This paper studies the relationship between vegetable sales volume and the effect of season on pricing. MATLAB was used to normalize the sales volume of category and single product, and descriptive statistical analysis was used to calculate the mean, variance and skewness, and the distribution of edible fungi was concentrated, while the distribution of cauliflower was close to normal, and the sales volume distribution of single product was also obtained. SPSS was used to analyze the relationship between category and single product sales, and Pearson correlation analysis was used to find that caullower and nightshade had a significant correlation. Among single products, beef head lettuce had the greatest correlation with Xixia mushroom. Multiple linear regression model was used to analyze the model equation of the total sales volume of different categories in different quarters, and 2022.6.30-2023.6.30 was divided into four quarters, and the sales volume of the next week was predicted by ARIMA model.

Yashi Guo, Xiaozhen Chen. Research on automatic pricing of vegetable commodities based on optimization model. Academic Journal of Business & Management (2024) Vol. 6, Issue 5: 147-153. https://doi.org/10.25236/AJBM.2024.060520.

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