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Forecasting tourism demand with multisource big data

Citations

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Cited by:

  1. Li, Cheng & Zheng, Weimin & Ge, Peng, 2022. "Tourism demand forecasting with spatiotemporal features," Annals of Tourism Research, Elsevier, vol. 94(C).
  2. Edmond H. C. Wu & Jihao Hu & Rui Chen, 2022. "Monitoring and forecasting COVID-19 impacts on hotel occupancy rates with daily visitor arrivals and search queries," Current Issues in Tourism, Taylor & Francis Journals, vol. 25(3), pages 490-507, February.
  3. Zheng, Weimin & Huang, Liyao & Lin, Zhibin, 2021. "Multi-attraction, hourly tourism demand forecasting," Annals of Tourism Research, Elsevier, vol. 90(C).
  4. Cheng, Yingyi & Zhao, Bing & Peng, Siqi & Li, Kai & Yin, Yue & Zhang, Jinguang, 2024. "Effects of cultural landscape service features in national forest parks on visitors’ sentiments: A nationwide social media-based analysis in China," Ecosystem Services, Elsevier, vol. 67(C).
  5. Jiao, Xiaoying & Chen, Jason Li & Li, Gang, 2021. "Forecasting tourism demand: Developing a general nesting spatiotemporal model," Annals of Tourism Research, Elsevier, vol. 90(C).
  6. Liu, Congzheng & Letchford, Adam N. & Svetunkov, Ivan, 2022. "Newsvendor problems: An integrated method for estimation and optimisation," European Journal of Operational Research, Elsevier, vol. 300(2), pages 590-601.
  7. Ruochen Yang, 2023. "Use and Experience of Tourism Green Spaces in Ishigaki City before and during the COVID-19 Pandemic Based on Web Review Data," Sustainability, MDPI, vol. 15(12), pages 1-24, June.
  8. Jianxin Zhang & Yuting Yan & Jinyue Zhang & Peixue Liu & Li Ma, 2023. "Investigating the Spatial-Temporal Variation of Pre-Trip Searching in an Urban Agglomeration," Sustainability, MDPI, vol. 15(14), pages 1-17, July.
  9. Park, Eunhye & Park, Jinah & Hu, Mingming, 2021. "Tourism demand forecasting with online news data mining," Annals of Tourism Research, Elsevier, vol. 90(C).
  10. Dimitrios Belias & Sawsan Malik & Ioannis Rossidis & Christos Mantas, 2021. "The Use of Big Data in Tourism: Current Trends and Directions for Future Research," Academic Journal of Interdisciplinary Studies, Richtmann Publishing Ltd, vol. 10, September.
  11. Maksim Godovykh & Jorge Ridderstaat & Carissa Baker & Alan Fyall, 2021. "COVID-19 and Tourism: Analyzing the Effects of COVID-19 Statistics and Media Coverage on Attitudes toward Tourism," Forecasting, MDPI, vol. 3(4), pages 1-14, November.
  12. Gao, Feng & Chi, Hong & Shao, Xueyan, 2021. "Forecasting residential electricity consumption using a hybrid machine learning model with online search data," Applied Energy, Elsevier, vol. 300(C).
  13. Doris Chenguang Wu & Shiteng Zhong & Richard T R Qiu & Ji Wu, 2022. "Are customer reviews just reviews? Hotel forecasting using sentiment analysis," Tourism Economics, , vol. 28(3), pages 795-816, May.
  14. Ying Zhang & Jiehang Song & Angelo Sciacca & Jin Chan & Xiaoguang Qi, 2022. "Novel Sentiment Lexica Derived from User Generating Content by Chinese Tourists in Pacific Islands," Sustainability, MDPI, vol. 14(23), pages 1-23, November.
  15. You-Hai Lu & Peixue Liu & Xiaowan Zhang & Jun Zhang & Caiyun Shen, 2022. "Spatial-Temporal Differences in the Effect of Epidemic Risk Perception on Potential Travel Intention: A Macropsychology-Based Risk Perception Perspective," SAGE Open, , vol. 12(4), pages 21582440221, December.
  16. Gunter, Ulrich & Zekan, Bozana, 2021. "Forecasting air passenger numbers with a GVAR model," Annals of Tourism Research, Elsevier, vol. 89(C).
  17. Bulatovic, Iva & Papatheodorou, Andreas, 2023. "Civil aviation and tourism demand in Montenegro: A panel data approach," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 9(1), pages 25-36.
  18. Zhang, Yishuo & Li, Gang & Muskat, Birgit & Law, Rob & Yang, Yating, 2020. "Group pooling for deep tourism demand forecasting," Annals of Tourism Research, Elsevier, vol. 82(C).
  19. Weaver, Adam, 2021. "Tourism, big data, and a crisis of analysis," Annals of Tourism Research, Elsevier, vol. 88(C).
  20. Vatsa, Puneet, 2021. "Seasonality and cycles in tourism demand—redux," Annals of Tourism Research, Elsevier, vol. 90(C).
  21. Raniah Alsahafi & Ahmed Alzahrani & Rashid Mehmood, 2023. "Smarter Sustainable Tourism: Data-Driven Multi-Perspective Parameter Discovery for Autonomous Design and Operations," Sustainability, MDPI, vol. 15(5), pages 1-64, February.
  22. Buda Baji'c & Sr{dj}an Mili'cevi'c & Aleksandar Anti'c & Slobodan Markovi'c & Nemanja Tomi'c, 2024. "Neural Network Modeling for Forecasting Tourism Demand in Stopi\'{c}a Cave: A Serbian Cave Tourism Study," Papers 2404.04974, arXiv.org.
  23. Zhang, Yishuo & Li, Gang & Muskat, Birgit & Vu, Huy Quan & Law, Rob, 2021. "Predictivity of tourism demand data," Annals of Tourism Research, Elsevier, vol. 89(C).
  24. Jian-Wu Bi & Tian-Yu Han & Yanbo Yao, 2024. "Collaborative forecasting of tourism demand for multiple tourist attractions with spatial dependence: A combined deep learning model," Tourism Economics, , vol. 30(2), pages 361-388, March.
  25. Chuan Zhang & Ao‐Yun Hu & Yu‐Xin Tian, 2023. "Daily tourism forecasting through a novel method based on principal component analysis, grey wolf optimizer, and extreme learning machine," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2121-2138, December.
  26. Li, Hengyun & Gao, Huicai & Song, Haiyan, 2023. "Tourism forecasting with granular sentiment analysis," Annals of Tourism Research, Elsevier, vol. 103(C).
  27. Jessie Bravo & Roger Alarcón & Carlos Valdivia & Oscar Serquén, 2023. "Application of Machine Learning Techniques to Predict Visitors to the Tourist Attractions of the Moche Route in Peru," Sustainability, MDPI, vol. 15(11), pages 1-25, June.
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