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  4. Vol 7, Issue 11, 2023

Supermarket Vegetable Commodities Based on TOPSIS-ARIMA Modeling Optimization Research on Replenishment and Pricing

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DOI: 10.23977/acss.2023.071110 | Downloads: 6 | Views: 231

Author(s)

Zhao Xin 1, Lu Wenjun 2, Jiang Manyi 1, Song Zijun 1

Affiliation(s)

1 Department of Economic Management and Law, South China University, Hengyang, 421001, China
2 School of Resources, Environment and Safety Engineering, South China University, Hengyang, 421001, China

Corresponding Author

Zhao Xin

ABSTRACT

With the development of social economy, green and healthy food has gradually become the primary choice of consumers, thus intensifying the competition of vegetable commodities, resulting in the supply of vegetables sometimes exceeds the demand. However, since vegetables are characterized by a short freshness period and deterioration of dish quality, different factors affecting the sales and selling price of the commodities are considered comprehensively to meet the superstore to obtain the maximum return. Firstly, considering that the cost-plus pricing of vegetable commodities has a strong correlation with the discount price, transportation loss rate and storage time, the Topsis model is established to evaluate the different degrees of influence of the above factors, which results in the degrees of influence of the discount price, the transportation loss rate and the storage time on the cost-plus pricing of 21%, 42% and 37%, respectively. Secondly, we calculated the values of the above four indexes and obtained the linear fitting function between the total sales volume and the indexes, and concluded that the discount price is positively related to the total sales volume, with the maximum slope of 9.3218 and the minimum of 0.64; while the cost-plus pricing is negatively correlated with the total sales volume, with the minimum slope of -13.12 and the maximum slope of -0.944, which indicates that when the discount degree is bigger and the cost-plus pricing is lower, each vegetable category will be affected by the discount price and the cost-plus pricing. The lower the discount level and the lower the cost-plus pricing, the higher the sales volume of each vegetable category. Then the autoregressive model (AR) and autoregressive integral sliding average model (ARIMA) are used to fit the maximum value of interest to the sales price and sales volume of cauliflower and aquatic roots and tubers over time in three years to form a training set, and finally the daily replenishment total and pricing of each vegetable category in the coming week are predicted to give advice to the superstores on replenishment and pricing to maximize the revenue of the superstores.

KEYWORDS

Autoregressive modeling, autoregressive integral sliding average modeling, cost-plus determination

CITE THIS PAPER

Zhao Xin, Lu Wenjun, Jiang Manyi, Song Zijun, Supermarket Vegetable Commodities Based on TOPSIS-ARIMA Modeling Optimization Research on Replenishment and Pricing. Advances in Computer, Signals and Systems (2023) Vol. 7: 65-73. DOI: http://dx.doi.org/10.23977/acss.2023.071110.

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