Pricing and replenishment strategy formulation for the fresh produce market

Abstract

To improve the profit margin of the fresh supermarket and optimize the pricing and replenishment strategies of goods, this article provides a time series analysis of the sales volume of various categories and individual items of vegetables. The sales volume and the relationship with time are analyzed on a monthly, quarterly, and annual basis. The article discovers the seasonal and cyclical patterns in the sales volume of vegetable categories and individual items. Using the Spearman correlation coefficient and hypothesis testing, the study reveals strong positive correlations in the sales volume of cauliflower and leafy flower products, as well as strong negative correlations in the sales volume of eggplant and aquatic root and stem products. To formulate pricing strategies for the fresh supermarket in the coming week, the article uses the ARIMA model to forecast the daily total sales volume of various categories. It also constructs a planning model for maximizing the revenue of the fresh supermarket, taking expected profit margin, discount factors, and daily replenishment total as independent variables. The simulated annealing algorithm is employed to solve this model, and the result indicates that the maximum revenue for the fresh supermarket in the coming week is 4269.6 yuan. The article provides procurement and pricing strategies for the fresh supermarket in the next week based on this analysis.