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

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

18 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)1573-1592
Number of pages20
Journal / PublicationCurrent Issues in Tourism
Volume26
Issue number10
Online published14 Apr 2022
Publication statusPublished - 2023

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