Daily tourism demand forecasting: the impact of complex seasonal patterns and holiday effects

被引:16
作者
Liu, Yunhao [1 ,2 ]
Feng, Gengzhong [1 ]
Chin, Kwai-Sang [2 ]
Sun, Shaolong [1 ]
Wang, Shouyang [3 ]
机构
[1] Xi An Jiao Tong Univ, Sch Management, Xian, Peoples R China
[2] City Univ Hong Kong, Dept Adv Design & Syst Engn, Kowloon, Hong Kong, Peoples R China
[3] Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
Tourism demand forecasting; daily tourism demand; holiday effects; seasonal patterns; FB Prophet; EMPIRICAL MODE DECOMPOSITION; TIME-SERIES; NEURAL-NETWORK; OCCUPANCY; ACCURACY; TRAVEL;
D O I
10.1080/13683500.2022.2060067
中图分类号
F [经济];
学科分类号
02 ;
摘要
Daily tourism demand forecasting can provide important implications for the tourism industry. However, there exist limitations in applying traditional methods to forecast daily tourism demand because of the complex seasonal patterns and holiday effects. In this study, we introduce FB Prophet and apply it to the forecasting of daily tourism demand in the Jiuzhai Valley National Park and Macao from Mainland China. The decomposition result of FB Prophet shows its ability to handle the influence of seasonal patterns and holiday effects. The forecasting results show that considering seasonal patterns, holiday effects, and other predictors can significantly improve the forecasting performance, and FB Prophet outperforms other methods.
引用
收藏
页码:1573 / 1592
页数:20
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