Scenario forecasting for global tourism
This study provides innovative forecasts of the probabilities of certain scenarios of tourism demand. The scenarios of interest are constructed in relation to tourism growth and economic growth. The probability forecasts based on these scenarios provide valuable information for destination policymak...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://eprints.nottingham.ac.uk/60947/ |
| _version_ | 1848799824870113280 |
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| author | Wu, Doris Chenguang Cao, Zheng Wen, Long Song, Haiyan |
| author_facet | Wu, Doris Chenguang Cao, Zheng Wen, Long Song, Haiyan |
| author_sort | Wu, Doris Chenguang |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | This study provides innovative forecasts of the probabilities of certain scenarios of tourism demand. The scenarios of interest are constructed in relation to tourism growth and economic growth. The probability forecasts based on these scenarios provide valuable information for destination policymakers. The time-varying parameter panel vector autoregressive (TVP-PVAR) model is adopted for scenario forecasting. Both the accuracy rate and the Brier score are used to evaluate the forecasting performance. A global set of 25 tourism destinations is empirically examined, and the results confirm that the TVP-PVAR model with a time-varying error covariance matrix is generally a promising tool for forecasting. Our study contributes to tourism forecasting literature in advocating the use of scenario forecasting to facilitate industry decision-making in situations wherein forecasts are defined by two or more dimensions simultaneously. In addition, it is the first study to introduce the TVP-PVAR model to tourism demand forecasting. |
| first_indexed | 2025-11-14T20:41:49Z |
| format | Article |
| id | nottingham-60947 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:41:49Z |
| publishDate | 2020 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-609472020-06-22T02:14:37Z https://eprints.nottingham.ac.uk/60947/ Scenario forecasting for global tourism Wu, Doris Chenguang Cao, Zheng Wen, Long Song, Haiyan This study provides innovative forecasts of the probabilities of certain scenarios of tourism demand. The scenarios of interest are constructed in relation to tourism growth and economic growth. The probability forecasts based on these scenarios provide valuable information for destination policymakers. The time-varying parameter panel vector autoregressive (TVP-PVAR) model is adopted for scenario forecasting. Both the accuracy rate and the Brier score are used to evaluate the forecasting performance. A global set of 25 tourism destinations is empirically examined, and the results confirm that the TVP-PVAR model with a time-varying error covariance matrix is generally a promising tool for forecasting. Our study contributes to tourism forecasting literature in advocating the use of scenario forecasting to facilitate industry decision-making in situations wherein forecasts are defined by two or more dimensions simultaneously. In addition, it is the first study to introduce the TVP-PVAR model to tourism demand forecasting. 2020-06-15 Article PeerReviewed application/pdf en cc_by https://eprints.nottingham.ac.uk/60947/1/Submission_12%20Feb_final.pdf Wu, Doris Chenguang, Cao, Zheng, Wen, Long and Song, Haiyan (2020) Scenario forecasting for global tourism. Journal of Hospitality & Tourism Research . p. 109634802091999. ISSN 1096-3480 scenario forecasting time-varying parameter panel vector autoregressive tourism growth economic growth Brier score http://dx.doi.org/10.1177/1096348020919990 doi:10.1177/1096348020919990 doi:10.1177/1096348020919990 |
| spellingShingle | scenario forecasting time-varying parameter panel vector autoregressive tourism growth economic growth Brier score Wu, Doris Chenguang Cao, Zheng Wen, Long Song, Haiyan Scenario forecasting for global tourism |
| title | Scenario forecasting for global tourism |
| title_full | Scenario forecasting for global tourism |
| title_fullStr | Scenario forecasting for global tourism |
| title_full_unstemmed | Scenario forecasting for global tourism |
| title_short | Scenario forecasting for global tourism |
| title_sort | scenario forecasting for global tourism |
| topic | scenario forecasting time-varying parameter panel vector autoregressive tourism growth economic growth Brier score |
| url | https://eprints.nottingham.ac.uk/60947/ https://eprints.nottingham.ac.uk/60947/ https://eprints.nottingham.ac.uk/60947/ |