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Combining statistical and judgmental forecasts via a web-based tourism demand forecasting system

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Cited by:

  1. Hanyuan Zhang & Jiangping Lu, 2022. "Forecasting hotel room demand amid COVID-19," Tourism Economics, , vol. 28(1), pages 200-221, February.
  2. Gaojun Zhang & Jinfeng Wu & Bing Pan & Junyi Li & Minjie Ma & Muzi Zhang & Jian Wang, 2017. "Improving daily occupancy forecasting accuracy for hotels based on EEMD-ARIMA model," Tourism Economics, , vol. 23(7), pages 1496-1514, November.
  3. Lin, Vera Shanshan & Goodwin, Paul & Song, Haiyan, 2014. "Accuracy and bias of experts’ adjusted forecasts," Annals of Tourism Research, Elsevier, vol. 48(C), pages 156-174.
  4. Vera Shanshan Lin, 2019. "Judgmental adjustments in tourism forecasting practice: How good are they?," Tourism Economics, , vol. 25(3), pages 402-424, May.
  5. Marisol Valencia Cárdenas & Juan Gabriel Vanegas López & Juan Carlos Correa Morales & Jorge Aníbal Restrepo Morales, 2017. "Comparing forecasts for tourism dynamics in Medellín, Colombia," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 86, pages 199-230, Enero - J.
  6. Kauko, Karlo & Palmroos, Peter, 2014. "The Delphi method in forecasting financial markets— An experimental study," International Journal of Forecasting, Elsevier, vol. 30(2), pages 313-327.
  7. Spithourakis, Georgios P. & Petropoulos, Fotios & Nikolopoulos, Konstantinos & Assimakopoulos, Vassilios, 2015. "Amplifying the learning effects via a Forecasting and Foresight Support System," International Journal of Forecasting, Elsevier, vol. 31(1), pages 20-32.
  8. 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.
  9. Goodwin, Paul & Meeran, Sheik & Dyussekeneva, Karima, 2014. "The challenges of pre-launch forecasting of adoption time series for new durable products," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1082-1097.
  10. 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.
  11. Marisol Valencia Cárdenas & Juan Gabriel Vanegas L�pez & Juan Carlos Correa Morales & Jorge An�bal Restrepo Morales, 2016. "Comparación de pronósticos para la dinámica del turismo en Medellín, Colombia," Revista Lecturas de Economía, Universidad de Antioquia, CIE, issue 86, pages 199-230.
  12. Zhang, Hanyuan & Song, Haiyan & Wen, Long & Liu, Chang, 2021. "Forecasting tourism recovery amid COVID-19," Annals of Tourism Research, Elsevier, vol. 87(C).
  13. Rivera, Roberto, 2016. "A dynamic linear model to forecast hotel registrations in Puerto Rico using Google Trends data," Tourism Management, Elsevier, vol. 57(C), pages 12-20.
  14. Andrea Saayman & Ilsé Botha, 2017. "Non-linear models for tourism demand forecasting," Tourism Economics, , vol. 23(3), pages 594-613, May.
  15. Guizzardi, Andrea & Stacchini, Annalisa, 2015. "Real-time forecasting regional tourism with business sentiment surveys," Tourism Management, Elsevier, vol. 47(C), pages 213-223.
  16. Doris Chenguang Wu & Jingyan Liu & Haiyan Song & Anyu Liu & Hui Fu, 2019. "Developing a Web-based regional tourism satellite account (TSA) information system," Tourism Economics, , vol. 25(1), pages 67-84, February.
  17. Eleonora Di Matteo & Paolo Roma & Santo Zafonte & Umberto Panniello & Lorenzo Abbate, 2021. "Development of a Decision Support System Framework for Cultural Heritage Management," Sustainability, MDPI, vol. 13(13), pages 1-27, June.
  18. Winkler, Jens & Moser, Roger, 2016. "Biases in future-oriented Delphi studies: A cognitive perspective," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 63-76.
  19. 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.
  20. Hassani, Hossein & Webster, Allan & Silva, Emmanuel Sirimal & Heravi, Saeed, 2015. "Forecasting U.S. Tourist arrivals using optimal Singular Spectrum Analysis," Tourism Management, Elsevier, vol. 46(C), pages 322-335.
  21. 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.
  22. 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.
  23. Xi Wu & Adam Blake, 2023. "The Impact of the COVID-19 Crisis on Air Travel Demand: Some Evidence From China," SAGE Open, , vol. 13(1), pages 21582440231, January.
  24. Richard T.R. Qiu & Doris Chenguang Wu & Vincent Dropsy & Sylvain Petit & Stephen Pratt & Yasuo Ohe, 2021. "TOURIST ARRIVAL FORECAST AMID COVID-19: A perspective from the Asia and Pacific team," Post-Print hal-03138092, HAL.
  25. George Athanasopoulos & Rob J Hyndman & Mitchell O'Hara-Wild, 2021. "The Road to Recovery from COVID-19 for Australian Tourism," Monash Econometrics and Business Statistics Working Papers 1/21, Monash University, Department of Econometrics and Business Statistics.
  26. Larissa Koupriouchina & Jean-Pierre van der Rest & Zvi Schwartz, 2023. "Judgmental Adjustments of Algorithmic Hotel Occupancy Forecasts: Does User Override Frequency Impact Accuracy at Different Time Horizons?," Tourism Economics, , vol. 29(8), pages 2143-2164, December.
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