Multi-scale analysis-driven tourism forecasting: insights from the peri-COVID-19

doi:10.1080/13683500.2022.2144151

	Multi-scale analysis-driven tourism forecasting: insights from the peri-COVID-19
	Li, Mingchen 2,3; Zhang, Chengyuan 1; Wang, Shouyang 2,3; Sun, Shaolong 4
刊名	CURRENT ISSUES IN TOURISM
	2022-11-22
页码	24
关键词	Tourism demand forecasting divide and conquer Facebook prophet deep learning peri-COVID-19 era
ISSN号	1368-3500
DOI	10.1080/13683500.2022.2144151
英文摘要	Tourism managers and practitioners rely on accurate demand forecasting and well-informed management guidance. Given the pandemic's consequences on tourism, future analysis in the during-epidemic era is urgently needed. This study aims to achieve three goals combining the utilization of decomposition algorithms and deep learning models: 1) to investigate the changes in tourism demand according to seasonal fluctuations of various frequencies, 2) to improve modelling accuracy in tourism demand forecasting during non-crisis periods and in the peri-COVID-19 era, and 3) to analyze tourism demand evolution in the peri-Covid-19 era. The volume of domestic tourism in Hawaii is used as sample data for demonstration and validation. The empirical findings demonstrate that the framework provided in this study has excellent interpretability and forecasting accuracy, surpasses all benchmark models in terms of error calculation and statistical tests and can provide further insights into peri-Covid-19 demand analysis and management.
资助项目	National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities ; Research Program of Shaanxi Soft Science, China ; [72201201] ; [72101197] ; [62141223] ; [71988101] ; [SK2021007] ; [2022KRM015]
WOS研究方向	Social Sciences - Other Topics
语种	英语
出版者	ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
WOS记录号	WOS:000889584600001
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/60595]
专题	中国科学院数学与系统科学研究院
通讯作者	Sun, Shaolong
作者单位	1.Xidian Univ, Sch Econ & Management, Xian, Peoples R China 2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China 3.Univ Chinese Acad Sci, Sch Econ & Management, Beijing, Peoples R China 4.Xi An Jiao Tong Univ, Sch Management, Xian, Peoples R China
推荐引用方式 GB/T 7714	Li, Mingchen,Zhang, Chengyuan,Wang, Shouyang,et al. Multi-scale analysis-driven tourism forecasting: insights from the peri-COVID-19[J]. CURRENT ISSUES IN TOURISM,2022:24.
APA	Li, Mingchen,Zhang, Chengyuan,Wang, Shouyang,&Sun, Shaolong.(2022).Multi-scale analysis-driven tourism forecasting: insights from the peri-COVID-19.CURRENT ISSUES IN TOURISM,24.
MLA	Li, Mingchen,et al."Multi-scale analysis-driven tourism forecasting: insights from the peri-COVID-19".CURRENT ISSUES IN TOURISM (2022):24.