本文研究了基于Matlab的蔬菜类商品自动定价与补货决策优化问题。随着零售业竞争的加剧和消费者需求的多样化,蔬菜类商品的定价与补货决策成为超市经营者面临的重要挑战。本文分析了蔬菜类商品的经营特点,梳理了现有的定价策略和补货决策理论。在此基础上,利用Matlab软件,结合蔬菜销售数据,考虑了蔬菜的平均损耗率、预期销售量等因素下构建了自动定价模型,实现了基于成本加成策略的定价优化。研究过程中,运用了SPSSPRO的频数分析、皮尔逊相关系数分析等方法,揭示了蔬菜销售量的分布特征和品类间的关联性。此外,设计了补货决策优化模型,通过模拟退火算法、粒子群优化算法等智能优化方法,得出了最佳的自动定价策略及补货量。实证研究结果表明,本文提出的模型能够显著提高蔬菜类商品的销售效率和利润水平。This paper studies the automatic pricing and replenishment decision-making optimization of vegetable products based on Matlab. With the intensification of retail competition and the diversification of consumer demand, the pricing and replenishment decisions of vegetable products have become an important challenge for supermarket operators. This paper analyzes the operating characteristics of vegetable commodities and combs the existing pricing strategy and replenishment decision theory. On this basis, using Matlab software, combined with vegetable sales data, considering the average loss rate of vegetables, expected sales and other factors, an automatic pricing model was constructed to achieve pricing optimization based on cost-plus strategy. In the course of the study, SPSSPRO frequency analysis, Pearson correlation coefficient analysis and other methods were used to reveal the distribution characteristics of vegetable sales and the correlation between categories. In addition, the replenishment decision-making optimization model is designed, and the optimal automatic pr
本文构建了公共部门生产企业进入市场的一般均衡模型,利用2000—2006年度中国工业企业数据库和海关数据库合并数据,通过ACF修正后得到无偏一致的成本加成,随后验证了De Loecker et al.(2016)提出的“成本—价格传递”理论。研究发现在样本期间内,控制了不随时间变动的企业—产品层面的成本加成率后,边际成本的变化能够在90%的程度上解释价格的变化。最后,本文分析了企业进出口行为下成本加成与资源配置效应,发现企业从单纯国内销售转向出口兼具内销,能够降低企业内部资源错配,提高资源配置效率。本文的研究拓展了以往成本加成理论,将成本加成纳入“国际+国内”双维度背景下考察,给目前我国“双循环”发展提供了政策启示。
