Big data analytics and forecasting in hospitality and tourism / / guest editors Doris Chenguang Wu, Ji Wu and Haiyan Song
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| Titolo: |
Big data analytics and forecasting in hospitality and tourism / / guest editors Doris Chenguang Wu, Ji Wu and Haiyan Song
|
| Pubblicazione: | [Place of publication not identified] : , : Emerald Publishing Limited, , 2021 |
| Descrizione fisica: | 1 online resource (389 pages) |
| Disciplina: | 910.68 |
| Soggetto topico: | Tourism - Management |
| Tourism - Marketing | |
| Persona (resp. second.): | WuDoris Chenguang |
| WuJi | |
| SongHaiyan | |
| Nota di contenuto: | Cover -- Guest editorial -- Tourism demand nowcasting using a LASSO-MIDAS model -- Forecasting daily attraction demand using big data from search engines and social media -- High-frequency forecasting from mobile devices' bigdata: an application to tourism destinations' crowdedness -- A segmented machine learning modeling approach of social media for predicting occupancy -- Which search queries are more powerful in tourism demand forecasting: searches via mobile device or PC? -- Timing matters: crisis severity and occupancy rate forecasts in social unrest periods -- Are environmental-related online reviews more helpful? A big data analytics approach -- Listening to your employees: analyzing opinions from online reviews of hotel companies -- Artificial intelligence for hospitality big data analytics: developing a prediction model of restaurant review helpfulness for customer decision-making -- Asymmetric relationship between customer sentiment and online hotel ratings: the moderating effects of review characteristics -- Toward travel pattern aware tourism region planning: a big data approach -- Extracting revisit intentions from social media big data: a rule-based classification model -- Spatial-temporal evolution patterns of hotels in China:1978-2018 -- Destination image through social media analytics and survey method -- Do the flipped impacts of hotels matter to the popularity of Airbnb? -- The decision tree for longer-stay hotel guest: the relationship between hotel booking determinants and geographical distance -- Using social media photos as a proxy to estimate the recreational value of (im)movable heritage: the Rubjerg Knude(Denmark) lighthouse. |
| Titolo autorizzato: | Big data analytics and forecasting in hospitality and tourism |
| ISBN: | 1-80262-510-0 |
| Formato: | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9910818644703321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |
Serie:
International Journal of Contemporary Hospitality Management