Acta turistica, Vol. 37 No. 2, 2025.
Prethodno priopćenje
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
; Ekonomski fakultet Sveučilišta u Zagrebu, Zagreb, Hrvatska
Katarina ĆURKO
; Ekonomski fakultet Sveučilišta u Zagrebu, Zagreb, Hrvatska
Jasmina PIVAR
; Ekonomski fakultet Sveučilišta u Zagrebu, Zagreb, Hrvatska
Sažetak
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.
Ključne riječi
k-means; statistical analysis; visualization; COVID-19; international tourist flows
Hrčak ID:
343137
URI
Datum izdavanja:
31.12.2025.
Posjeta: 441 *