日本旅遊需求預測─片段線性模型的應用

隨著全球的發展，日本旅遊產業的發展對於日本經濟與社會帶來了越來越重要的貢獻。本研究以片段線性模型，根據每月赴日旅客人次（月資料自1975至2018年），對日本旅遊需求進行預測。以評價模型預測能力指標──均方根百分比誤差（Root Mean Square Percentage Error，RMSPE）以及平均絕對百分比誤差（Mean Absolute Percentage Error，MAPE）估測精確度。實證分析結果，片段線性模型於樣本外預測期間，無論是向前預測6個月、向前預測12個月、向前預測18個月及向前預測24個月之MAPE值與RMSPE值皆低於10％，顯示模型之預測能力高度準確，期望研究結果能為相關研究領域做出貢獻。

關鍵字

預測；旅遊需求；片段線性模型；日本；全球化

並列摘要

Japan's tourism industry became more significant in contribution to the society in the global developments. By using the piecewise linear model, this research forecasts the demand for Japan tourism based on the monthly tourist arrivals（monthly data from 1975 to 2018）. In addition, we use the root mean square percentage error（RMSPE）and mean absolute percentage error（MAPE）to assess the precision of the forecasting models. According to the results of empirical analysis, the prediction of piecewise linear approach during the period of out-of-sample time, both for forward prediction for 6, 12 , 18, and 24 months, MAPE and RMSPE values are lower than 10%, indicating that the predictive ability of the model is highly accurate. Hopefully, the outcome of this reaserch may make a contribution to the relevant academic fields.