Call for Papers: Special Issue on tourism forecasting in the journal Forecasting
Tourism and its time series forecasts are of high importance for regional and national economies all over the world. Their importance has become even more evident in a period when demand suffered an abrupt rupture due to SARS-CoV-2.
With the COVID-19 vaccination now in sight, recovery of the tourism sector is expected. More than ever, accurate forecasting of tourism demand at all levels is of utmost importance for investors, as well as local and national political decision-makers to prepare infrastructures, investments, and recruitment to receive tourists.
The aim of this Special Issue titled "Tourism Forecasting: Time-Series Analysis of World and Regional Data" is to collect contributions about analyzing and forecasting tourism time series before, during, and after the pandemic period.
We are pleased to invite you to submit your valuable contributions in the main scope of the journal Forecasting and devoted to tourism forecasting. Global, national, and regional data analyses are welcomed, in addition to sectorial tourism analyses (transportation, accommodation, domestic tourism, senior tourism, health tourism, scientific tourism, etc.). All forecasting methods devoted to tourism time series are welcome. Contributions considering the COVID-19 pandemic period analysis and the recovery period for the tourism sector forecast, considering similar or different opening scenarios are particularly welcomed in this Special Issue.
For this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:
- Analysis of tourism time series;
- Forecasting of tourism time series using linear and non-linear models;
- Univariate and multivariate models;
- Statistical, machine learning, and hybrid models;
- Limitations and possibilities of forecasting in the light of the COVID-19 pandemic;
- Scenario forecasting;
- Point, interval, and density forecasting;
- Big data as leading indicators in the COVID-19 pandemic;
- Forecast combination;
- Directional change accuracy;
- Ex-ante tourism demand forecasting;
- Forecasting for single attractions, tourism segments, the sharing economy, etc.