Study on Pricing and Replenishment Decision of Vegetable Products Based on SARIMA Model

Abstract

In fresh food superstores, vegetable commodities are characterized by a short shelf life and deterioration in quality over time. To meet market demand and profit, merchants usually sell vegetables with shipping losses and deteriorating quality at a discount. Therefore, the pricing and replenishment strategies of vegetables have an important impact on the profit maximization of fresh produce superstores. The aim of this paper is to reveal the patterns by processing and analyzing the past sales data. The distribution pattern between different categories of vegetables is obtained through Pearson's coefficient. Then the correlation coefficients between different vegetable categories were calculated by ridge regression model. In the order of aquatic root vegetables, cauliflower vegetables, leafy vegetables, pepper vegetables, eggplant vegetables and edible mushroom vegetables, the coefficients of sales unit price were -0.535, -0.936, -2.498, -0.658, -0.279 and -1.157 respectively. Then the optimal model and the daily replenishment and pricing strategy for maximizing the revenue were determined by using the SARIMA model. The above model helps the superstore to adjust the replenishment plan and pricing strategy, and to better meet the market demand and increase sales revenue and profit. Also, it can be extended from a specific problem to other products with similar characteristics.