Forecasting Model for the International Tourism Demand in Taiwan

Thanh-Lam Nguyen, Jui-Chan Huang, Chuang-Chi Chiu, Ming-Hung Shu and Wen-Ru Tsai
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Thanh-Lam Nguyen: National Kaohsiung University of Applied Sciences, Taiwan
Jui-Chan Huang: National Kaohsiung University of Applied Sciences, Taiwan
Chuang-Chi Chiu: Taiwan Knowledge Bank, Taiwan
Ming-Hung Shu: National Kaohsiung University of Applied Sciences, Taiwan
Wen-Ru Tsai: National Kaohsiung University of Applied Sciences, Taiwan Abstract: Purpose: Tourism has been considered a complexly integrated and self-contained economic activity but it is one of the biggest industries in many countries. This paper aims at finding an accurate forecasting model in order to make the tourism industry grow stably. Design/methodology/approach: However, the determinants of the international tourism demand are not fully identified; therefore, in this paper, it is strongly suggested to use Grey forecasting model which is widely used to deal mainly with the problems of uncertainty with few data points and/or poor information which is said to be “partial known, partial unknown”. In order to improve the accuracy of the model, an improved & accurate forecasting model FGM is created by combining the Fourier residual modification with the traditional Grey model GM(1,1). Findings: FGM(1,1) had a very low mean absolute percentage error (MAPE) of 1.5755% in the case of monthly international tourist arrival in Taiwan. And therefore, it is selected to forecast the inbound tourism demand in Taiwan for the time being. Originality/value: Though many researches have been conducted in employing Grey forecasting model and Fourier residual modification, they are revisited and applied in the case of the international tourism demand in Taiwan.

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Keywords: tourism demand; grey forecasting; fourier modification (search for similar items in EconPapers)
Date: 2013
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