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Tourism demand forecasting using short video information

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  • Hu, Mingming
  • Dong, Na
  • Hu, Fang

Abstract

Based on short video information, this study extracted two explanatory variables, popularity and publicity, to empirically forecast weekly tourism demand for a destination (Macao) and a tourist attraction (Mount Siguniang, China). Results indicated that 1) models integrating the popularity or publicity of short videos outperform models without these attributes in tourism demand forecasting; 2) compared with popularity, models featuring publicity from short videos can generate more accurate forecasts; 3) models combining publicity and popularity do not necessarily exceed the performance of models including only publicity; and 4) when models account for search queries as well as publicity, search queries help improve forecasting accuracy for tourist attractions (this positive impact does not apply to destinations).

Suggested Citation

  • Hu, Mingming & Dong, Na & Hu, Fang, 2024. "Tourism demand forecasting using short video information," Annals of Tourism Research, Elsevier, vol. 109(C).
    • Handle: RePEc:eee:anture:v:109:y:2024:i:c:s0160738324001154
    DOI: 10.1016/j.annals.2024.103838
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    References listed on IDEAS

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