Acta turistica, Vol. 37 No. 2, 2025.
Preliminary communication
https://doi.org/10.22598/at/2025.37.2.213
CLUSTERING EUROPEAN COUNTRIES BY POST-COVID-19 AIRPASSENGER RECOVERY (2018–2023): AN EXPLORATORY ANALYSIS
Ivan JAJIĆ
; University of Zagreb Faculty of Economics & Business, Zagreb, Croatia
Katarina ĆURKO
; University of Zagreb Faculty of Economics & Business, Zagreb, Croatia
Jasmina PIVAR
; University of Zagreb Faculty of Economics & Business, Zagreb, Croatia
Abstract
The authors analyze Eurostat’s air-passenger data for 29 European countries during three reference years – 2018 (pre-COVID), 2020 (COVID-19), and 2023 (recovery). By applying the k-means clustering method on standardized variables heterogenous recovery patterns are classified. Model selection is supported by the Elbow method, Silhouette approach, and Calinski–Harabasz index. The findings reveal heterogeneous recovery by 2023. All clusters are reported in detail including percentage changes and robustness checks. Managerial and policy implications for air transport and tourism (capacity planning, route development, targeted incentives) and information technologies’ contribution to enhancing analytical processes and supporting data-driven decision-making are discussed.
Keywords
k-means; statistical analysis; visualization; COVID-19; international tourist flows
Hrčak ID:
343137
URI
Publication date:
31.12.2025.
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