International Journal of Business and Management · 2011 · 12 citations · 20 references
BusinessTourism ManagementForecastingTime Series AnalysisTourismForecast EvaluationMultivariate ForecastingTime Series EconometricsTime Series ForecastingTime Series ModelingTourism EconomicsArima ModelsDemand Forecasting ModelsEvaluationInternational Demand ForecastingMonthly ForecastingMoving Average ProcessesTourism Demand ModellingTourism Forecasting
The paper deals with forecasting international tourists footfalls in India, applying an assortment of uni-variatetime series forecasting models, for monthly data spreading over Dec 1990 to Jan 2010. The forecastingperformance of various competing models is evaluated with MAPE and other criteria. Also the actual andforecasted values are compared since Feb 2010 to Sept 2010 for better evaluation. The SARIMA model performsbetter than other competing model for forecasting, with lowest MAPE value. In fact it has an advantage overother models as it explicates autoregressive and moving average process not only for the data series but also ofseasonality. As a policy implication, SARIMA model can be used for forecasting tourists demand in India.
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