Rethinking COVID-19 tourism recovery
研究提出基于情景的预测方法，结合机器学习和统计模型测试旅游复苏路径，发现预测结果因历史危机选择而异，为政府和行业在疫情不确定性下规划提供参考。
• 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.