Tourism demand forecasting – a review on the variables and models

• Main Authors: Mohd Khaidi, Sarah, Abu, Noratikah, Muhammad, Noryanti
• Format: Conference or Workshop Item
• Language: English
• Published: IOP Publishing 2019
• Subjects: G Geography (General); QA Mathematics
• Online Access: http://umpir.ump.edu.my/id/eprint/35140/1/2019%20Jour%20of%20Phy%20Tourism%20demand%20forecasting%20a%20review%20on%20the%20variables%20and%20models.pdf; http://umpir.ump.edu.my/id/eprint/35140/; https://doi.org/10.1088/1742-6596/1366/1/012111
• Institution: Universiti Malaysia Pahang

With the growth of the world's tourism industry, researchers took advantage to conduct numerous studies in forecasting of tourism demand. The objective of this paper is to review the studies on tourism demand starting from 2010 to 2018 which varies on the explanatory variables, such as tourist income, exchange rate, gross domestic product, and others. In addition, this study also reviewed the models used to forecast and analyse tourism demand which are time-series model, econometric causal model and artificial intelligence model. The result from this review shows it is difficult to conclude which models performed the best for tourism demand. However, in most of the studies, combined models outperformed single model. Furthermore, the authors mentioned about the roles of tourism practitioners in the industry, tourism seasonality and suggestions for further studies in the future.