Daily tourism demand forecasting : the impact of complex seasonal patterns and holiday effects
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 1573-1592 |
Number of pages | 20 |
Journal / Publication | Current Issues in Tourism |
Volume | 26 |
Issue number | 10 |
Online published | 14 Apr 2022 |
Publication status | Published - 2023 |
Link(s)
Abstract
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.
Research Area(s)
- Tourism demand forecasting, daily tourism demand, holiday effects, seasonal patterns, FB Prophet, EMPIRICAL MODE DECOMPOSITION, TIME-SERIES, NEURAL-NETWORK, OCCUPANCY, ACCURACY, TRAVEL
Citation Format(s)
Daily tourism demand forecasting: the impact of complex seasonal patterns and holiday effects. / Liu, Yunhao; Feng, Gengzhong; Chin, Kwai-Sang et al.
In: Current Issues in Tourism, Vol. 26, No. 10, 2023, p. 1573-1592.
In: Current Issues in Tourism, Vol. 26, No. 10, 2023, p. 1573-1592.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review