TY  - JOUR
T1  - Forecasting the Chinese Tourist Arrivals to Thailand the Time Series Approach
AU - Gong, Xue AU - Sriboonchitta, Songsak AU - Kuson, Siwarat 
JO  - The Social Sciences
VL  - 11
IS  - 19
SP  - 4617
EP  - 4621
PY  - 2016
DA  - 2001/08/19
SN  - 1818-5800
DO  - sscience.2016.4617.4621
UR  - https://makhillpublications.co/view-article.php?doi=sscience.2016.4617.4621
KW  - Chinese tourist arrivals
KW  -forecasting
KW  -Thailand
KW  -ARIMA method
KW  -SARIMA method
AB  - 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.
ER  -