A Study on Pricing and Replenishment Decision of Vegetable Commodity Based on Demand-Volume-Cost Model

Xufeng Li; Qingxin Huang

doi:10.54097/vnhnwz49

Authors

Xufeng Li
Qingxin Huang

DOI:

https://doi.org/10.54097/vnhnwz49

Keywords:

LM algorithm, Arima model, Planning model, Optimization model.

Abstract

This paper aims to develop pricing and replenishment strategies for vegetable commodities in superstores. The characteristics of perishability, short life cycles, and other factors make it challenging to determine pricing and replenishment decisions. The study proposes the use of a weighting method to define the price for each vegetable category. Additionally, sub-models are established for market demand prediction, price-volume relationship, and cost-plus pricing. The ARIMA time series forecasting model is used for market demand forecasting, while a logarithmic model, fitted non-linearly using the L-M algorithm, is employed for the price-sales model. Through the derived sub-model expressions, the optimal replenishment volume and markup rate that maximize the superstore's profit are determined. The calculated maximum profit from selling vegetable goods in the coming week is 2179.68 yuan. In this paper, a profit model is constructed by considering the relationship between demand, sales volume, and cost, which can provide suggestions for superstores to improve the economic efficiency of vegetable products.

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