Forecasting the Foreign Tourist Arrivals to Vietnam Using the Autoregressive Integrated Moving Average Method
Le Tung ()
Additional contact information
Le Tung: Faculty of Economics and Public Management Ho Chi Minh City Open University Vietnam, Postal: VN
Journal of Advanced Research in Management, 2018, vol. 9, issue 6, 1135-1144
Abstract:
The tourism has been recognized as the most important service sector in the economic development strategy of the Vietnamese government for the decades The number of foreign visitors to Vietnam has increased rapidly over the years however the quality of the forecasting work has not met the requirements of the planning development The serious over loading of Vietnamese infrastructure as well as serving network has come by the problems in the forecasting There is a large gap between the forecasting information and the real growth of the tourism sector in Vietnam In order to solve this issue our paper employs the ARIMA method to identify a more suitable tool for forecasting the foreign tourist arrivals to Vietnam The data is used by the monthly form collected from the January 2009 to June 2018 The regression result determines the ARIMA 2 1 12 is the optimal model and applied to forecast the number of visitors come to Vietnam for three months of the third quarter in 2018 Finally our study result provides a useful forecasting tool for not only the Vietnamese policymakers but also the businesses in the tourism sector in Vietnam in the future
Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (4)
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:srs:jemt00:v:9:y:2018:i:6:p:1135-1144
Access Statistics for this article
Journal of Advanced Research in Management is currently edited by Ramona PIRVU
More articles in Journal of Advanced Research in Management from ASERS Publishing
Bibliographic data for series maintained by Claudiu Popirlan ( this e-mail address is bad, please contact ).