International Journal of New Developments in Engineering and Society, 2023, 7(9); doi: 10.25236/IJNDES.2023.070906.
Jinlun Yu, Jiawei Li, Siyuan Wang
School of Automation Science and Engineering, Xi’an Jiaotong University, Xi’an, 710049, China
The comprehensive analysis of sales optimization and individual pricing strategies for vegetable commodities is crucial for the profitability of fresh food supermarkets. Drawing from transaction records of specific vegetable items in a supermarket, this study reveals that different vegetable categories exhibit cyclical patterns in sales over time and certain inter-category correlations exist. Through Pearson correlation analysis, we identified strong sales-time correlations between Shanghai green and Yunnan choy sum (correlation coefficient of 0.94), bamboo leaf vegetables and sweet potatoes (0.96), and Yunnan lettuce and Yunnan choy sum (0.96), suggesting promising sales combinations for supermarkets. An algorithmic approach was employed to derive a functional relationship between sales volume and pricing for different vegetable categories, which generally follows an exponential relationship, albeit with variations among categories. Leveraging transactional big data, we used LSTM time series forecasting to provide optimal restocking quantities and pricing decisions for various vegetable categories from July 1-7, 2023. Ultimately, by offering insights into sales combinations, optimal restocking volumes, and pricing decisions, this paper aids fresh food supermarkets in achieving higher profits and holds practical significance for enhancing the market circulation of fresh produce.
Commodity sales and pricing strategy, Correlation Analysis, LSTM model
Jinlun Yu, Jiawei Li, Siyuan Wang. Research on the optimization of vegetable sales and pricing strategy of single products. International Journal of New Developments in Engineering and Society (2023) Vol.7, Issue 9: 31-36. https://doi.org/10.25236/IJNDES.2023.070906.
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