Research Article
Research on Automatic Replenishment and Pricing Strategy of Vegetables Based on Dynamic planning of targets
@INPROCEEDINGS{10.4108/eai.23-2-2024.2345941, author={Shihua Cai and Tainian Wang and Wen Yuan and Qing Zhu and MengHuang Hu and Liyan He and Chunshan Jin}, title={Research on Automatic Replenishment and Pricing Strategy of Vegetables Based on Dynamic planning of targets}, proceedings={Proceedings of the 4th International Conference on Informatization Economic Development and Management, IEDM 2024, February 23--25, 2024, Kuala Lumpur, Malaysia}, publisher={EAI}, proceedings_a={IEDM}, year={2024}, month={5}, keywords={auto-replenishment; cost-plus pricing; dynamic planning of targets; linear regression models}, doi={10.4108/eai.23-2-2024.2345941} }- Shihua Cai
Tainian Wang
Wen Yuan
Qing Zhu
MengHuang Hu
Liyan He
Chunshan Jin
Year: 2024
Research on Automatic Replenishment and Pricing Strategy of Vegetables Based on Dynamic planning of targets
IEDM
EAI
DOI: 10.4108/eai.23-2-2024.2345941
Abstract
As the national living standard continue to improve, the demand for goods across all categories in shopping malls is increasing, particularly for vegetable products, which are considered to be necessities of life. After preprocessing the data in the Vegetable Industry Data In-depth Research and Analysis and Development Strategic Planning Report, this study establishes a linear regression model by Pearson correlation coefficient method. Additionally, it transforms the replenishment and pricing strategy problem into a backpack problem under dynamic programming by using time series analysis and Holt-Winter smoothing index method. It is found that the backpack problem under dynamic programming can model the automatic replenishment of vegetables, and predict the replenishment volume of each category and single product to gram units through the sales volume of each category and each single product, which is convenient for vegetable merchants to efficiently price and purchase the corresponding vegetable categories and quantities reasonably.
