Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/93083
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | School of Hotel and Tourism Management | en_US |
| dc.creator | Liu, A | en_US |
| dc.creator | Lin, VS | en_US |
| dc.creator | Li, G | en_US |
| dc.creator | Song, H | en_US |
| dc.date.accessioned | 2022-06-09T06:13:43Z | - |
| dc.date.available | 2022-06-09T06:13:43Z | - |
| dc.identifier.issn | 0047-2875 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/93083 | - |
| dc.language.iso | en | en_US |
| dc.publisher | SAGE Publications | en_US |
| dc.rights | This is the accepted version of the publication Liu, A., Lin, V. S., Li, G., & Song, H., Ex ante tourism forecasting assessment, Journal of Travel Research (Volume: 61 issue: 1) pp. 64-75. Copyright © 2020 (The Author(s)). DOI: 10.1177/0047287520974456 | en_US |
| dc.subject | Data characteristics | en_US |
| dc.subject | Ex ante forecasts | en_US |
| dc.subject | Forecasting errors | en_US |
| dc.subject | Forecasting horizons | en_US |
| dc.subject | International tourism demand | en_US |
| dc.title | Ex ante tourism forecasting assessment | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.spage | 64 | en_US |
| dc.identifier.epage | 75 | en_US |
| dc.identifier.volume | 61 | en_US |
| dc.identifier.issue | 1 | en_US |
| dc.identifier.doi | 10.1177/0047287520974456 | en_US |
| dcterms.abstract | Although numerous studies have focused on forecasting international tourism demand, minimal light has been shed on the factors influencing the accuracy of real-world ex ante forecasting. This study evaluates the forecasting errors across various prediction horizons by analyzing the annually published forecasts of the Pacific Asia Tourism Association (PATA) from 2013 to 2017, comprising 765 origin–destination pairs covering 31 destinations in the region. The regression analysis shows that the variation in tourism demand and gross domestic product (GDP), covariation between tourism demand and GDP, order of lagged variables, origin, destination, and forecasting method all have significant effects on the forecasting accuracy over different horizons. This suggests that tourism forecasting should account for these factors in the future. | en_US |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Journal of travel research, Jan. 2022, v. 61, no. 1, p. 64-75 | en_US |
| dcterms.isPartOf | Journal of travel research | en_US |
| dcterms.issued | 2022-01 | - |
| dc.identifier.scopus | 2-s2.0-85096819026 | - |
| dc.identifier.eissn | 1552-6763 | en_US |
| dc.description.validate | 202206 bckw | en_US |
| dc.description.oa | Accepted Manuscript | en_US |
| dc.identifier.FolderNumber | SHTM-0155 | - |
| dc.description.fundingSource | Others | en_US |
| dc.description.fundingText | The Hong Kong Polytechnic University | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.identifier.OPUS | 49919703 | - |
| dc.description.oaCategory | Green (AAM) | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Song_Tourism_Forecasting_Assessment.pdf | Pre-Published version | 1.56 MB | Adobe PDF | View/Open |
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