Abstract
The COVID-19 pandemic and corresponding border control policies of various destinations have had a profound impact on the tourism industry worldwide. Although a few destinations adopted a ‘co-existence’ policy by partially re-opening their borders, changes in the COVID-19 situation, particularly with respect to the spread of new variants, have caused major uncertainties for the tourism industry.
Against this background, with the goal of advancing tourism forecasting methodologies and informing industrial practitioners about good practices in tourism forecasting and the predicted impact of COVID-19, in July 2020 the Curated Collection of Annals of Tourism Research on Tourism Forecasting announced a forecasting competition. Three competing teams, namely the Asia and Pacific team (Qiu et al., 2021), the Europe team (Liu et al., 2021) and the Africa team (Kourentzes et al., 2021), implemented two stages of tourism demand forecasting (ex post forecasts for 2019Q1–2019Q4 and ex ante forecasts for 2020Q1–2021Q4), represented by inbound visitor arrivals or hotel nights, for 20 countries/regions.
The competition rules for both stages and the results of the accuracy evaluation of the first-stage forecasting (i.e., ex post forecasting for the period 2019Q1–2019Q4) were described in Song and Li (2021). The Asia and Pacific team won Stage 1 of the competition by stacking five time-series models, which outperformed the benchmark seasonal naïve model by 22 % in terms of accuracy, evaluated by the relative mean absolute scaled error (MASE) against seasonal naïve model. The forecasting evaluation results for Stage 2 and the overall competition results of the three teams are set forth in this commentary and will be presented at the 8th Conference of the International Association for Tourism Economics in Perpignan, France in June 2022.