Author(s)

Xiaoyu Li ¹, Xu Liu ¹, Yixuan Zhong ¹

Affiliation(s)

¹ School of Information, Xi'an University of Finance and Economics, Xi'an, 710100, China

Corresponding Author

Yixuan Zhong

ABSTRACT

Fresh food superstores play a crucial role in people's lives, providing people with a variety of fresh ingredients. While ensuring that customers' needs are met, this paper investigates how to carry out reasonable pricing and replenishment, so as to maximize the superstore's total revenue. In order to solve this problem, this paper establishes a time series forecasting model, including ARIMA model and exponential smoothing method, which is used to forecast the total sales of each vegetable category in the coming week. Based on this, the pricing of each category of vegetables was calculated by cost-plus pricing method. Then, the practical constraints of the superstore are considered: the total number of saleable items is controlled at 27-33, and the order quantity of each item satisfies the minimum display quantity of 2.5 kg. Based on these constraints, the objective benefit maximization function is constructed to screen out the eligible individual items, and the daily replenishment and pricing strategies for these items are calculated. Through the study, the conclusion of this paper is that superstores should flexibly adjust their daily replenishment plans based on forecasted replenishment and actual sales to ensure that inventory meets customer demand while avoiding inventory backlogs and waste. Attracting customers to buy products packaged in per-serving bundles increases single sales, thus maximizing profits.

KEYWORDS

Time Series Analysis, Vegetable Sales, Pricing Optimization

CITE THIS PAPER

Xiaoyu Li, Xu Liu, Yixuan Zhong, Research on sales and pricing optimization of vegetable category based on ARIMA model and exponential smoothing method. Information Systems and Economics (2024) Vol. 5: 170-179. DOI: http://dx.doi.org/10.23977/infse.2024.050323.

REFERENCES

[1] Pan Xiaofei, Xie Zhiheng, Wang Shuyun. Optimization decision of fresh food superstore preservation efforts and pricing considering loss aversion[J]. Highway Transportation Science and Technology, 2022, 39(06):177- 185+190.
[2] Nie Yuxuan. Research on automatic pricing and replenishment strategy of fresh commodities based on ARIMA prediction optimization model--taking vegetable commodities as an example[J]. Commercial Exhibition Economy, 2024(05)
[3] Wei Zihang. Association analysis of fresh vegetables purchase based on Apriori algorithm[J]. Software, 2024, 45(01): 131-133.
[4] Yang Shuai, Huang Xiangmeng, Wang Junbin. Research on joint optimization strategy of shelf allocation and pricing for fresh food [J]. Supply Chain Management, 2022, 3(08):49-59.
[5] Liu Xiaoyun. Research on inventory control of community fresh food retail terminal considering the change of customer flow [D]. Hangzhou University of Electronic Science and Technology, 2023.

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