous (VUCA) periods, focusing on post-pandemic passenger trends and current challenges. It also
explores how airports can enhance resilience through improved processes, efficiency, and stronger stakeholder relationships. We found that smaller airports, in particular, will face revenue pressures, growing competition, and increased dependence on non-aeronautical revenue. State aid, increasingly tied to decarbonisation and digitalisation, will also become more challenging to secure. Linking empirical research findings with actionable strategies to enhance airport resilience and address these issues, we introduce the VUCAIR framework, a strategic
model designed to help airports anticipate and respond effectively to ongoing VUCA conditions in the global aviation landscape
Metadata
Item Type: | Article (Published) |
---|---|
Refereed: | Yes |
Uncontrolled Keywords: | Airport performance; Aviation resilience; Passenger Traffic; VUCA; VUCAIR |
Subjects: | Business > Assistive computer technology |
DCU Faculties and Centres: | UNSPECIFIED |
Publisher: | Springer |
Official URL: | https://www.sciencedirect.com/science/article/pii/... |
Copyright Information: | Authors |
ID Code: | 31050 |
Deposited On: | 09 May 2025 09:40 by Marina Efthymiou . Last Modified 09 May 2025 09:40 |
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