Sama Circular Model on Forecasting Foreign Guest Nights in Anuradhapura of Sri Lanka

Abstract

The Sama Circular Model (SCM) is a modern development in univariate time series. It is a powerful technique to capture wave-like patterns with the trend of a data series. Forecasting occupancy is very useful for the tourism industry in Sri Lanka. Anuradhapura is one of the leading ancient cities of Sri Lanka which is highly occupied by a foreign guest. Therefore, the study was a focus on forecasting occupancy guest nights. Monthly data of foreign guest nights for the period of January 2008 to December 2017 were obtained from the Sri Lanka Tourism Development Authority (SLTDA). The SCM and Seasonal Autoregressive Integrated Moving Average (SARIMA) models were tested for forecasting. The Anderson–Darling test, Auto-Correlation Function (ACF), and Ljung-Box Q (LBQ)-test were used as the goodness of fit tests in model validation. The best-fitting model was selected by comparing by absolute measurements of errors. The study concluded that Sama Circular Model performed better than SARIMA. Therefore, it is recommended to test the Sama Circular Model for other business activities in the tourism industry of Sri Lanka.

Keywords: Occupancy, Sama Circular Model, SARIMA