Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/98457
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | School of Hotel and Tourism Management | en_US |
| dc.creator | Chen, J | en_US |
| dc.creator | Becken, S | en_US |
| dc.creator | Stantic, B | en_US |
| dc.date.accessioned | 2023-05-04T07:09:04Z | - |
| dc.date.available | 2023-05-04T07:09:04Z | - |
| dc.identifier.uri | http://hdl.handle.net/10397/98457 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Elsevier Ltd | en_US |
| dc.rights | © 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). | en_US |
| dc.rights | The following publication Chen, J., Becken, S., & Stantic, B. (2022). Harnessing social media to understand tourist travel patterns in muti-destinations. Annals of Tourism Research Empirical Insights, 3(2), 100079 is available at https://doi.org/10.1016/j.annale.2022.100079. | en_US |
| dc.subject | Travel patterns | en_US |
| dc.subject | Social network analysis | en_US |
| dc.subject | Social media | en_US |
| dc.subject | Core-periphery theory | en_US |
| dc.subject | Centrality | en_US |
| dc.title | Harnessing social media to understand tourist travel patterns in muti-destinations | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.volume | 3 | en_US |
| dc.identifier.issue | 2 | en_US |
| dc.identifier.doi | 10.1016/j.annale.2022.100079 | en_US |
| dcterms.abstract | Understanding travel patterns is helpful for decision-makers to draw insights from consumers' perspectives. This work took advantage of social media and analysed tourists' travel patterns from the length of itineraries and duration of stay. Using Chinese tourists in Australia as a case study, results showed that most visitors prefer to stay in two core destinations, with an average duration of 8.5 days, while adding one destination increases the stay by around 2.5 days and caps at approximately 14 days. The travel patterns were further analysed by social network analysis and explained the network structure using core-periphery theory. The results were compared with official national survey data and demonstrated encouraging accuracy, which provides practical implications for destination planning and management. | en_US |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Annals of tourism research empirical insights, Nov. 2022, v. 3, no. 2, 100079 | en_US |
| dcterms.isPartOf | Annals of tourism research empirical insights | en_US |
| dcterms.issued | 2022-11 | - |
| dc.identifier.eissn | 2666-9579 | en_US |
| dc.identifier.artn | 100079 | en_US |
| dc.description.validate | 202305 bckw | en_US |
| dc.description.oa | Version of Record | en_US |
| dc.identifier.FolderNumber | OA_Others | - |
| dc.description.fundingSource | Not mention | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.description.oaCategory | CC | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 1-s2.0-S2666957922000477-main.pdf | 1.66 MB | Adobe PDF | View/Open |
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