Some of the methodological approaches cited in Li article are reflected in the statistics presented on China.org. The data used to come up with statistics presented on the website was subdivided into two methods namely the qualitative and quantitative methods. The quantitative literature for undertaking predictions together with some artificial intelligence techniques have been employed in forecasting the tourism demand in Greater China. Time series has been extensively used in Li’s article and China.org. The statistics provided are in line with the UNWTO standards and guidelines. There has been an identification of constraints and gaps as well as appropriate recommendations for upgrading the existing criteria to cater for future demands. Factors of demand that have to be identified are seasonality and outbound tourism.
Some of the analytical methodologies suggested for meta-analysis include the use of time-series, econometric models, and artificial intelligence methods (Li, 2009). Tourism managers can use the data from modelling and forecasting to make preparations to fulfil the forecasted future tourism demand. Also, tourism demand has impacts on airlines, tour operators, and hospitality industry. Therefore, measuring tourism demand enables proper planning across all these sectors to enable them to take full advantage of the tourism products. For instance, in the field of tourism career opportunities, measuring tourism demand enables tourism related job forecasting (Goeldner & Ritchie, 2003). Forecasting serves a wide range of practitioners from either private or public sectors in numerous ways. For that reason, accurate forecasts of tourism product sales together with the development of tourism demand in a country’s destination can assist the relevant authorities to decide as well as implement policies for the purpose of realizing sustainable development of tourism (Frechtling, 2001).
References
Goeldner, C., & Ritchie, J. (2003). Tourism. Hoboken, N.J.: Wiley.
Frechtling, D. C. (2001). Forecasting Tourism Demand: Methods and Strategies. Oxford:
Butterworth-Heinemann.
Li, G. (2009). Tourism Demand Modeling and Forecasting: A Review of Literature Related to Greater China. Journal of China Tourism Research, 5(1), 2-40.
