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dc.contributor.authorLim, C.
dc.contributor.authorChan, Felix
dc.contributor.editorAnderssen, R.S., R.D. Braddock and L.T.H. Newham
dc.date.accessioned2017-01-30T10:58:07Z
dc.date.available2017-01-30T10:58:07Z
dc.date.created2015-03-03T20:13:47Z
dc.date.issued2009
dc.identifier.citationLim, C. and Chan, F. 2009. Forecasting tourist accommodation demand in New Zealand, in Anderssen, R.S., R.D. Braddock and L.T.H. Newham (ed), 18th World IMACS / MODSIM Congress, Jul 13 2009, pp. 1251-1257. Cairns, Australia: The Modelling and Simulation Society of Australia and New Zealand Inc..
dc.identifier.urihttp://hdl.handle.net/20.500.11937/7159
dc.description.abstract

Tourism accounts for about 9% of New Zealand’s Gross Domestic Product, 10% ofemployment and 18% of export earnings in 2007 (Ministry of Tourism, 2008a). The industry is NewZealand’s largest export earner and its major tourist source markets include Australia, UK, USA, Japan and China. International and domestic tourists in New Zealand use a range of accommodation in their travel, from private homes to commercial and other accommodation. Tourist accommodation types are classified under the following five categories: hotels (include resorts), motels (motor inns, apartments and motels), hosted (private hotels, guesthouses, bed and breakfast and farm stays), backpackers/hostels, and caravan parks/camping grounds (Ministry of Tourism, 2008b). Figure 1 shows that tourist accommodation available from 1997 to 2007 is predominantly hotels and motels.Seasonality has attracted considerable interest in empirical tourism research and forecasting. However, the analysis of such recurring phenomenon is sparse in hospitality research, with only one study to date having analysed seasonal unit roots prior to forecasting guest nights for the tourist lodging industry. This paper examines the seasonality of hotel-motel occupancy in New Zealand using monthly time series from 1997 to 2007. The presence of seasonal unit roots is detected using the HEGY procedures. Numerous Box-Jenkins models are estimated and the twelve differenced SARMA(2,2)(0,2)12 is the optimal model selected to forecast hotel-motel room nights.

dc.publisherThe Modelling and Simulation Society of Australia and New Zealand Inc.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectHEGY procedures
dc.subjectSeasonality
dc.subjectunit roots
dc.subjectnonstationarity
dc.subjectforecasting hotel-motel room nights
dc.titleForecasting tourist accommodation demand in New Zealand
dc.typeConference Paper
dcterms.source.startPage1251
dcterms.source.endPage1257
dcterms.source.titleInterfacing modelling and simulation with mathematical and computational sciences
dcterms.source.seriesInterfacing modelling and simulation with mathematical and computational sciences
dcterms.source.isbn978-0-9758400-7-8
dcterms.source.conference18th World IMACS / MODSIM Congress
dcterms.source.conference-start-dateJul 13 2009
dcterms.source.conferencelocationCairns, Australia
dcterms.source.placeAustralia
curtin.departmentSchool of Economics and Finance
curtin.accessStatusOpen access
curtin.contributor.orcidChan, Felix [0000-0003-3045-7178]
curtin.contributor.scopusauthoridChan, Felix [7202586446]


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