| dc.description.abstract | This study proposes a procedure for selecting forecasting models to
support a coffee store chain in choosing suitable techniques for their business. It
compares traditional and modern statistical methods for predicting the 4 – week
heading demand of two coffee – based categories, Espresso and Vietnamese
Coffee. The quantitative techniques employed include SES, ARIMA, LS, MLR,
DT, and RF. DT and SES are identified as the optimal methods for Espresso and
Vietnamese Coffee, respectively, based on error measures such as MAE,
sMAPE, RelMAE, MdAE, sMdAPE, and RelMdAE, with the mean method as
the benchmark. Additionally, the study suggests the optimal weekly order
quantity for coffee packages using the newsvendor model to maximize profit. | en_US |
