The Social Sciences
ISSN: Online 1993-6125ISSN: Print 1818-5800
Abstract
The ARIMA Model is good for tourism demand forecasting when the uncertainty is low. However, when several uncertainty events happened, such as Chinese holidays, political turmoil and structural changes in our study, the model reacts very weakly. After comparing the out-of-sample forecast performances of ARIMA and Seasonal ARIMA (SARIMA) Models, we suggest that the SARIMA Model produce a more stable forecast especially when the structural change occurs and high uncertainty appears. We recommend the policy makers and relevant travel decision section to use SARIMA method to conduct the tourist forecasting.
How to cite this article:
Songsak Sriboonchitta, Siwarat Kuson and Xue Gong. Forecasting the Chinese Tourist Arrivals to Thailand the Time Series Approach.
DOI: https://doi.org/10.36478/sscience.2016.4617.4621
URL: https://www.makhillpublications.co/view-article/1818-5800/sscience.2016.4617.4621