Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/77356
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dc.contributor.authorDanhua Jiangen_US
dc.contributor.authorJianxu Liuen_US
dc.contributor.authorJirakom Sirisrisakulchaien_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.date.accessioned2022-10-16T07:28:45Z-
dc.date.available2022-10-16T07:28:45Z-
dc.date.issued2021-07-27en_US
dc.identifier.issn17426596en_US
dc.identifier.issn17426588en_US
dc.identifier.other2-s2.0-85112460941en_US
dc.identifier.other10.1088/1742-6596/1978/1/012063en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85112460941&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/77356-
dc.description.abstractThe purpose of this paper is to study the tourism demand of Thailand from six major source countries (CN, JP, KO, MAS, SG and LA) in two regions of Asia (East Asia and Southeast Asia). The data is from 1997q1 to 2020q1, which can also provide some advice for the recovery of Thailand tourism post COVID-19. Compared with previous studies, we consider the dependence of tourist flow in the same region. Precisely, we estimated the impact of tourism flows between pairwise countries in each region. This also provides a complement to the subsequent research on the structure of tourism dependence for tourism demand of Thailand. The Copula-based approaches are increasingly being used for tourism demand, we apply the copula-ARDL (ECM) framework to forecast tourist arrivals from two regions. Using the characteristics of correlation matrix in the trivariate Gaussian copula model, we have innovatively performed unconstrained parametric optimization of these two models to ensure the accuracy of the forecasting.en_US
dc.subjectPhysics and Astronomyen_US
dc.titleForecasting Thailand inbound tourist flow association for tourism demanden_US
dc.typeConference Proceedingen_US
article.title.sourcetitleJournal of Physics: Conference Seriesen_US
article.volume1978en_US
article.stream.affiliationsShandong University of Finance and Economicsen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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