Forecasting Domestic Guest Nights in Ancient Cities of Sri Lanka: Hybrid Approach

Abstract

The Ancient Cities are highly occupied by domestic tourists after 2009. The high occupancy increases the demand for accommodation. Hence, the hotel industry should adopt various practices to maximize profits and minimize the risk. This can be achieved by accurate forecasting. But, there were least attempts on forecasting occupancy guest nights of domestic tourist in Ancient Cities of Sri Lanka. Therefore, this study was focused on forecasting occupancy guest nights of domestic tourist in Ancient Cities of Sri Lanka. Monthly data of domestic guest nights for the period of January 2008 to December 2016 were obtained from Sri Lanka Tourism Development Authority (SLTDA). Descriptive statistics were obtained. The trend models; Linear, Quadratic, Growth Curve and S-Curve models were tested. The AndersonDarling test revealed the residuals of Linear and Quadratic were normally distributed, but Ljung-Box Q-test and Auto-Correlation Function (ACF) does not confirm the independence. Therefore the de-trended data were further analyzed; the stationary of the series was tested by Augmented Dickey-Fuller (ADF) test and ACF. Then the Auto-Regressive Integrated Moving Average (ARIMA) model was tested on each series. The ARIMA model was well fitted for de-trended series of Linear trend and Growth Curve models. Hence, the residuals of two hybrid models; Linear trend-ARIMA and Growth Curve trend-ARIMA models were tested for model assumptions. It was concluded that both hybrid models; Linear trend-ARIMA and Growth Curve-ARIMA are suitable for forecasting occupancy guest nights of domestic tourist in Ancient Cities of Sri Lanka.