Showing 1 - 10 of 17
Purpose – This study aims to apply a new forecasting approach to improve predictions in the hospitality industry. To do so, the authors developed a multivariate setting that allows the incorporation of the cross-correlations in the evolution of tourist arrivals from visitor markets to a...
Persistent link: https://www.econbiz.de/10014764401
By means of Self-Organizing Maps we cluster fourteen European countries according to the most suitable way to model their agents’ expectations. Using the financial crisis of 2008 as a benchmark, we distinguish between those countries that show a progressive anticipation of the crisis and those...
Persistent link: https://www.econbiz.de/10011194342
The increasing interest aroused by more advanced forecasting techniques, together with the requirement for more accurate forecasts of tourism demand at the destination level due to the constant growth of world tourism, has lead us to evaluate the forecasting performance of neural modelling...
Persistent link: https://www.econbiz.de/10010729816
This study presents an extension of the Gaussian process regression model for multiple-input multiple-output forecasting. This approach allows modelling the cross-dependencies between a given set of input variables and generating a vectorial prediction. Making use of the existing correlations in...
Persistent link: https://www.econbiz.de/10011650323
The objective of this paper is to compare different forecasting methods for the short run forecasting of Business Survey Indicators. We compare the forecasting accuracy of Artificial Neural Networks (ANN) vs. three different time series models: autoregressions (AR), autoregressive integrated...
Persistent link: https://www.econbiz.de/10010710596
The objective of this paper is to compare different forecasting methods for the short run forecasting of Business Survey Indicators. We compare the forecasting accuracy of Artificial Neural Networks (ANN) vs. three different time series models: autoregressions (AR), autoregressive integrated...
Persistent link: https://www.econbiz.de/10010710607
Persistent link: https://www.econbiz.de/10010412358
This study presents an extension of the Gaussian process regression model for multiple-input multiple-output forecasting. This approach allows modelling the cross-dependencies between a given set of input variables and generating a vectorial prediction. Making use of the existing correlations in...
Persistent link: https://www.econbiz.de/10011537542
Persistent link: https://www.econbiz.de/10011476086
Persistent link: https://www.econbiz.de/10011430763