Comparative Time Series Forecasting of International Tourist Arrivals to Thailand through the Sadao Border Checkpoint, Songkhla Province
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Abstract
This study aims to analyze the movement patterns of the number of international tourists entering Thailand through the Sadao border checkpoint in Songkhla Province in each period, in order to examine the trend, seasonal variation, and cyclical components of the time–series, and to compare the forecasting performance between the Holt–Winters exponential smoothing method and the
Box–Jenkins method. The data consisted of monthly numbers of international tourists entering Thailand via the Sadao border checkpoint during 2012 to 2019, totaling 96 months. The data were devided into two subsets: a training set covering 2012–2018 and a testing set for 2019. These datasets were used to estimate and evaluate two time-series forecasting techniques, namely the Holt–Winters exponential smoothing method and the Box–Jenkins model. Model adequacy and forecasting performance were assessed using the mean absolute percentage error (MAPE) and the root mean square error (RMSE).
The results showed that the number of international tourists entering Thailand through the Sadao border checkpoint, Songkhla Province, from 2012 to 2019 exhibited a steadily increasing trend over time and was significantly influended by seasonal factors. The seasonal index was highest in December, followed by June, April, and March, respectively, while September had the lowest seasonal index, followed by January and October. In addition, a cyclical component was observed, as the pattern of increases and decreases in tourist numbers tended to repeat during the same periods each year. The comparison of forecasting performance indicated that the Holt–Winters exponential smoothing method outperformed the Box–Jenkins model, yielding a lower mean absolute percentage error (11.29%) and a lower root mean square error (24,609.12). Therefore, the Holt–Winters exponential smoothing method was found to be more suitable for forecasting the number of tourists entering Thailand through the Sadao border checkpoint than the Box–Jenkins model. Accurate tourist arrival forecasts obtained from such models provide essential information to support tourism policy formulation and planning, as well as to enhance the efficiency of resource management and the long-term development of the tourism sector.
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