Regional data forecasting accuracy: The case of Thailand
Article Abstract:
Data on guest arrivals at accommodation establishments in nine city-based regions in Thailand from 1996 to 2002 are analyzed to determine whether such sub regional data can provide accurate tourist arrival forecasts, in absolute and relative terms, to cross-border flow data. The accuracy of the regional forecasting of tourist arrivals, both international and domestic, enables accurate forecasting of regional tourism demand in Thailand, and also in China and India where such data are available.
Publication Name: Journal of Travel Research
Subject: Travel industry
ISSN: 0047-2875
Year: 2006
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Forecasting short time-series tourism demand with artificial intelligence models
Article Abstract:
A study investigates the accuracy of fuzzy time series and grey theory artificial intelligence (AI) models in forecasting annual tourist arrivals to the US and compares their performance with that of the traditional and simple double moving average and double exponential smoothing methods. Findings indicate that the complicated, expensive AI models are not likely to generate more accurate forecasting than the simple models, and should be adopted only after careful consideration.
Publication Name: Journal of Travel Research
Subject: Travel industry
ISSN: 0047-2875
Year: 2006
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Analyzing and forecasting tourism demand: a rough sets approach
Article Abstract:
The study examines the rough sets approach to tourism demand analysis and evaluates the qualitative non-economic factors influencing forecasting demand. The results indicate that leisure time and climate have a stronger impact on tourist arrivals compared to economic factors.
Publication Name: Journal of Travel Research
Subject: Travel industry
ISSN: 0047-2875
Year: 2008
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