International Journal of New Developments in Engineering and Society, 2023, 7(9); doi: 10.25236/IJNDES.2023.070909.
Yunhang Lv, Xiulan Han, Mengyu Xu, Yunxiang Tan
School of Ecology and Environment, Hainan University, Hainan, Haikou, 507228, China
Vegetable products have the characteristics of short shelf life. If they can't be sold out in time, it will cause waste, which will lead to the loss of merchants. Therefore, it is of great significance to formulate reasonable purchase quantity and pricing strategy. In view of this, this paper studies the purchase quantity and pricing strategy of vegetable commodities by establishing multiple linear regression model, ARIMA time series model and exponential smoothing time model. The results show that: (1) the relationship between consumers' purchase of various vegetables can be understood through correlation analysis; (2) By establishing time series, exponential smoothing model and combining multiple linear regression, the daily sales volume and daily replenishment volume can be better predicted, thus guiding pricing decision. (3) In the process of vegetable pricing, combining the historical pricing method can make the pricing decision more reliable, and adopting different pricing strategies for different vegetables according to consumers' purchasing psychology is conducive to increasing vegetable sales.
Time series model, Multiple linear regression, Exponentially smoothed time series, ABC classification
Yunhang Lv, Xiulan Han, Mengyu Xu, Yunxiang Tan. Study on Vegetable Pricing Based on Time Series and Exponential Smoothing Model. International Journal of New Developments in Engineering and Society (2023) Vol.7, Issue 9: 48-56. https://doi.org/10.25236/IJNDES.2023.070909.
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