Research on modeling the estimation and forecasting of tourism demand has evolved with increasing sophistication and improved quality. In this study, 155 research papers published between 1995 and 2009 were identified and were classified into three main groups according to the methods and techniques adopted-an econometric-based approach, time series techniques, and artificial intelligence (AI)-based methods. It appears that the more advanced methods such as cointegration, error correction model, time varying parameter model, and their combinations with systems of equations produce better results in terms of forecasting accuracy. We also discuss the implications and suggest future directions of tourism research techniques and methods.
- Artificial intelligence
- Time series
- Tourism demand modeling
ASJC Scopus subject areas
- Tourism, Leisure and Hospitality Management