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Forecasting city arrivals with Google Analytics

Citations

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Cited by:

  1. Villamediana, Jenely & Küster, Inés & Vila, Natalia, 2019. "Destination engagement on Facebook: Time and seasonality," Annals of Tourism Research, Elsevier, vol. 79(C).
  2. Li, Cheng & Zheng, Weimin & Ge, Peng, 2022. "Tourism demand forecasting with spatiotemporal features," Annals of Tourism Research, Elsevier, vol. 94(C).
  3. 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.
  4. Tarmo Kalvet & Maarja Olesk & Marek Tiits & Janika Raun, 2020. "Innovative Tools for Tourism and Cultural Tourism Impact Assessment," Sustainability, MDPI, vol. 12(18), pages 1-30, September.
  5. Roy, Gobinda & Sharma, Swati, 2021. "Measuring the role of factors on website effectiveness using vector autoregressive model," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
  6. Bi, Jian-Wu & Liu, Yang & Li, Hui, 2020. "Daily tourism volume forecasting for tourist attractions," Annals of Tourism Research, Elsevier, vol. 83(C).
  7. 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.
  8. 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).
  9. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
  10. 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.
  11. 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.
  12. Deqing Wang & Yinqiu Song & Hongyan Zhang & Shengjie Pan, 2020. "The Effectiveness of Chinas Monetary Policy: Based on the Mixed-Frequency Data," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 10(3), pages 325-339, March.
  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. Ulrich Gunter, 2021. "Improving Hotel Room Demand Forecasts for Vienna across Hotel Classes and Forecast Horizons: Single Models and Combination Techniques Based on Encompassing Tests," Forecasting, MDPI, vol. 3(4), pages 1-36, November.
  15. Yi-Chung Hu, 2023. "Tourism combination forecasting using a dynamic weighting strategy with change-point analysis," Current Issues in Tourism, Taylor & Francis Journals, vol. 26(14), pages 2357-2374, July.
  16. 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).
  17. Cao, Zheng & Li, Gang & Song, Haiyan, 2017. "Modelling the interdependence of tourism demand: The global vector autoregressive approach," Annals of Tourism Research, Elsevier, vol. 67(C), pages 1-13.
  18. 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.
  19. Thomas J. Lampoltshammer & Stefanie Wallinger & Johannes Scholz, 2023. "Bridging Disciplinary Divides through Computational Social Sciences and Transdisciplinarity in Tourism Education in Higher Educational Institutions: An Austrian Case Study," Sustainability, MDPI, vol. 15(10), pages 1-16, May.
  20. 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.
  21. Yang, Yang & Zhang, Honglei, 2019. "Spatial-temporal forecasting of tourism demand," Annals of Tourism Research, Elsevier, vol. 75(C), pages 106-119.
  22. 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.
  23. Li, Hengyun & Hu, Mingming & Li, Gang, 2020. "Forecasting tourism demand with multisource big data," Annals of Tourism Research, Elsevier, vol. 83(C).
  24. Mazanec, Josef A., 2020. "Hidden theorizing in big data analytics: With a reference to tourism design research," Annals of Tourism Research, Elsevier, vol. 83(C).
  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. Georgios Giotis & Evangelia Papadionysiou, 2022. "The Role of Managerial and Technological Innovations in the Tourism Industry: A Review of the Empirical Literature," Sustainability, MDPI, vol. 14(9), pages 1-20, April.
  27. Anastasiou, Dimitris & Drakos, Konstantinos & Kapopoulos, Panayotis, 2022. "Predicting international tourist arrivals in Greece with a novel sector-specific business leading indicator," MPRA Paper 113860, University Library of Munich, Germany.
  28. 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.
  29. Jiahui Huang & Chenglong Zhang, 2024. "Daily Tourism Demand Forecasting with the iTransformer Model," Sustainability, MDPI, vol. 16(23), pages 1-22, December.
  30. 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.
  31. 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.
  32. 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.
  33. 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.
  34. Mingming Hu & Haifeng Yang & Doris Chenguang Wu & Shuai Ma, 2024. "A novel two-stage combination model for tourism demand forecasting," Tourism Economics, , vol. 30(8), pages 1925-1950, December.
  35. Yuruixian Zhang & Wei Chong Choo & Yuhanis Abdul Aziz & Choy Leong Yee & Jen Sim Ho, 2022. "Go Wild for a While? A Bibliometric Analysis of Two Themes in Tourism Demand Forecasting from 1980 to 2021: Current Status and Development," Data, MDPI, vol. 7(8), pages 1-38, July.
  36. 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.
  37. Ulrich Gunter & Irem Önder & Egon Smeral, 2020. "Are Combined Tourism Forecasts Better at Minimizing Forecasting Errors?," Forecasting, MDPI, vol. 2(3), pages 1-19, June.
  38. Weaver, Adam, 2021. "Tourism, big data, and a crisis of analysis," Annals of Tourism Research, Elsevier, vol. 88(C).
  39. 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.
  40. 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.
  41. 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.
  42. Assaf, A. George & Tsionas, Mike G., 2019. "Forecasting occupancy rate with Bayesian compression methods," Annals of Tourism Research, Elsevier, vol. 75(C), pages 439-449.
  43. Li, Hengyun & Gao, Huicai & Song, Haiyan, 2023. "Tourism forecasting with granular sentiment analysis," Annals of Tourism Research, Elsevier, vol. 103(C).
  44. 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.
  45. Xu, Shilin & Liu, Yang & Jin, Chun, 2023. "Forecasting daily tourism demand with multiple factors," Annals of Tourism Research, Elsevier, vol. 103(C).
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