Predictivity of tourism demand data

被引:9
|
作者
Zhang, Yishuo [1 ,2 ]
Li, Gang [1 ]
Muskat, Birgit [3 ]
Vu, Huy Quan [4 ]
Law, Rob [5 ]
机构
[1] Deakin Univ, Sch Informat Technol, Burwood, Vic 3125, Australia
[2] Chinese Acad Sci, Xinjiang Tech Inst Phys & Chem, Urumqi 830011, Peoples R China
[3] Australian Natl Univ, ANU Coll Business & Econ, Res Sch Management, Canberra, ACT 2601, Australia
[4] Deakin Univ, Dept Informat Syst & Business Analyt, Burwood, Vic 3125, Australia
[5] Hong Kong Polytech Univ, Sch Hotel & Tourism Management, Kowloon, 17 Sci Museum Rd,TST East, Hong Kong, Peoples R China
关键词
Data characteristics; Entropy; Predictivity; Tourism demand forecasting; TIME-SERIES; PREDICTABILITY; ARRIVALS; ENTROPY; ACCURACY; MODELS;
D O I
10.1016/j.annals.2021.103234
中图分类号
F [经济];
学科分类号
02 ;
摘要
As tourism researchers continue to search for solutions to determine the best possible forecasting performance, it is important to understand the maximum predictivity achieved by models, as well as how various data characteristics influence the maximum predictivity. Drawing on information theory, the predictivity of tourism demand data is quantitatively evaluated and beneficial for improving the performance of tourism demand forecasting. Empirical results from Hong Kong tourism demand data show that 1) the predictivity could largely help the researchers estimate the best possible forecasting performance and understand the influence of various data characteristics on the forecasting performance.; 2) the predictivity can be used to assess the short effect of external shock - such as SARS over tourism demand forecasting. (c) 2021 Elsevier Ltd. All rights reserved.
引用
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页数:16
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