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Forecasting Model for the International Tourism Demand in Taiwan

Author

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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.)

Abstract

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Suggested Citation

  • Thanh-Lam Nguyen & Jui-Chan Huang & Chuang-Chi Chiu & Ming-Hung Shu & Wen-Ru Tsai, 2013. "Forecasting Model for the International Tourism Demand in Taiwan," Diversity, Technology, and Innovation for Operational Competitiveness: Proceedings of the 2013 International Conference on Technology Innovation and Industrial Management,, ToKnowPress.
    • Handle: RePEc:tkp:tiim13:s5_61-70
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    References listed on IDEAS

    as
    1. Witt, Stephen F. & Witt, Christine A., 1995. "Forecasting tourism demand: A review of empirical research," International Journal of Forecasting, Elsevier, vol. 11(3), pages 447-475, September.
    2. Haiyan Song & Stephen F. Witt & Gang Li, 2003. "Modelling and Forecasting the Demand for Thai Tourism," Tourism Economics, , vol. 9(4), pages 363-387, December.
    3. Gonzalez, Pilar & Moral, Paz, 1995. "An analysis of the international tourism demand in Spain," International Journal of Forecasting, Elsevier, vol. 11(2), pages 233-251, June.
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    Cited by:

    1. Yi-Chung Hu, 2021. "Forecasting tourism demand using fractional grey prediction models with Fourier series," Annals of Operations Research, Springer, vol. 300(2), pages 467-491, May.
    2. Yi-Chung Hu, 2021. "Developing grey prediction with Fourier series using genetic algorithms for tourism demand forecasting," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(1), pages 315-331, February.

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