The purpose of this paper is to understand the trend and forecast the number of tourists from different regions of the world to Mauritius.
The paper adopts two grey system models, the even model GM(1,1) and the non-homogeneous discrete grey model (NDGM), to forecast the total number of international tourism to Mauritius and its structure from different regions tourist arrivals to Mauritius for the next three years. Grey system theory models were used to account for uncertainties and the dynamism of the tourism sector environment. The two models were applied as a comparison to obtain more reliable forecasting figures.
The results demonstrate that both of the grey system models can be successfully applied with high accuracy for Mauritian tourism prediction, and also the number of tourist arrivals to Mauritius shows a continued augmentation for the upcoming years.
Forecasting is meaningful since the Government of Mauritius, private companies or any concerned authority can adopt the forecasting methods exposed in this paper for the development of the tourism sector through managerial and economic decision making.
Mauritius is a charming travel destination. Through this paper, it can be seen that future tourism travel to Mauritius has been successfully predicted based on previous data. Moreover, it seems that the grey system theory models have not been utilised yet as forecasting tools for the tourism sector of Mauritius as opposed to other countries such as China and Taiwan.
This work was supported by National Natural Science Foundation of China under Grant No. 71671090, Aeronautical Science Foundation of China under grant 2014ZG52068, MOE (Ministry of Education in China) Liberal Arts and Social Sciences Foundation under Grant No. 15YJCZH189 and Qinglan Project for excellent youth or middle-aged academic leaders in Jiangsu Province (China).
Pirthee, M. (2017), "Grey-based model for forecasting Mauritius international tourism from different regions", Grey Systems: Theory and Application, Vol. 7 No. 2, pp. 259-271. https://doi.org/10.1108/GS-04-2017-0008Download as .RIS
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