Digital commerce activities have been on the rise in the last years. Several types of forecasting models are considered to predict outcome variables in the context of e-commerce. This research seeks to develop a robust methodology for modelling and forecasting sales volume. Additionally, we suggest that other management-related variables could be relevant to e-commerce sales volume. Our analysis shows that by highlighting the series of sales volume, the proposed model is able to make accurate predictions of trends and seasonality. Overall, the use of exponential smoothing methodologies could be considered very reliable and efficient in the e-commerce context.

This work is partially financed by national funds through FCT – Fundação para a Ciência e a Tecnologia under the project UIDB/00006/2020. https://doi.org/10.54499/UIDB/00006/2020.

E-commerce · sales · employment · time series · exponential smoothing models · forecasting · prediction error