Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/89470
DC Field | Value | Language |
---|---|---|
dc.contributor | School of Hotel and Tourism Management | - |
dc.creator | Assaf, AG | - |
dc.creator | Li, G | - |
dc.creator | Song, H | - |
dc.creator | Tsionas, MG | - |
dc.date.accessioned | 2021-04-09T08:49:41Z | - |
dc.date.available | 2021-04-09T08:49:41Z | - |
dc.identifier.issn | 0047-2875 | - |
dc.identifier.uri | http://hdl.handle.net/10397/89470 | - |
dc.language.iso | en | en_US |
dc.publisher | SAGE Publications | en_US |
dc.rights | This is the accepted version of the publication Assaf, A. G., Li, G., Song, H., & Tsionas, M. G., Modeling and forecasting regional tourism demand using the bayesian global vector autoregressive (BGVAR) model, Journal of Travel Research (Volume 58 and issue 3) pp. 383-397. Copyright © 2018 (The Author(s)). DOI: 10.1177/0047287518759226. | en_US |
dc.subject | Bayesian global VAR | en_US |
dc.subject | forecasting | en_US |
dc.subject | impulse response analysis | en_US |
dc.subject | Southeast Asia | en_US |
dc.subject | Spillover | en_US |
dc.subject | tourism demand | en_US |
dc.title | Modeling and forecasting regional tourism demand using the Bayesian Global Vector Autoregressive (BGVAR) model | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 383 | - |
dc.identifier.epage | 397 | - |
dc.identifier.volume | 58 | - |
dc.identifier.issue | 3 | - |
dc.identifier.doi | 10.1177/0047287518759226 | - |
dcterms.abstract | Increasing levels of global and regional integration have led to tourist flows between countries becoming closely linked. These links should be considered when modeling and forecasting international tourism demand within a region. This study introduces a comprehensive and accurate systematic approach to tourism demand analysis, based on a Bayesian global vector autoregressive (BGVAR) model. An empirical study of international tourist flows in nine countries in Southeast Asia demonstrates the ability of the BGVAR model to capture the spillover effects of international tourism demand in this region. The study provides clear evidence that the BGVAR model consistently outperforms three other alternative VAR model versions throughout one- to four-quarters-ahead forecasting horizons. The potential of the BGVAR model in future applications is demonstrated by its superiority in both modeling and forecasting tourism demand. | - |
dcterms.accessRights | open access | - |
dcterms.bibliographicCitation | Journal of travel research, 1 Mar. 2019, v. 58, no. 3, p. 383-397 | - |
dcterms.isPartOf | Journal of travel research | - |
dcterms.issued | 2019-03-01 | - |
dc.identifier.scopus | 2-s2.0-85044053309 | - |
dc.identifier.eissn | 1552-6763 | - |
dc.description.validate | 202104 bcvc | - |
dc.description.oa | Accepted Manuscript | - |
dc.identifier.FolderNumber | a0681-n09 | - |
dc.identifier.SubFormID | 889 | - |
dc.description.fundingSource | RGC | - |
dc.description.fundingText | PolyU 155014/5B | - |
dc.description.pubStatus | Published | - |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
15. BGVAR_Assaf_et_al.pdf | Pre-Published version | 1.59 MB | Adobe PDF | View/Open |
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