Measuring daily tourism mobility spillover at the intra-metropolis level with mobile positioning data
Although tourism mobility spillover continues to be a key indicator for tourism management, more innovative research must be conducted at the micro level and high sampling frequency. Against the backdrop of an increasing number of global cities, in this paper, we evaluate the daily tourism mobility...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
|
| Series: | Regional Studies, Regional Science |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/21681376.2024.2412015 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846114498473099264 |
|---|---|
| author | Nicola Camatti Giulia Carallo Roberto Casarin Xiang Feng |
| author_facet | Nicola Camatti Giulia Carallo Roberto Casarin Xiang Feng |
| author_sort | Nicola Camatti |
| collection | DOAJ |
| description | Although tourism mobility spillover continues to be a key indicator for tourism management, more innovative research must be conducted at the micro level and high sampling frequency. Against the backdrop of an increasing number of global cities, in this paper, we evaluate the daily tourism mobility spillover inside a worldwide city of China: Shanghai. Based on the Granger causal network model and an original mobile positioning dataset, we analyse the causal relationship between local tourism flows and the spillover effects of tourism mobility within Shanghai. By categorising tourists into ‘local tourists from Shanghai’ and ‘tourists from out of Shanghai’, we reveal a significant causal relationship between Shanghai districts and flows generated by ‘tourists from out of Shanghai’. The analysis of the causal network structure also reveals key districts and points of interest that significantly contribute to congestion in tourism mobility and Shanghai's dynamics. This econometric approach offers policymakers a valuable tool to monitor mobility drivers and optimise flows within the city. |
| format | Article |
| id | doaj-art-1bee4fd3831c4e97a051ac829377a15d |
| institution | Kabale University |
| issn | 2168-1376 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Regional Studies, Regional Science |
| spelling | doaj-art-1bee4fd3831c4e97a051ac829377a15d2024-12-20T09:37:14ZengTaylor & Francis GroupRegional Studies, Regional Science2168-13762024-12-0111170172310.1080/21681376.2024.2412015Measuring daily tourism mobility spillover at the intra-metropolis level with mobile positioning dataNicola Camatti0Giulia Carallo1Roberto Casarin2Xiang Feng3Department of Economics, Ca’ Foscari University of Venice, Venice, ItalyDepartment of Economics, Ca’ Foscari University of Venice, Venice, ItalyDepartment of Economics, Ca’ Foscari University of Venice, Venice, ItalyUrban Science and Regional Planning Department, School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai, People’s Republic of ChinaAlthough tourism mobility spillover continues to be a key indicator for tourism management, more innovative research must be conducted at the micro level and high sampling frequency. Against the backdrop of an increasing number of global cities, in this paper, we evaluate the daily tourism mobility spillover inside a worldwide city of China: Shanghai. Based on the Granger causal network model and an original mobile positioning dataset, we analyse the causal relationship between local tourism flows and the spillover effects of tourism mobility within Shanghai. By categorising tourists into ‘local tourists from Shanghai’ and ‘tourists from out of Shanghai’, we reveal a significant causal relationship between Shanghai districts and flows generated by ‘tourists from out of Shanghai’. The analysis of the causal network structure also reveals key districts and points of interest that significantly contribute to congestion in tourism mobility and Shanghai's dynamics. This econometric approach offers policymakers a valuable tool to monitor mobility drivers and optimise flows within the city.https://www.tandfonline.com/doi/10.1080/21681376.2024.2412015Spillover effectstourismintra-metropolis mobilityGranger causal networkmobile positioningShanghai |
| spellingShingle | Nicola Camatti Giulia Carallo Roberto Casarin Xiang Feng Measuring daily tourism mobility spillover at the intra-metropolis level with mobile positioning data Regional Studies, Regional Science Spillover effects tourism intra-metropolis mobility Granger causal network mobile positioning Shanghai |
| title | Measuring daily tourism mobility spillover at the intra-metropolis level with mobile positioning data |
| title_full | Measuring daily tourism mobility spillover at the intra-metropolis level with mobile positioning data |
| title_fullStr | Measuring daily tourism mobility spillover at the intra-metropolis level with mobile positioning data |
| title_full_unstemmed | Measuring daily tourism mobility spillover at the intra-metropolis level with mobile positioning data |
| title_short | Measuring daily tourism mobility spillover at the intra-metropolis level with mobile positioning data |
| title_sort | measuring daily tourism mobility spillover at the intra metropolis level with mobile positioning data |
| topic | Spillover effects tourism intra-metropolis mobility Granger causal network mobile positioning Shanghai |
| url | https://www.tandfonline.com/doi/10.1080/21681376.2024.2412015 |
| work_keys_str_mv | AT nicolacamatti measuringdailytourismmobilityspilloverattheintrametropolislevelwithmobilepositioningdata AT giuliacarallo measuringdailytourismmobilityspilloverattheintrametropolislevelwithmobilepositioningdata AT robertocasarin measuringdailytourismmobilityspilloverattheintrametropolislevelwithmobilepositioningdata AT xiangfeng measuringdailytourismmobilityspilloverattheintrametropolislevelwithmobilepositioningdata |