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| Format: | Artículo científico |
| Language: | en |
| Published: |
Universidade do Algarve
2016
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| Online Access: | https://www.redalyc.org/articulo.oa?id=388745016010 |
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Table of Contents:
- Forecasting tourist in-flow in South East Asia: A case of Singapore Manoj Kumar Seema Sharma Estudios de Turismo Singapore Forecasting Seasonal ARIMA Tourist Arrivals This study attempts to forecast tourist inflow in South East Asia and choses Singapore as a case. For Singapore, tourism is one of the major sources of foreign exchange earnings since it has no natural resources to support its economy. Therefore, forecasting of tourist arrivals in the country becomes very important for the reason that the forecasting may help tourism related service industries (e.g. airlines, hot els, shopping malls, transporters and catering services, etc.) to plan and prepare their resources and activities in an optimal way. In this paper, seasonal autoregressive integrated moving average (SARIMA) methodology was considered for making monthly pre dictions on tourist arrival in Singapore. The best model for forecasting is found out to be (1,0,1)(1,1,0)12 and monthly forecasting were obtained for two years in future. Further, various statistical tests (e.g. Dickey Fuller, KPSS, HEGY, Ljung - Box, Box - P ierce etc.) were applied on the time series for adequacy of best model to fit, residual autocorrelation analysis and for the accuracy of the prediction. 2016 artículo científico 2182-8458 https://www.redalyc.org/articulo.oa?id=388745016010 en http://www.redalyc.org/revista.oa?id=3887 Tourism & Management Studies application/pdf Universidade do Algarve Tourism & Management Studies (Portugal) Num.1 Vol.12