IDEAS home Printed from https://ideas.repec.org/r/eee/touman/v57y2016icp12-20.html
   My bibliography  Save this item

A dynamic linear model to forecast hotel registrations in Puerto Rico using Google Trends data

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals with Google Trends and Mixed Frequency Data," EconStor Preprints 187420, ZBW - Leibniz Information Centre for Economics.
  2. Tomas Havranek & Ayaz Zeynalov, 2021. "Forecasting tourist arrivals: Google Trends meets mixed-frequency data," Tourism Economics, , vol. 27(1), pages 129-148, February.
  3. 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.
  4. Bi, Jian-Wu & Liu, Yang & Li, Hui, 2020. "Daily tourism volume forecasting for tourist attractions," Annals of Tourism Research, Elsevier, vol. 83(C).
  5. 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.
  6. Armand Viljoen & Andrea Saayman & Melville Saayman, 2019. "Determinants influencing inbound arrivals to Africa," Tourism Economics, , vol. 25(6), pages 856-883, September.
  7. Javier Sebastian, 2016. "Blockchain in financial services: Regulatory landscape and future challenges," Working Papers 16/21, BBVA Bank, Economic Research Department.
  8. 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.
  9. 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.
  10. Jian Mou & Wenting Liu & Chong Guan & J. Christopher Westland & Jongki Kim, 2024. "Predicting the cryptocurrency market using social media metrics and search trends during COVID-19," Electronic Commerce Research, Springer, vol. 24(2), pages 1307-1333, June.
  11. Takahashi, Carlos Kazunari & Figueiredo, Júlio César Bastos de & Scornavacca, Eusebio, 2024. "Investigating the diffusion of innovation: A comprehensive study of successive diffusion processes through analysis of search trends, patent records, and academic publications," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
  12. Hatice Öncel Çekim & Ahmet Koyuncu, 2022. "The Impact of Google Trends on the Tourist Arrivals: A Case of Antalya Tourism," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 10(1), pages 1-14, June.
  13. 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.
  14. Lim, Sungkyu & Seetaram, Neelu & Hosany, Sameer & Li, Matthew, 2023. "Consumption of pop culture and tourism demand: Through the lens of herding behaviour," Annals of Tourism Research, Elsevier, vol. 99(C).
  15. Correa, Alexander, 2021. "Prediciendo la llegada de turistas a Colombia a partir de los criterios de Google Trends," Revista Lecturas de Economía, Universidad de Antioquia, CIE, issue No. 95, pages 105-134, July.
  16. 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.
  17. Daniel E. O'Leary, 2024. "Toward an extended framework of exhaust data for predictive analytics: An empirical approach," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 31(2), June.
  18. 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.
  19. Serhan Cevik, 2022. "Where should we go? Internet searches and tourist arrivals," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4048-4057, October.
  20. Zeynalov, Ayaz, 2017. "Forecasting Tourist Arrivals in Prague: Google Econometrics," MPRA Paper 83268, University Library of Munich, Germany.
  21. Li, Hengyun & Hu, Mingming & Li, Gang, 2020. "Forecasting tourism demand with multisource big data," Annals of Tourism Research, Elsevier, vol. 83(C).
  22. Hulya Bakirtas & Vildan Gulpinar Demirci, 2022. "Can Google Trends data provide information on consumer’s perception regarding hotel brands?," Information Technology & Tourism, Springer, vol. 24(1), pages 57-83, March.
  23. 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).
  24. Peixue Liu & Xiao Xiao & Jie Zhang & Ronghua Wu & Honglei Zhang, 2018. "Spatial Configuration and Online Attention: A Space Syntax Perspective," Sustainability, MDPI, vol. 10(1), pages 1-15, January.
  25. F. Antolini & L. Grassini, 2019. "Foreign arrivals nowcasting in Italy with Google Trends data," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(5), pages 2385-2401, September.
  26. 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.
  27. Chumnumpan, Pattarin & Shi, Xiaohui, 2019. "Understanding new products’ market performance using Google Trends," Australasian marketing journal, Elsevier, vol. 27(2), pages 91-103.
  28. 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.
  29. 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.
  30. Abay,Kibrom A. & Hirfrfot,Kibrom Tafere & Woldemichael,Andinet, 2020. "Winners and Losers from COVID-19 : Global Evidence from Google Search," Policy Research Working Paper Series 9268, The World Bank.
  31. Jiaer He & Roberto Rivera, 2023. "A Modeling Approach of Return and Volatility of Structured Investment Products with Caps and Floors," Papers 2311.06282, arXiv.org.
  32. 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.
  33. 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.
  34. Yuqian Zhang, 2023. "Using Google Trends to track the global interest in International Financial Reporting Standards: Evidence from big data," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 30(2), pages 87-100, April.
  35. Cebrián, Eduardo & Domenech, Josep, 2024. "Addressing Google Trends inconsistencies," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
  36. Lash, Michael T. & Sajeesh, S. & Araz, Ozgur M., 2023. "Predicting mobility using limited data during early stages of a pandemic," Journal of Business Research, Elsevier, vol. 157(C).
  37. Silvia Emili & Paolo Figini & Andrea Guizzardi, 2020. "Modelling international monthly tourism demand at the micro destination level with climate indicators and web-traffic data," Tourism Economics, , vol. 26(7), pages 1129-1151, November.
  38. Mingming Hu & Haiyan Song, 2020. "Data source combination for tourism demand forecasting," Tourism Economics, , vol. 26(7), pages 1248-1265, November.
  39. 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.
  40. 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.
  41. Li, Hengyun & Gao, Huicai & Song, Haiyan, 2023. "Tourism forecasting with granular sentiment analysis," Annals of Tourism Research, Elsevier, vol. 103(C).
  42. 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.
  43. Boone, Tonya & Ganeshan, Ram & Jain, Aditya & Sanders, Nada R., 2019. "Forecasting sales in the supply chain: Consumer analytics in the big data era," International Journal of Forecasting, Elsevier, vol. 35(1), pages 170-180.
  44. Abay, Kibrom A. & Ibrahim, Hosam, 2020. "Winners and losers from COVID-19: Evidence from Google search data for Egypt," MENA policy notes 8, International Food Policy Research Institute (IFPRI).
  45. Ahmed Shoukry Rashad, 2022. "The Power of Travel Search Data in Forecasting the Tourism Demand in Dubai," Forecasting, MDPI, vol. 4(3), pages 1-11, July.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.