Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/21785
Title: Modeling tourism demand
Authors: Law, R 
Goh, C
Pine, R
Keywords: Tourism demand forecasting
Rough sets
Information Table
Condition attributes
Decision attribute
Issue Date: 2004
Publisher: Routledge, Taylor & Francis Group
Source: Journal of travel & tourism marketing, 2004, v. 16, no. 2-3, p. 61-69 How to cite?
Journal: Journal of travel & tourism marketing 
Abstract: Most of the existing studies on tourism demand forecasting apply economic models that use mathematical 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/10397/21785
ISSN: 1054-8408
EISSN: 1540-7306
DOI: 10.1300/J073v16n02_05
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