A review of research on tourism demand forecasting: Launching the Annals of Tourism Research Curated Collection on tourism demand forecasting

Haiyan Song, Tianran Qiu, Jinah Park

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

This study reviews 211 key papers published between 1968 and 2018, for a better understanding of how the methods of tourism demand forecasting have evolved over time. The key findings, drawn from comparisons of method-performance profiles over time, are that forecasting models have grown more diversified, that these models have been combined, and that the accuracy of forecasting has been improved. Given the complexity of determining tourism demand, there is no single method that performs well for all situations, and the evolution of forecasting methods is still ongoing. This article also launches the Annals of Tourism Research Curated Collection on tourism demand forecasting, which contains past and hot off the press work on the topic and will continue to grow as new articles on the topic appear in Annals.
Original languageEnglish
Pages (from-to)338-362
JournalAnnals of Tourism Research
Volume75
DOIs
Publication statusPublished - 22 Mar 2019

Keywords

  • Tourism demand
  • Time series
  • Econometric model
  • Forecast combination
  • Artificial intelligence model
  • Judgment forecasts

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