Can multi-source heterogeneous data improve the forecasting performance of tourist arrivals amid COVID-19? : mixed-data sampling approach / Jing Wu, Mingchen Li, Erlong Zhao, Shaolong Sun, Shouyang Wang
| Medienart: |
Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:98 |
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| Enthalten in: |
Tourism management - 98(2023) vom: Okt., Seite 1-17 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Wu, Jing [VerfasserIn] |
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| Themen: |
GDFM |
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| doi: |
10.1016/j.tourman.2023.104759 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
1851565272 |
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| 245 | 1 | 0 | |a Can multi-source heterogeneous data improve the forecasting performance of tourist arrivals amid COVID-19? |b mixed-data sampling approach |c Jing Wu, Mingchen Li, Erlong Zhao, Shaolong Sun, Shouyang Wang |
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| 650 | 4 | |a Tourism demand forecasting |7 (dpeaa)DE-206 | |
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| 700 | 1 | |a Zhao, Erlong |e verfasserin |4 aut | |
| 700 | 1 | |a Sun, Shaolong |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Shouyang |e verfasserin |4 aut | |
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| 982 | |2 26 |1 00 |x DE-206 |b The coronavirus disease (COVID-19) pandemic has already caused enormous damage to the global economy and various industries worldwide, especially the tourism industry. In the post-pandemic era, accurate tourism demand recovery forecasting is a vital requirement for a thriving tourism industry. Therefore, this study mainly focuses on forecasting tourist arrivals from mainland China to Hong Kong. A new direction in tourism demand recovery forecasting employs multi-source heterogeneous data comprising economy-related variables, search query data, and online news data to motivate the tourism destination forecasting system. The experimental results confirm that incorporating multi-source heterogeneous data can substantially strengthen the forecasting accuracy. Specifically, mixed data sampling (MIDAS) models with different data frequencies outperformed the benchmark models. | ||