Group pooling for deep tourism demand forecasting

Zhang, Yishuo, Li, Gang, Muskat, Birgit, Law, Rob and Yang, Yating 2020, Group pooling for deep tourism demand forecasting, Annals of Tourism Research, vol. 82, pp. 1-17, doi: 10.1016/j.annals.2020.102899.

Attached Files
Name Description MIMEType Size Downloads

Title Group pooling for deep tourism demand forecasting
Author(s) Zhang, Yishuo
Li, GangORCID iD for Li, Gang orcid.org/0000-0003-1583-641X
Muskat, Birgit
Law, Rob
Yang, Yating
Journal name Annals of Tourism Research
Volume number 82
Article ID 102899
Start page 1
End page 17
Total pages 17
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Publication date 2020-05
ISSN 0160-7383
Keyword(s) Tourism demand forecasting
AI-based methodology
Group-pooling method
Deep-learning model
Tourism demand similarity
Asia Pacific travel patterns
Language eng
DOI 10.1016/j.annals.2020.102899
Indigenous content off
Field of Research 1506 Tourism
1505 Marketing
1504 Commercial Services
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2020, Elsevier Ltd
Persistent URL http://hdl.handle.net/10536/DRO/DU:30135739

Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 2 times in TR Web of Science
Scopus Citation Count Cited 4 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 54 Abstract Views, 1 File Downloads  -  Detailed Statistics
Created: Mon, 23 Mar 2020, 12:11:11 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.