Predictivity of tourism demand data

Yishuo Zhang, Gang Li, Birgit Muskat, Huy Quan Vu, Rob Law

Research output: Journal article publicationJournal articleAcademic researchpeer-review

9 Citations (Scopus)


As tourism researchers continue to search for solutions to determine the best possible forecasting performance, it is important to understand the maximum predictivity achieved by models, as well as how various data characteristics influence the maximum predictivity. Drawing on information theory, the predictivity of tourism demand data is quantitatively evaluated and beneficial for improving the performance of tourism demand forecasting. Empirical results from Hong Kong tourism demand data show that 1) the predictivity could largely help the researchers estimate the best possible forecasting performance and understand the influence of various data characteristics on the forecasting performance.; 2) the predictivity can be used to assess the short effect of external shock — such as SARS over tourism demand forecasting.

Original languageEnglish
Article number103234
JournalAnnals of Tourism Research
Publication statusPublished - Jul 2021


  • Data characteristics
  • Entropy
  • Predictivity
  • Tourism demand forecasting

ASJC Scopus subject areas

  • Development
  • Tourism, Leisure and Hospitality Management


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