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Forecasting tourism demand with composite search index

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Cited by:

  1. Binru Zhang & Yulian Pu & Yuanyuan Wang & Jueyou Li, 2019. "Forecasting Hotel Accommodation Demand Based on LSTM Model Incorporating Internet Search Index," Sustainability, MDPI, vol. 11(17), pages 1-14, August.
  2. Andreea Avramescu & Arkadiusz Wiśniowski, 2021. "Now-casting Romanian migration into the United Kingdom by using Google Search engine data," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 45(40), pages 1219-1254.
  3. Cheng Shi & Mengyang Liu & Yu Ye, 2021. "Measuring the Degree of Balance between Urban and Tourism Development: An Analytical Approach Using Cellular Data," Sustainability, MDPI, vol. 13(17), pages 1-19, August.
  4. Rodrigo Mulero & Alfredo García-Hiernaux, 2021. "Forecasting Spanish unemployment with Google Trends and dimension reduction techniques," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 12(3), pages 329-349, September.
  5. Martina Nannelli & Francesco Capone & Luciana Lazzeretti, 2022. "A bibliometric analysis on Artificial intelligence in Tourism. State of the art and future research avenues," Working Papers - Business wp2022_03.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
  6. Ziqi Yuan & Guozhu Jia, 2022. "Systematic investigation of keywords selection and processing strategy on search engine forecasting: a case of tourist volume in Beijing," Information Technology & Tourism, Springer, vol. 24(4), pages 547-580, December.
  7. Schaer, Oliver & Kourentzes, Nikolaos & Fildes, Robert, 2019. "Demand forecasting with user-generated online information," International Journal of Forecasting, Elsevier, vol. 35(1), pages 197-212.
  8. Bi, Jian-Wu & Liu, Yang & Li, Hui, 2020. "Daily tourism volume forecasting for tourist attractions," Annals of Tourism Research, Elsevier, vol. 83(C).
  9. Li, Jingjing & Tang, Ling & Wang, Shouyang, 2020. "Forecasting crude oil price with multilingual search engine data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
  10. Ling Tang & Chengyuan Zhang & Tingfei Li & Ling Li, 2021. "A novel BEMD-based method for forecasting tourist volume with search engine data," Tourism Economics, , vol. 27(5), pages 1015-1038, August.
  11. Armand Viljoen & Andrea Saayman & Melville Saayman, 2019. "Determinants influencing inbound arrivals to Africa," Tourism Economics, , vol. 25(6), pages 856-883, September.
  12. Javier Sebastian, 2016. "Blockchain in financial services: Regulatory landscape and future challenges," Working Papers 16/21, BBVA Bank, Economic Research Department.
  13. Li, Cheng & Ge, Peng & Liu, Zhusheng & Zheng, Weimin, 2020. "Forecasting tourist arrivals using denoising and potential factors," Annals of Tourism Research, Elsevier, vol. 83(C).
  14. Giovanni De Luca & Monica Rosciano, 2020. "Quantile Dependence in Tourism Demand Time Series: Evidence in the Southern Italy Market," Sustainability, MDPI, vol. 12(8), pages 1-18, April.
  15. Law, Rob & Li, Gang & Fong, Davis Ka Chio & Han, Xin, 2019. "Tourism demand forecasting: A deep learning approach," Annals of Tourism Research, Elsevier, vol. 75(C), pages 410-423.
  16. Katerina Volchek & Anyu Liu & Haiyan Song & Dimitrios Buhalis, 2019. "Forecasting tourist arrivals at attractions: Search engine empowered methodologies," Tourism Economics, , vol. 25(3), pages 425-447, May.
  17. Kulshrestha, Anurag & Krishnaswamy, Venkataraghavan & Sharma, Mayank, 2020. "Bayesian BILSTM approach for tourism demand forecasting," Annals of Tourism Research, Elsevier, vol. 83(C).
  18. A Fronzetti Colladon & B Guardabascio & R Innarella, 2021. "Using social network and semantic analysis to analyze online travel forums and forecast tourism demand," Papers 2105.07727, arXiv.org.
  19. Ming Yin & Feiya Lu & Xingxuan Zhuo & Wangzi Yao & Jialong Liu & Jijiao Jiang, 2024. "Prediction of daily tourism volume based on maximum correlation minimum redundancy feature selection and long short‐term memory network," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 344-365, March.
  20. Jimenez-Marquez, Jose Luis & Gonzalez-Carrasco, Israel & Lopez-Cuadrado, Jose Luis & Ruiz-Mezcua, Belen, 2019. "Towards a big data framework for analyzing social media content," International Journal of Information Management, Elsevier, vol. 44(C), pages 1-12.
  21. Liu, Yuan-Yuan & Tseng, Fang-Mei & Tseng, Yi-Heng, 2018. "Big Data analytics for forecasting tourism destination arrivals with the applied Vector Autoregression model," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 123-134.
  22. Wanhai You & Yuming Huang & Chien‐Chiang Lee, 2024. "Forecasting tourist flows in the COVID‐19 era using nonparametric mixed‐frequency VARs," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 473-489, March.
  23. Fatemeh Binesh & Amanda Belarmino & Carola Raab, 2021. "A meta-analysis of hotel revenue management," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(5), pages 546-558, October.
  24. Maximo Camacho & Matías José Pacce, 2018. "Forecasting travellers in Spain with Google’s search volume indices," Tourism Economics, , vol. 24(4), pages 434-448, June.
  25. Zhang, Chuan & Tian, Yu-Xin & Fan, Zhi-Ping, 2022. "Forecasting sales using online review and search engine data: A method based on PCA–DSFOA–BPNN," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1005-1024.
  26. Fei Ma & Yujie Zhu & Kum Fai Yuen & Qipeng Sun & Haonan He & Xiaobo Xu & Zhen Shang & Yan Xu, 2022. "Exploring the Spatiotemporal Evolution and Sustainable Driving Factors of Information Flow Network: A Public Search Attention Perspective," IJERPH, MDPI, vol. 19(1), pages 1-25, January.
  27. Muzi Zhang & Junyi Li & Bing Pan & Gaojun Zhang, 2018. "Weekly Hotel Occupancy Forecasting of a Tourism Destination," Sustainability, MDPI, vol. 10(12), pages 1-17, November.
  28. Han Liu & Yongjing Wang & Haiyan Song & Ying Liu, 2023. "Measuring tourism demand nowcasting performance using a monotonicity test," Tourism Economics, , vol. 29(5), pages 1302-1327, August.
  29. Haodong Sun & Yang Yang & Yanyan Chen & Xiaoming Liu & Jiachen Wang, 2023. "Tourism demand forecasting of multi-attractions with spatiotemporal grid: a convolutional block attention module model," Information Technology & Tourism, Springer, vol. 25(2), pages 205-233, June.
  30. Silva, Emmanuel Sirimal & Hassani, Hossein & Heravi, Saeed & Huang, Xu, 2019. "Forecasting tourism demand with denoised neural networks," Annals of Tourism Research, Elsevier, vol. 74(C), pages 134-154.
  31. Li, Hengyun & Hu, Mingming & Li, Gang, 2020. "Forecasting tourism demand with multisource big data," Annals of Tourism Research, Elsevier, vol. 83(C).
  32. Yang, Yang & Fan, Yawen & Jiang, Lan & Liu, Xiaohui, 2022. "Search query and tourism forecasting during the pandemic: When and where can digital footprints be helpful as predictors?," Annals of Tourism Research, Elsevier, vol. 93(C).
  33. Xu Huang & Emmanuel Silva & Hossein Hassani, 2018. "Causality between Oil Prices and Tourist Arrivals," Stats, MDPI, vol. 1(1), pages 1-21, October.
  34. Hirashima, Ashley & Jones, James & Bonham, Carl S. & Fuleky, Peter, 2017. "Forecasting in a Mixed Up World: Nowcasting Hawaii Tourism," Annals of Tourism Research, Elsevier, vol. 63(C), pages 191-202.
  35. Long Wen & Chang Liu & Haiyan Song, 2019. "Forecasting tourism demand using search query data: A hybrid modelling approach," Tourism Economics, , vol. 25(3), pages 309-329, May.
  36. Purva Grover & Arpan Kumar Kar, 2017. "Big Data Analytics: A Review on Theoretical Contributions and Tools Used in Literature," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 18(3), pages 203-229, September.
  37. Chumnumpan, Pattarin & Shi, Xiaohui, 2019. "Understanding new products’ market performance using Google Trends," Australasian marketing journal, Elsevier, vol. 27(2), pages 91-103.
  38. Eden Xiaoying Jiao & Jason Li Chen, 2019. "Tourism forecasting: A review of methodological developments over the last decade," Tourism Economics, , vol. 25(3), pages 469-492, May.
  39. 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.
  40. Wolfram Höpken & Tobias Eberle & Matthias Fuchs & Maria Lexhagen, 2019. "Google Trends data for analysing tourists’ online search behaviour and improving demand forecasting: the case of Åre, Sweden," Information Technology & Tourism, Springer, vol. 21(1), pages 45-62, March.
  41. Daxin Dong & Xiaowei Xu & Wen Xu & Junye Xie, 2019. "The Relationship Between the Actual Level of Air Pollution and Residents’ Concern about Air Pollution: Evidence from Shanghai, China," IJERPH, MDPI, vol. 16(23), pages 1-18, November.
  42. Wai Kit Tsang & Dries F. Benoit, 2020. "Gaussian processes for daily demand prediction in tourism planning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 551-568, April.
  43. Carmela Iorio & Giuseppe Pandolfo & Antonio D’Ambrosio & Roberta Siciliano, 2020. "Mining big data in tourism," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(5), pages 1655-1669, December.
  44. Song, Haiyan & Qiu, Richard T.R. & Park, Jinah, 2019. "A review of research on tourism demand forecasting," Annals of Tourism Research, Elsevier, vol. 75(C), pages 338-362.
  45. France, Stephen L. & Shi, Yuying & Kazandjian, Brett, 2021. "Web Trends: A valuable tool for business research," Journal of Business Research, Elsevier, vol. 132(C), pages 666-679.
  46. Ulrich Gunter & Irem Önder & Stefan Gindl, 2019. "Exploring the predictive ability of LIKES of posts on the Facebook pages of four major city DMOs in Austria," Tourism Economics, , vol. 25(3), pages 375-401, May.
  47. Marly Valenti Patandianan & Hiroyuki Shibusawa, 2020. "Evaluating the spatial spillover effects of tourism demand in Shizuoka Prefecture, Japan: an inter-regional input–output model," Asia-Pacific Journal of Regional Science, Springer, vol. 4(1), pages 73-90, February.
  48. 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).
  49. Shaolong Suna & Dan Bi & Ju-e Guo & Shouyang Wang, 2020. "Seasonal and Trend Forecasting of Tourist Arrivals: An Adaptive Multiscale Ensemble Learning Approach," Papers 2002.08021, arXiv.org, revised Mar 2020.
  50. Bai, Lijuan & Yan, Xiangbin & Yu, Guang, 2019. "Impact of CEO media appearance on corporate performance in social media," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
  51. Guizzardi, Andrea & Pons, Flavio Maria Emanuele & Angelini, Giovanni & Ranieri, Ercolino, 2021. "Big data from dynamic pricing: A smart approach to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1049-1060.
  52. Bi, Jian-Wu & Li, Hui & Fan, Zhi-Ping, 2021. "Tourism demand forecasting with time series imaging: A deep learning model," Annals of Tourism Research, Elsevier, vol. 90(C).
  53. Chuan Zhang & Yu-Xin Tian & Ling-Wei Fan, 2020. "Improving the Bass model’s predictive power through online reviews, search traffic and macroeconomic data," Annals of Operations Research, Springer, vol. 295(2), pages 881-922, December.
  54. Gang Xie & Xin Li & Yatong Qian & Shouyang Wang, 2021. "Forecasting tourism demand with KPCA-based web search indexes," Tourism Economics, , vol. 27(4), pages 721-743, June.
  55. Shaolong Sun & Yanzhao Li & Ju-e Guo & Shouyang Wang, 2020. "Tourism Demand Forecasting: An Ensemble Deep Learning Approach," Papers 2002.07964, arXiv.org, revised Jan 2021.
  56. Hou Jiang & Yaping Yang & Yongqing Bai, 2018. "Evaluation of All-for-One Tourism in Mountain Areas Using Multi-Source Data," Sustainability, MDPI, vol. 10(11), pages 1-19, November.
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