Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/99268
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | School of Hotel and Tourism Management | en_US |
| dc.creator | Liu, H | en_US |
| dc.creator | Gao, C | en_US |
| dc.creator | Tsai, H | en_US |
| dc.date.accessioned | 2023-07-04T08:29:58Z | - |
| dc.date.available | 2023-07-04T08:29:58Z | - |
| dc.identifier.issn | 1354-8166 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/99268 | - |
| dc.language.iso | en | en_US |
| dc.publisher | SAGE Publications | en_US |
| dc.rights | This is the accepted version of the publication Liu, H., Gao, C., & Tsai, H. (2024). Spatial spillover and determinants of tourism efficiency: A low carbon emission perspective. Tourism Economics, 30(3), 543-566. Copyright © 2023 (The Author(s)). DOI: 10.1177/13548166231167045. | en_US |
| dc.subject | Bootstrap slacks-based measure model | en_US |
| dc.subject | Carbon emission | en_US |
| dc.subject | Spatial Durbin model | en_US |
| dc.subject | Spatial spillover effect | en_US |
| dc.subject | Tourism carbon efficiency | en_US |
| dc.title | Spatial spillover and determinants of tourism efficiency : a low carbon emission perspective | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.spage | 543 | en_US |
| dc.identifier.epage | 566 | en_US |
| dc.identifier.volume | 30 | en_US |
| dc.identifier.issue | 3 | en_US |
| dc.identifier.doi | 10.1177/13548166231167045 | en_US |
| dcterms.abstract | This paper measures tourism carbon efficiency (TCE) in China by incorporating energy consumption and carbon dioxide (CO2) emissions into an efficiency assessment framework, and to further investigate the determinants of TCE by considering the spatial spillover effects. To do this, a bootstrap slacks-based measure (SBM) model was applied to assess the TCE in 30 provincial-level administrative regions of China from 2008 to 2019. Next, the Moran’s index and spatial Durbin model (SDM) were adopted to explore the spatial distribution and determinants of TCE. The results indicate that regional differences affect the level of China’s TCE, as do spatial spillover effects. In addition, technology innovation, urbanization rate, and government support positively affect TCE. In contrast, economic growth negatively affects TCE. Educational attainment, green infrastructure, and government support have a negative spatial spillover effect on TCE. Transportation infrastructure has a negative total effect on TCE. | en_US |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Tourism economics, May 2024, v. 30, no. 3, p. 543-566 | en_US |
| dcterms.isPartOf | Tourism economics | en_US |
| dcterms.issued | 2024-05 | - |
| dc.identifier.scopus | 2-s2.0-85152284921 | - |
| dc.identifier.eissn | 2044-0375 | en_US |
| dc.description.validate | 202306 bcww | en_US |
| dc.description.oa | Accepted Manuscript | en_US |
| dc.identifier.FolderNumber | a2150 | - |
| dc.identifier.SubFormID | 46797 | - |
| dc.description.fundingSource | RGC | en_US |
| dc.description.fundingSource | Others | en_US |
| dc.description.fundingText | Others: National Natural Science Foundation of China; Key project of Anhui Philosophy and Social Science Planning Fund; Innovation Development of Anhui Social Science; Research Fund for University Postgraduate | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.description.oaCategory | Green (AAM) | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Liu_Spatial_Spillover_Determinants.pdf | Pre-Published version | 1.16 MB | Adobe PDF | View/Open |
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