Author(s)

Yichen Du ¹

Affiliation(s)

¹ School of Mathematical Sciences, Henan Institute of Science and Technology, Xinxiang, 453003, China

Corresponding Author

Yichen Du

ABSTRACT

In this paper, in order to explore the distribution pattern and interrelationship among fresh vegetables and to make replenishment decisions for each vegetable category on the same day without exactly knowing the specific single product and purchase price, we use the systematic clustering model and the ARMA model to derive the similarity degree of the sales situation of different single products of vegetables, and the replenishment quantity and pricing strategy for the next seven days of the different categories of sales volume and cost-plus pricing, and we verify the reasonableness of the model by using the leafy and flowery vegetables as an example. The rationality of the model was verified with the example of leafy vegetables, yielding forecast relative errors of 0.1934 and 0.3334, which are in line with the expected situation. From the demand side, the study enables consumers to buy fresh vegetables on the same day. From the supply side, supermarkets can reduce unnecessary waste due to the perishability of vegetables. 

KEYWORDS

Hierarchical Cluster Analysis, ARMA model, autoregressive moving average model, sales forecast

CITE THIS PAPER

Yichen Du, Fresh Vegetable Sales and Pricing Forecasting Based on Systematic Clustering and ARMA Modeling. Information Systems and Economics (2024) Vol. 5: 12-18. DOI: http://dx.doi.org/10.23977/infse.2024.050202.

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