A review of research on tourism demand forecasting
Richard T.R. Qiu and
Annals of Tourism Research, 2019, vol. 75, issue C, 338-362
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.
Keywords: Tourism demand; Time series; Econometric model; Forecast combination; Artificial intelligence model; Judgment forecasts (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:anture:v:75:y:2019:i:c:p:338-362
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