Abstract:
Uncertainty in the demand for a newspaper is a major problem that
newspaper companies come across because the printing process of a
newspaper highly depends on the newspaper demand. Better forecast is very
essential to print a newspaper because the quantity of printing will be
decided based on the forecasted value. Having an appropriate forecast of
weekly total demand is essential to take important business decisions like
budget planning and inventory controlling in newspaper industry. In this
study, an analysis was carried out by using weekly data of demand from
January 2013 to July 2014 for a daily newspaper. The main objective of this
research was to fit a suitable model for forecasting the weekly demand of
daily newspaper. The data set was divided into two parts; one for model
fitting and other for model validation. Different Auto Regressive Integrated
Moving Average (ARIMA) models were fitted for the data and best model
for forecasting was identified by using minimum Mean Absolute Percentage
Error (MAPE) value. ARIMA (2, 1, 3) model was identified as the best
model for weekly demand forecasting. MAPE value for weekly demand is
11.84%. The fitted ARIMA models were efficient in weekly demand
forecasting for the newspaper since the maximum error percentage for fitted
values were about 8%. The proposed model was found to perform well in
predicting the weekly demand for the selected newspaper. Furthermore, the
proposed model with minor adjustments can be used for weekly demand
forecasting for any daily newspaper in Sri Lanka by applying the same
procedure.