Tourism forecasting has garnered considerable interest. However, integrating tourism
forecasting with volatility is significantly less typical. This study investigates the performance …

Many past studies conducted have explored and focused primarily on forecasting and
predicting tourism demand. However, this research aims to concentrate on the aspect of how …

This study attempts to enhance the effectiveness of stochastic volatility data. This work
presents an empirical case involving the forecasting of tourism demand to demonstrate the …

Existing research has shown that combination can effectively improve tourism forecasting
accuracy compared with single model. However, the model uncertainty and structural …

Even though both symmetric and asymmetric conceptions of news impacts are well-
established in the disciplines of economics and financial markets, the effects of combining …

Much research shows that combining forecasts improves accuracy relative to individual
forecasts. However, existing non-tourism related literature shows that combined forecasts …

Combination forecasting is an important in the literature on tourism. This study considers
three important issues to develop a more accurate combination forecasting method for …

Quantitative methods for forecasting tourist arrivals can be subdivided into causal methods
and non-causal methods. Non-causal time series methods remain popular tourism …

This study introduces an innovative framework that harnesses the most recent transformer
architecture to enhance tourism demand forecasting. The proposed transformer-based …

Previous studies have shown that different market factors influence tourism demand at
different timescales. Accordingly, we propose the decomposition ensemble learning …