International journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN:2313-626X

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 Volume 7, Issue 1 (January 2020), Pages: 87-99

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 Original Research Paper

 Title: Application of grey system theory and ARIMA model to forecast factors of tourism: A case of Binh Thuan Province in Vietnam

 Author(s): Nhu-Ty Nguyen 1, Bao-Phuong-Uyen Nguyen 1, Thanh-Tuyen Tran 2, *

 Affiliation(s):

 1School of Business, International University - VNU-HCMC, Quarter 6, Linh Trung Ward, Thu Duc District, Ho Chi Minh City, Vietnam
 2Scientific Research Center, Lac Hong University, No.10 Huynh Van Nghe Street, Dong Nai Province, Vietnam

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 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0002-9900-8592

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2020.01.009

 Abstract:

Tourism is becoming 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 for predicting the demand for tourism 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; the authors 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 MAPE, MSE, RMSE, and MAD to compare the forecasting model results. As a result, GM (1, 1), DGM (1, 1), Verhulst 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 Verhulst give better calculation than the other models. Besides, the performance of GM (1, 1), DGM (1, 1), Verhulst and ARIMA to forecast the number of visitors of the top six markets (Russia, Germany, France, Korea, China, and the 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. Moreover, recently, tourism industry has developed rapidly in Binh Thuan. Hence, the government has to propose suitable policies to develop local tourism industry. 

 © 2019 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: Tourism, Forecasting, Vietnam, Grey models, ARIMA

 Article History: Received 25 November 2018,Received in revised form 28 October 2019, Accepted 12 November 2019

 Acknowledgment:

No Acknowledgment.

 Compliance with ethical standards

 Conflict of interest:  The authors declare that they have no conflict of interest.

 Citation:

 Nguyen NT, Nguyen BPU, and Tran TT (2020). Application of grey system theory and ARIMA model to forecast factors of tourism: A case of Binh Thuan Province in Vietnam. International Journal of Advanced and Applied Sciences, 7(1): 87-99

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 Figures

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 Tables

 Table 1 Table 2 Table 3 Table 4 Table 5 Table 6 Table 7 Table 8 Table 9 Table 10 Table 11 Table 12 Table 13 Table 14 Table 15 

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