The methodological progress of tourism demand forecasting: A review of related literature

Carey Goh, Chun Hung Roberts Law

Research output: Journal article publicationJournal articleAcademic researchpeer-review

55 Citations (Scopus)

Abstract

Research on modeling the estimation and forecasting of tourism demand has evolved with increasing sophistication and improved quality. In this study, 155 research papers published between 1995 and 2009 were identified and were classified into three main groups according to the methods and techniques adopted-an econometric-based approach, time series techniques, and artificial intelligence (AI)-based methods. It appears that the more advanced methods such as cointegration, error correction model, time varying parameter model, and their combinations with systems of equations produce better results in terms of forecasting accuracy. We also discuss the implications and suggest future directions of tourism research techniques and methods.
Original languageEnglish
Pages (from-to)296-317
Number of pages22
JournalJournal of Travel and Tourism Marketing
Volume28
Issue number3
DOIs
Publication statusPublished - 1 Apr 2011

Keywords

  • Artificial intelligence
  • Econometrics
  • Review
  • Time series
  • Tourism demand modeling

ASJC Scopus subject areas

  • Tourism, Leisure and Hospitality Management
  • Marketing

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