Modeling tourism demand: A decision rules based approach

Chun Hung Roberts Law, Carey Goh, Ray Pine

Research output: Journal article publicationJournal articleAcademic researchpeer-review

7 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)61-69
Number of pages9
JournalJournal of Travel and Tourism Marketing
Volume16
Issue number2-3
DOIs
Publication statusPublished - 1 Jul 2004
Externally publishedYes

Keywords

  • Condition attributes
  • Decision attribute
  • Information Table
  • Rough sets
  • Tourism demand forecasting

ASJC Scopus subject areas

  • Tourism, Leisure and Hospitality Management
  • Marketing

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