UM  > 工商管理學院  > 綜合度假村及旅遊管理學系
Tourism demand forecasting: A deep learning approach
Law,Rob1; Li,Gang2; Fong,Davis Ka Chio3; Han,Xin4
Source PublicationAnnals of Tourism Research

Traditional tourism demand forecasting models may face challenges when massive amounts of search intensity indices are adopted as tourism demand indicators. Using a deep learning approach, this research studied the framework in forecasting monthly Macau tourist arrival volumes. The empirical results demonstrated that the deep learning approach significantly outperforms support vector regression and artificial neural network models. Moreover, the construction and identification of highly relevant features from the proposed deep network architecture provide practitioners with a means of understanding the relationships between various tourist demand forecasting factors and tourist arrival volumes. This article also launches the Annals of Tourism Research Curated Collection on Tourism Demand Forecasting, a special selection of research in this field

KeywordAttention Mechanism Deep Learning Feature Engineering Lag Order Long-short-term-memory Tourism Demand Forecasting
URLView the original
Indexed BySSCI
WOS Research AreaSocial Sciences - Other Topics ; Sociology
WOS SubjectHospitality, Leisure, Sport & Tourism ; Sociology
WOS IDWOS:000474679500030
Fulltext Access
Citation statistics
Cited Times [WOS]:17   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Corresponding AuthorLaw,Rob
Affiliation1.School of Hotel & Tourism Management,The Hong Kong Polytechnic University,,Kowloon,Hong Kong
2.School of Information Technology,Deakin University,,Geelong,3216,Australia
3.Faculty of Business Administration,University of Macau,,Macau,China
4.School of Computer Science,Xi'an Shiyou University,,710065,China
Recommended Citation
GB/T 7714
Law,Rob,Li,Gang,Fong,Davis Ka Chio,et al. Tourism demand forecasting: A deep learning approach[J]. Annals of Tourism Research,2019,75:410-423.
APA Law,Rob,Li,Gang,Fong,Davis Ka Chio,&Han,Xin.(2019).Tourism demand forecasting: A deep learning approach.Annals of Tourism Research,75,410-423.
MLA Law,Rob,et al."Tourism demand forecasting: A deep learning approach".Annals of Tourism Research 75(2019):410-423.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Law,Rob]'s Articles
[Li,Gang]'s Articles
[Fong,Davis Ka Chio]'s Articles
Baidu academic
Similar articles in Baidu academic
[Law,Rob]'s Articles
[Li,Gang]'s Articles
[Fong,Davis Ka Chio]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Law,Rob]'s Articles
[Li,Gang]'s Articles
[Fong,Davis Ka Chio]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.