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

Author

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  • Yunhao Liu
  • Gengzhong Feng
  • Kwai-Sang Chin
  • Shaolong Sun
  • Shouyang Wang

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.

Suggested Citation

  • Yunhao Liu & Gengzhong Feng & Kwai-Sang Chin & Shaolong Sun & Shouyang Wang, 2023. "Daily tourism demand forecasting: the impact of complex seasonal patterns and holiday effects," Current Issues in Tourism, Taylor & Francis Journals, vol. 26(10), pages 1573-1592, May.
    • Handle: RePEc:taf:rcitxx:v:26:y:2023:i:10:p:1573-1592
    DOI: 10.1080/13683500.2022.2060067
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