| dc.description.abstract | Tourism is more and more popular and this industry continues to
develop strongly around the world. Thus, forecasting tourism demand plays an
important role in development. In this study, the purpose is to provide some
appropriate models to predict the tourism demand in Binh Thuan Province in
Vietnam. There are five models applied in this study, namely GM (1,1), DGM
(1,1), DGM (2,1), Verhulst and ARIMA; we try to test these models to find
which concise and accurate forecasting models being able to predict the best
result about the tourism demand.
So as to ensure the precision, the authors collected data of total revenue,
domestic visitor, international tourists and top six countries having the biggest
numbers of visitors (Russia, Germany, France, Korea, China and USA) in ten
years (between 2008 to 2017) from Binh Thuan Department of Culture, Sports
and Tourism. We apply Mean Absolute Percentage Error (MAPE), Mean
Squared Error (MSE), Root Mean Square Error (RMSE), Mean Absolute
Deviation (MAD) to compare the results of forecasting models.
As a result, grey Verhulst, DGM (1,1), GM (1,1) and ARIMA augment
excellent results and minimum forecasted errors. In terms of total revenue,
ARIMA is the best choice for prediction. About the domestic visitors and
international tourists, GM (1,1), DGM (1,1) and Verhust give the better
calculation than the other models. Besides, the performance of GM (1,1),
DGM (1,1), Verhulst and ARIMA about forecasting the number of travelers of
top six markets (Russia, Germany, France, Korea, China and USA) sending
the largest number of tourists describes good results. For all the factors, DGM
(2,1) is rejected to predict due to the poor results.
Also, recently, tourism industry has developed rapidly in Binh Thuan. Hence,
the government has to propose suitable policies to develop local tourism
industry. | en_US |
