Forecasting tourism: a combined approach

被引：44
作者：
Chu, FL [1 ]
机构：
[1] Natl Taiwan Univ, Grad Inst San Min Chu 1, Taipei 10764, Taiwan
来源：
TOURISM MANAGEMENT | 1998年 / 19卷 / 06期
关键词：
combined forecast model; seasonal nonseasonal ARIMA; sine wave nonlinear regression; Singapore; mean absolute percentage error;
D O I：
10.1016/S0261-5177(98)00053-3
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
In this article, we employ a combined seasonal nonseasonal ARIMA and sine wave nonlinear regression forecast model to predict international tourism arrivals, as represented by the number of world-wide visitors to Singapore. Compared with a similar study of the accuracy of international tourist arrivals forecasts by Chan (Journal of Travel Research, 1993, 31, 58-60)(1) and Chu (Journal of Travel Research, 1998, 36, 79-84)(2) using other univariate time series models, our proposed model has the smallest mean absolute percentage error. (C) 1998 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码：515 / 520
页数：6
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