Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/32005
Title: Modeling tourism demand : a decision rules based approach
Authors: Law, R 
Goh, C
Pine, R
Keywords: Condition attributes
Decision attribute
Information table
Rough sets
Tourism demand forecasting
Issue Date: 2014
Publisher: Taylor and Francis
Source: In G Zheng (Ed.), Management science applications in tourism and hospitality, p. 986-996. Taylor & Francis, 2014 How to cite?
Abstract: Most of the existing studies on tourism demand forecasting apply economic models that usemathematical functions, which require many statistical assumptions and limitations. This paper presents a new approach that applies the rough sets theory to form a forecasting model for tourism demand. The objective of this research is to create patterns which are able to distinguish between the classes of arrivals in terms of volume, based upon differences in the characteristics in each arrival. The information about the arrivals was organized in an Information Table where the number of arrivals corresponds to condition attributes, and the classification was defined by a decision attribute that indicated the forecast categorical value of future arrivals. Utilizing Japanese arrivals data in Hong Kong, empirical results showed the induced decision rules could accurately forecast (86.5%) of the test data.
URI: http://hdl.handle.net/10397/32005
ISBN: 978-131578247-8
DOI: 10.4324/9781315782478
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