The Methodological Progress of Tourism Demand Forecasting: A Review of Related Literature

被引:75
|
作者
Goh, Carey [1 ]
Law, Rob [1 ]
机构
[1] Hong Kong Polytech Univ, Sch Hotel & Tourism Management, Kowloon, Hong Kong, Peoples R China
关键词
Tourism demand modeling; review; econometrics; time series; artificial intelligence; INTERNATIONAL TOURISM; TIME-SERIES; NEURAL-NETWORK; TRAVEL DEMAND; ERROR-CORRECTION; UNITED-STATES; MODEL; COINTEGRATION; DETERMINANTS; SEASONALITY;
D O I
10.1080/10548408.2011.562856
中图分类号
F [经济];
学科分类号
02 ;
摘要
Research on modeling the estimation and forecasting of tourism demand has evolved with increasing sophistication and improved quality. In this study, 155 research papers published between 1995 and 2009 were identified and were classified into three main groups according to the methods and techniques adoptedan econometric-based approach, time series techniques, and artificial intelligence (AI)-based methods. It appears that the more advanced methods such as cointegration, error correction model, time varying parameter model, and their combinations with systems of equations produce better results in terms of forecasting accuracy. We also discuss the implications and suggest future directions of tourism research techniques and methods.
引用
收藏
页码:296 / 317
页数:22
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