Research on Automatic Pricing and Replenishment Decisions for Vegetable Commodities Based on Pearson Correlation Analysis and VAR Model

Abstract

This paper investigates the automatic pricing and replenishment decisions for vegetable commodities based on Pearson correlation analysis and the Vector Autoregression (VAR) model. By analyzing vegetable sales data, box plots and histograms reveal the sales volume distribution patterns of different categories and individual vegetable products, and Pearson correlation analysis uncovers the intrinsic relationships among them. A VAR model is further constructed to forecast the sales volume and pricing of vegetables, combined with the cost-plus pricing strategy from economic principles to determine the replenishment volume and pricing strategy that maximizes profits. The study demonstrates that the model can effectively guide supermarkets in achieving optimal pricing and replenishment for vegetable products, enhancing the economic benefits.