Back to results

Victoria University

Identifying and predicting turning points in Australian inbound tourism demand growth

Abstract

dc:description.abstract

This study identifies the importance of forecasting turning points in tourism demand. Recognising the limitations of the current linear models in use, and the lack of adequate research in turning point prediction in tourism, the objective of this study is to forecast turning points in tourism demand accurately by applying nonlinear models such as Logit, Probit and Markov Switching and the Leading Indicator approach. The specific aim of this study is to forecast turning points in Australian inbound tourism demand growth caused by ‘economic factors’ within both the tourism generating country and destination country (Australia). This objective of this study is achieved by establishing that Logit and Probit models can be used effectively in turning point forecasting of tourism demand.

Degree

thesis:*
Name dc:type.qualificationname
phd
Level dc:type.qualificationlevel
doctoral
Grantor dc:publisher.institution
Victoria University
Year dc:date.issued
2010

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Fernando, Emmanuel

Subjects

dc:subject × 2

Rights

Language dc:language
en

Chain of custody

source
Harvested from
Victoria University (Australia)
Base URL
vuir.vu.edu.au/cgi/oai2
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Fernando, Emmanuel. Identifying and predicting turning points in Australian inbound tourism demand growth. doctoral thesis, Victoria University, 2010.