Rethinking COVID-19 tourism recovery
• Introduces scenario-based forecasting for tourism during crises. • Combines machine learning and statistical models to test recovery paths. • Shows forecasts vary depending on the historical crisis used. • Informs government and industry planning under pandemic uncertainty. • Provides advanced methods for resilient tourism forecasting and decision-making.
Authors
- Efstathios Polyzos (ORCID: https://orcid.org/0000-0002-4317-1809)
- Anestis Fotiadis (ORCID: https://orcid.org/0000-0001-8806-7987)
- Tzung-Cheng Huan
Institutions
- National Chiayi University (TW)
- Zayed University (AE)
Publication Details
- Journal
- Annals of Tourism Research
- Published
- 2026-02-26
- DOI
- https://doi.org/10.1016/j.annals.2026.104147
- Primary Topic
- Diverse Aspects of Tourism Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00