Forecasting inbound tourism demand to China using time series models and belief functions

© Springer International Publishing Switzerland 2015. Modeling uncertainty is a key issue in forecasting. In the tourism area, forecasts are used by governments, airline companies and operators to design tourism policies and they should include a quantification of uncertainties. This paper proposed...

Full description

Saved in:

Bibliographic Details
Main Authors:	Jiechen Tang, Songsak Sriboonchitta, Xinyu Yuan
Format:	Book Series
Published:	2018
Subjects:	Computer Science
Online Access:	https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84919360820&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/54392
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	Chiang Mai University

id	th-cmuir.6653943832-54392
record_format	dspace
spelling	th-cmuir.6653943832-543922018-09-04T10:12:49Z Forecasting inbound tourism demand to China using time series models and belief functions Jiechen Tang Songsak Sriboonchitta Xinyu Yuan Computer Science © Springer International Publishing Switzerland 2015. Modeling uncertainty is a key issue in forecasting. In the tourism area, forecasts are used by governments, airline companies and operators to design tourism policies and they should include a quantification of uncertainties. This paper proposed a new approach to forecast the tourism demand, which is time series models combined with belief functions. We used this method to predict the demand for China international tourism, with an explicit representation of forecast uncertainty. The monthly data of international tourist arrival cover the period from January 1991 to June 2013. The result show that time seriesmodels combined with belief functions is a computationally simple and effective method. 2018-09-04T10:12:49Z 2018-09-04T10:12:49Z 2015-01-01 Book Series 1860949X 2-s2.0-84919360820 10.1007/978-3-319-13449-9_23 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84919360820&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/54392
institution	Chiang Mai University
building	Chiang Mai University Library
country	Thailand
collection	CMU Intellectual Repository
topic	Computer Science
spellingShingle	Computer Science Jiechen Tang Songsak Sriboonchitta Xinyu Yuan Forecasting inbound tourism demand to China using time series models and belief functions
description	© Springer International Publishing Switzerland 2015. Modeling uncertainty is a key issue in forecasting. In the tourism area, forecasts are used by governments, airline companies and operators to design tourism policies and they should include a quantification of uncertainties. This paper proposed a new approach to forecast the tourism demand, which is time series models combined with belief functions. We used this method to predict the demand for China international tourism, with an explicit representation of forecast uncertainty. The monthly data of international tourist arrival cover the period from January 1991 to June 2013. The result show that time seriesmodels combined with belief functions is a computationally simple and effective method.
format	Book Series
author	Jiechen Tang Songsak Sriboonchitta Xinyu Yuan
author_facet	Jiechen Tang Songsak Sriboonchitta Xinyu Yuan
author_sort	Jiechen Tang
title	Forecasting inbound tourism demand to China using time series models and belief functions
title_short	Forecasting inbound tourism demand to China using time series models and belief functions
title_full	Forecasting inbound tourism demand to China using time series models and belief functions
title_fullStr	Forecasting inbound tourism demand to China using time series models and belief functions
title_full_unstemmed	Forecasting inbound tourism demand to China using time series models and belief functions
title_sort	forecasting inbound tourism demand to china using time series models and belief functions
publishDate	2018
url	https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84919360820&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/54392
_version_	1681424312123260928

Forecasting inbound tourism demand to China using time series models and belief functions

Similar Items