Wei Min
School of Management, Xiamen University, Xiamen, 361005, China
ABSTRACT
Experts and scholars from home and abroad have made multi-angle exploration and research on the tourism market forecasting, attained a lot of research achievement and also laid a solid foundation for the completion of this article. In China, as an important channel of foreign exchange earnings in trade in services, tourism industry has an important duty of expanding foreign exchange earnings. Derived from the expenditure of foreign tourists, international tourism revenue is a part of national income from other countries which flowing into the destination country or region and is used to compensate for the value of tourism products (services). The development of Chinas tourism industry and tourism market can not only attract domestic and foreign idle funds flowing to the tourism industry, but also to attract a large number of tourists that come from the country (territory) outside, thereby increasing our foreign exchange earnings. So, international tourism revenue becomes an important indicator to measure tourism especially inbound tourism. This study applied the regression model to analyzing and forecasting the rules and trends of tourism development.
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How to cite this article
Wei Min, 2013. Forecast and Inspection of Inbound Tourism Market in China. Journal of Applied Sciences, 13: 3387-3393.
DOI: 10.3923/jas.2013.3387.3393
URL: https://scialert.net/abstract/?doi=jas.2013.3387.3393
DOI: 10.3923/jas.2013.3387.3393
URL: https://scialert.net/abstract/?doi=jas.2013.3387.3393
REFERENCES
- Alleyne, D., 2006. Can seasonal unit root testing improve the forecasting accuracy of tourist arrivals? Tourism Econ., 12: 45-64.
Direct Link - Abbott, A., G. De Vita and L. Altinayc, 2012. Revisiting the convergence hypothesis for tourism markets: Evidence from Turkey using the pairwise approach. Tourism Manage., 33: 537-544.
CrossRef - Coshall, J.T., 2005. A selection strategy for modelling UK tourism flows by air to European destinations. Tourism Econ., 11: 141-158.
CrossRef - Davidson, R. and J.G. MacKinnon, 1998. Graphical methods for investigating the size and power of hypothesis tests. Manchester School, 66: 1-26.
CrossRef - Goh, C. and R. Law, 2011. The methodological progress of tourism demand forecasting: A review of related literature. J. Travel Tourism Market., 28: 296-317.
CrossRef - Gouveia, P.M.D.C.B. and P.M.M. Rodrigues, 2005. Dating and synchronizing tourism growth cycles. Tourism Econ., 11: 501-515.
CrossRef - Huang, J.H. and J.C.H. Min, 2002. Earthquake devastation and recovery in tourism: The Taiwan case. Tourism Manage., 23: 145-154.
CrossRef - Jackman, M. and K. Greenidge, 2010. Modelling and forecasting tourist flows to barbados using structural time series models. Tourism Hosp. Res., 10: 1-13.
Direct Link - Koc, E. and G. Altinay, 2007. An analysis of seasonality in monthly per person tourist spending in Turkish inbound tourism from a market segmentation perspective. Tourism Manage., 28: 227-237.
CrossRefDirect Link - Li, Y., 2000. Geographical consciousness and tourism experience. Ann. Tourism Res., 27: 863-883.
CrossRefDirect Link - Li, Y.P. and R.L.B. Lo, 2004. Applicability of the market appeal-robusticity matrix: A case study of heritage tourism. Tourism Manage., 25: 789-800.
CrossRef - Smeral, E. and M. Wuger, 2005. Does complexity matter? Methods for improving forecasting accuracy in tourism: The case of Austria. J. Travel Res., 44: 100-110.
Direct Link - Makridakis, S., 1986. The art and science of forecasting An assessment and future directions. Int. J. Forecasting, 2: 15-39.
CrossRefDirect Link - Ucar, N. and T. Omay, 2009. Testing for unit root in nonlinear heterogeneous panels. Econ. Lett., 104: 5-8.
CrossRef