Research on Vegetable Replenishment and Pricing Optimization Decision Based on SARIMA Model and Regression Analysis

Abstract

In the context of fresh supermarkets, which are confronted with the challenges of short shelf life and susceptibility to deterioration of vegetable products, these establishments require daily replenishment and careful pricing. To develop more rational pricing strategies, this study starts by using regression analysis to create a linear regression equation that correlates total sales volume with cost-plus pricing. Through a rigorous statistical analysis, a regression equation with heightened reliability is derived to better forecast the relationship between total sales volume and cost-plus pricing. Subsequently, a Seasonal Autoregressive Integrated Moving Average (SARIMA) model is implemented. Drawing on historical sales data, the study forecasts the daily replenishment quantities and pricing strategies for various categories of vegetables in the upcoming week.