A piecewise linear approach to modeling and forecasting demand for Macau tourism

Tourism Management

Volumn 32, Issue 6, 2011, Pages 1414-1420

  Chu, Fong Lin ^a  

^a NATIONAL TAIWAN UNIVERSITY   (Taiwan)

Author keywords

Forecast; Macau; Piecewise linear model; Tourism demand

Indexed keywords

ACCURACY ASSESSMENT; BENCHMARKING; DEMAND ANALYSIS; FORECASTING METHOD; TOURISM MANAGEMENT; TOURISM MARKET; TOURIST ATTRACTION; TOURIST BEHAVIOR; TOURIST DESTINATION; TREND ANALYSIS;

CHINA; MACAU;

EID: 79960304270     PISSN: None     EISSN: 02615177     Source Type: Journal    
DOI: 10.1016/j.tourman.2011.01.018     Document Type: Article

References (36)

1. Ballie R.T. Long memory processes and fractional integration in econometrics. Journal of Econometrics 1996, 73:5-59.
2. Box G.E.P., Jenkins G.M. Time series analysis: Forecasting and control 1970, Holden Day, San Francisco.
3. Calantone R.J., de Benedetto A., Bojanic D.C. Multi method forecasts for tourism analysis. Annals of Tourism Research 1988, 15:387-406.
4. Cho V. A comparison of three different approaches to tourist arrival forecasting. Tourism Management 2003, 24:323-330.
5. Chu F.L. Forecasting tourism demand in Asian-Pacific countries. Annals of Tourism Research 1998, 25:597-615.
6. Chu F.L. Forecasting tourism demand with ARMA-based methods. Tourism Management 2009, 30:741-751.
7. Cochrane D., Orcutt G.H. Application of least squares regressions to relationships containing autocorrelated error terms. Journal of American Statistical Association 1949, 44:32-61.
8. Crouch I.G. The study of international tourism demand: a survey of practice. Journal of Travel Research 1994, 32:41-55.
9. Durbin J. Estimation of parameters in time series regression models. Journal of Royal Statistical Society, Series B 1960, 22:139-153.
10. Engle R.F. Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica 1982, 50:987-1007.
11. Fildes R., Makridakis S. The impact of empirical accuracy studies on time-series analysis and forecasting. International Statistical Review 1995, 63:289-308.
12. Fritz G., Brandon C., Xander J. Combining time series and econometric forecast of tourism activity. Annals of Tourism Research 1984, 11:219-229.
13. Fuji E.T., Mak H. Forecasting tourism demand: some methodology issues. Annals of Regional Science 1981, 15:72-83.
14. Geurts M. Forecasting the Hawaiian tourism market. Journal of Travel Research 1982, 21:18-21.
15. Geurts M., Ibrahim I.B. Comparing the Box-Jenkins approach with the exponentially smoothed forecasting model: application to Hawaii tourists. Journal of Marketing Research 1975, 12:182-188.
16. Gil-Alana L.A. Modeling international monthly arrivals using seasonal univariate long-memory processes. Tourism Management 2005, 26:867-878.
17. Granger C.W.J., Engle R.F. Econometric forecasting: a brief survey of current and future techniques. Forecasting in the social and natural sciences 1987, 117-140. D. Reidel Publishing, Dordrecht. K. Land, S. Schneider (Eds.).
18. Granger C.W.J., Joyeux R. An introduction to long-memory time series models and fractional differencing. Journal of Time Series Analysis 1980, 1:15-39.
19. Hildreth C., Lu J.Y. Demand relations with autocorrelated disturbances. Technical Bulletin 1960, Vol. 276. Michigan State University Agricultural Station.
20. Hosking J.R.M. Fractional differencing. Biometrika 1981, 68:165-176.
21. Law R. Back-propagation learning in improving the accuracy of neural network-based tourism demand forecasting. Tourism Management 2000, 21:331-340.
22. Law R., Au N. A neural network model to forecast Japanese demand for travel to Hong Kong. Tourism Management 1999, 20(1):89-97.
23. Lim C., McAleer M. Time series forecasts of international travel demand for Australia. Tourism Management 2002, 23:389-396.
24. Macau Government Tourist Office Macau travel and tourism statistics 2007 2007, Macau Government Tourist Office, Macau SAR.
25. Magnus J.R. Maximum likelihood estimation of the GLS model with unknown parameters in the disturbance covariance matrix. Journal of Econometrics 1978, 7:305-306.
26. The accuracy of major forecasting procedure 1984, John Wiley, New York. S. Makridakis, A. Anderson, R. Carbone, R. Fildes, M. Hibon, R. Lewandowske (Eds.).
27. Makridakis S., Hibon M. Accuracy of forecasting: an empirical investigation. Journal of the Royal Statistical Society 1979, 142:97-125.
28. Malamud B. Gravity model calibration of tourist travel to Las Vegas. Journal of Leisure Research 1973, 5:23-33.
29. Newbold P., Carlson W., Thorne Betty Statistics for business and economics 2007, Pearson Prentice Hall, New Jersey. 6th ed.
30. Prais S.J., Winsten C.B. Trend estimators and serial correlation. Cowles commission discussion paper 1954, No. 383. Chicago.
31. Song H., Li G. Tourism demand modeling and forecasting - a review of recent research. Tourism Management 2008, 29:203-220.
32. Song H., Witt S.F. Forecasting international tourist flows to Macau. Tourism Management 2006, 27:214-224.
33. Suits D., Mason A., Chan L. Spline function fitted by standard regression methods. Review of Economics and Statistics 1978, 60:132-139.
34. Witt S.F., Newbould G.D., Watkins A. Forecasting domestic tourism demand: application to Las Vegas arrivals data. Journal of Travel Research 1992, 31:36-41.
35. Witt S.F., Witt C.A. Tourism forecasting: error magnitude, direction of change of error and trend change error. Journal of Travel Research 1991, 30(2):26-33.
36. World Tourism Organization. http://www.world-tourism.org.