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

By Haiyan Song, Richard T. R. Qiu, Jinah Park. Annals of Tourism Research, 2019

460 citations recorded by the source corpus.

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.

Subfields: Sociology and Political Science, Tourism, Leisure and Hospitality Management

View Paper: https://www.semanticscholar.org/paper/9eb147f7b2fb30a6b1cdcf20b57ed0f09faf0eae

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Sociology and Political Science

1. Pritee Ray
2. Ratri Parida
3. Sanjita Jaipuria

In Tourism, Leisure and Hospitality Management

1. Pritee Ray
2. Ratri Parida
3. Sanjita Jaipuria

Citations in the corpus

• The impact of COVID-19 on tourism sector in India (2020, methodology): “Forecasting models used for predicting tourism demand Tourism forecasting has been an important topic of discussion and has evolved over the decades (Liu et al., 2019; Song et al., 2019).”