Global airport connectivity and resilience: a data-driven approach and inverse-U relationship, 1996–2024

This study analyzes the long-run evolution of global airport connectivity from 1996 to 2024 and examines how resilience to major shocks varies across the connectivity distribution. Using an extended Global Airport Connectivity Index (GACI) panel covering 101,049 airport–year observations and 5428 airports, it documents steady expansion punctuated by crises, a redistribution of connectivity across continents, and an increasingly multipolar hub hierarchy. The paper then develops a reproducible, multi-crisis resilience index with three components: depth (magnitude of loss), speed (pace of recovery), and adaptability (post-shock upgrading in the global hierarchy). The index aggregates realized airport performance across multiple major shocks, applies empirical-Bayes regularization to improve comparability across airports with uneven shock histories, and filters micro-fluctuations below 1% to reduce noise. Relating resilience to connectivity uncovers a consistent inverse-U relationship: resilience increases with connectivity up to a mid-scale range and declines among the most globally connected hubs. This pattern is consistent with greater exposure to synchronized shocks and scale-related operational frictions, although the analysis identifies the relationship rather than its underlying mechanisms. Robustness checks include alternative component weightings, pre-COVID estimates, crisis-specific recovery horizons, alternative adaptability definitions, region-specific COVID timing, an alternative fixed-scale connectivity construction, and non-overlapping crisis windows. These checks confirm the stability of the pattern. By embedding airport-level recovery behaviour in a three-decade network context, the GACI–resilience framework provides a systematic basis for comparing hub types and benchmarking realized resilience, and for informing route-development, infrastructure-planning, and policy strategies during pandemics, geopolitical disruptions, and other major shocks.

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Publication Details

Journal
Transportation Research Part E Logistics and Transportation Review
Published
2026-08-27
DOI
https://doi.org/10.1016/j.tre.2026.105192
Primary Topic
Aviation Industry Analysis and Trends
Type
article
Field-Weighted Citation Impact
0.00

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article

Global airport connectivity and resilience: a data-driven approach and inverse-U relationship, 1996–2024

Anming Zhang, Yilin Zhang, Tommy Cheung
Transportation Research Part E Logistics and Transportation Review
Aviation Industry Analysis and Trends
article

Global airport connectivity and resilience: a data-driven approach and inverse-U relationship, 1996–2024

Anming Zhang, Yilin Zhang, Tommy Cheung
article en

Abstract

This study analyzes the long-run evolution of global airport connectivity from 1996 to 2024 and examines how resilience to major shocks varies across the connectivity distribution. Using an extended Global Airport Connectivity Index (GACI) panel covering 101,049 airport–year observations and 5428 airports, it documents steady expansion punctuated by crises, a redistribution of connectivity across continents, and an increasingly multipolar hub hierarchy. The paper then develops a reproducible, multi-crisis resilience index with three components: depth (magnitude of loss), speed (pace of recovery), and adaptability (post-shock upgrading in the global hierarchy). The index aggregates realized airport performance across multiple major shocks, applies empirical-Bayes regularization to improve comparability across airports with uneven shock histories, and filters micro-fluctuations below 1% to reduce noise. Relating resilience to connectivity uncovers a consistent inverse-U relationship: resilience increases with connectivity up to a mid-scale range and declines among the most globally connected hubs. This pattern is consistent with greater exposure to synchronized shocks and scale-related operational frictions, although the analysis identifies the relationship rather than its underlying mechanisms. Robustness checks include alternative component weightings, pre-COVID estimates, crisis-specific recovery horizons, alternative adaptability definitions, region-specific COVID timing, an alternative fixed-scale connectivity construction, and non-overlapping crisis windows. These checks confirm the stability of the pattern. By embedding airport-level recovery behaviour in a three-decade network context, the GACI–resilience framework provides a systematic basis for comparing hub types and benchmarking realized resilience, and for informing route-development, infrastructure-planning, and policy strategies during pandemics, geopolitical disruptions, and other major shocks.

Transportation Research Part E Logistics and Transportation ReviewVol. 217
University of British Columbia (CA), Swinburne University of Technology (AU)
Social Sciences and Humanities Research Council of Canada
Industry, innovation and infrastructure
Openalex Percentile: Top 5%
Aviation Industry Analysis and Trends
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