Forecasting models of Chinese, Malaysian and South Korean tourists visiting Thailand

Abstract

This research presents a comparative study of two different forecasting methods based on the monthly Chinese, Malaysian, and South Korean tourists visiting Thailand. Holt-Winters method and Box-Jenkins method are compared. The data are taken from the Tourism Authority of Thailand, Ministry of Tourism and Sports starting from January, 2007 to December, 2018. The data are divided into 2 sets. The first set from January, 2007 to December, 2017 is used for constructing and selection the forecasting models. The second set from January, 2018 to December, 2018 is used for computing the accuracy of the forecasting model. The forecasting models are chosen by considering the smallest root mean square error (RMSE). The mean absolute percentage error (MAPE) is used to measure the accuracy of the model. The results show that Additive Holt-Winters method obtains the smallest RMSE for Chinese tourists and Box-Jenkins method gain the smallest RMSE for both Malaysian and South Korean tourists in the modeling process. While MAPE in the forecasting process for China, Malaysia and South Korea tourists are 10.22%, 11.71% and 5.14% respectively.