Research on Automatic Pricing and Replenishment Decision of Vegetable Products Based on Association Model

Vegetable merchandise sales play an important role in retailing, so effective pricing and replenishment strategies are critical to improving profits and customer satisfaction. A large amount of historical sales data including sales volume, price, seasonal variations and other relevant factors of vegetable items were first collected. Then, association models, such as association rule mining or collaborative filtering-based approaches, are used to analyse this data to discover the correlations between different commodities and customer purchasing patterns. In addition, association models can be used to predict future demand to optimise replenishment decisions. For example, if certain vegetable items are frequently purchased together, the system can automatically trigger a replenishment operation when the stock of one of the items falls below a certain threshold. Finally, the research could also explore how to take into account the impact of seasonal factors, promotional activities and competition on pricing and replenishment decisions to further improve the accuracy and usefulness of the model. This approach can be applied in real retail environments to provide merchants with smarter decision support.