Prévoir la demande touristique en s'appuyant sur le big data multisource

Annals of Tourism Research, Volume 83, juillet 2020
Publié le 27 avril 2020

Résumé

Based on internet big data from multiple sources (i.e., the Baidu search engine and two online review platforms, Ctrip and Qunar), this study forecasts tourist arrivals to Mount Siguniang, China. Key findings of this empirical study indicate that (a) tourism demand forecasting based on internet big data from a search engine and online review platforms can significantly improve forecasting performance; (b) compared with tourism demand forecasting based on single-source data from a search engine, demand forecasting based on multisource big data from a search engine and online review platforms demonstrates better performance; and (c) compared with tourism demand forecasting based on online review data from a single platform, forecasting performance based on multiple platforms is significantly better.

Auteurs

Hengyun Li, Mingming Hu, Gang Li
 

Prévoir la demande touristique en s'appuyant sur le big data multisource (en anglais sur le site Science Direct)