| dc.description.abstract | Sales forecasting is the key to the success of a supply chain, especially in the fashion
industry. Vietnam is a major apparel supplier for international brands and has a
dynamic, fast-growing market. The lack of complete forecasting systems in such a
market motivates our development of sales forecast procedures featuring quantifiable
results and practical implementation. Both statistical and machine learning methods
were tested using actual data. We found that Random Forest consistently yields the
lowest error metrics, followed closely by XGBoost. Meanwhile, clustering did not
provide conclusive evidence of improved accuracy. As the study’s data sources come
entirely from one company, these procedures are applicable for other firms to deploy
their data without external mining sources. | en_US |
