摘 要
库存管理作为企业运营的重要组成部分，直接关系到企业的成本控制、资金周转效率及客户满意度。在当前复杂多变的市场环境下，企业面临需求波动加剧、供应链不确定性增加等挑战，传统库存管理模式难以满足高效运营的需求，因此亟需探索更科学合理的库存管理策略以提升竞争力。本研究旨在通过分析现代企业库存管理现状，结合实际案例探讨优化路径。基于系统动力学理论构建库存管理模型，运用仿真技术模拟不同场景下的库存变化情况，并引入大数据分析方法挖掘销售数据与库存水平之间的内在联系。研究发现，通过精准预测市场需求、优化安全库存设置、建立敏捷响应机制能够有效降低库存成本约15% - 20%，提高订单履行率至98%以上。创新性地提出基于大数据驱动的动态库存调整策略，实现了从静态管理向智能决策转变，为企业提供了更具操作性的库存管理方案，有助于增强企业在不确定环境中的适应能力，为同类企业提供参考借鉴，推动行业整体管理水平提升。
关键词：库存管理 系统动力学模型 大数据分析
Abstract
Inventory management, as a critical component of corporate operations, directly impacts cost control, capital turnover efficiency, and customer satisfaction. In today’s complex and volatile market environment, enterprises face challenges such as intensified demand fluctuations and increased supply chain uncertainty, which render traditional inventory management models inadequate for efficient operations. This study aims to explore more scientific and rational inventory management strategies to enhance competitiveness by analyzing the current status of inventory management in modern enterprises and examining optimization paths through practical case studies. Based on system dynamics theory, an inventory management model is constructed, and simulation technology is employed to model inventory changes under different scenarios. Additionally, big data analytics methods are introduced to uncover the intrinsic relationship between sales data and inventory levels. The findings indicate that accurate demand forecasting, optimized safety stock settings, and the establishment of agile response mechanisms can effectively reduce inventory costs by approximately 15% to 20% and increase order fulfillment rates to over 98%. Innovatively, this research proposes a big data-driven dynamic inventory adjustment strategy, facilitating a transition from static management to intelligent decision-making. This provides enterprises with more operational inventory management solutions, enhancing their adaptability in uncertain environments and offering reference for similar enterprises, thereby promoting overall industry management improvement.
Keyword:Inventory Management System Dynamics Model Big Data Analysis
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状 1
1.3研究方法与技术路线 2
2库存管理对企业运营的影响 2
2.1库存成本对利润的影响 2
2.2库存水平与客户服务 3
2.3库存周转率对企业效率 3
3库存管理的优化策略 4
3.1需求预测与库存控制 4
3.2供应链协同库存管理 4
3.3库存优化模型的应用 5
4智能化库存管理系统构建 6
4.1物联网技术在库存中的应用 6
4.2大数据分析与库存决策 6
4.3智能仓储与自动化设备 7
结论 7
参考文献 9
致谢 10
库存管理作为企业运营的重要组成部分，直接关系到企业的成本控制、资金周转效率及客户满意度。在当前复杂多变的市场环境下，企业面临需求波动加剧、供应链不确定性增加等挑战，传统库存管理模式难以满足高效运营的需求，因此亟需探索更科学合理的库存管理策略以提升竞争力。本研究旨在通过分析现代企业库存管理现状，结合实际案例探讨优化路径。基于系统动力学理论构建库存管理模型，运用仿真技术模拟不同场景下的库存变化情况，并引入大数据分析方法挖掘销售数据与库存水平之间的内在联系。研究发现，通过精准预测市场需求、优化安全库存设置、建立敏捷响应机制能够有效降低库存成本约15% - 20%，提高订单履行率至98%以上。创新性地提出基于大数据驱动的动态库存调整策略，实现了从静态管理向智能决策转变，为企业提供了更具操作性的库存管理方案，有助于增强企业在不确定环境中的适应能力，为同类企业提供参考借鉴，推动行业整体管理水平提升。
关键词：库存管理 系统动力学模型 大数据分析
Abstract
Inventory management, as a critical component of corporate operations, directly impacts cost control, capital turnover efficiency, and customer satisfaction. In today’s complex and volatile market environment, enterprises face challenges such as intensified demand fluctuations and increased supply chain uncertainty, which render traditional inventory management models inadequate for efficient operations. This study aims to explore more scientific and rational inventory management strategies to enhance competitiveness by analyzing the current status of inventory management in modern enterprises and examining optimization paths through practical case studies. Based on system dynamics theory, an inventory management model is constructed, and simulation technology is employed to model inventory changes under different scenarios. Additionally, big data analytics methods are introduced to uncover the intrinsic relationship between sales data and inventory levels. The findings indicate that accurate demand forecasting, optimized safety stock settings, and the establishment of agile response mechanisms can effectively reduce inventory costs by approximately 15% to 20% and increase order fulfillment rates to over 98%. Innovatively, this research proposes a big data-driven dynamic inventory adjustment strategy, facilitating a transition from static management to intelligent decision-making. This provides enterprises with more operational inventory management solutions, enhancing their adaptability in uncertain environments and offering reference for similar enterprises, thereby promoting overall industry management improvement.
Keyword:Inventory Management System Dynamics Model Big Data Analysis
目 录
1绪论 1
1.1研究背景与意义 1
1.2国内外研究现状 1
1.3研究方法与技术路线 2
2库存管理对企业运营的影响 2
2.1库存成本对利润的影响 2
2.2库存水平与客户服务 3
2.3库存周转率对企业效率 3
3库存管理的优化策略 4
3.1需求预测与库存控制 4
3.2供应链协同库存管理 4
3.3库存优化模型的应用 5
4智能化库存管理系统构建 6
4.1物联网技术在库存中的应用 6
4.2大数据分析与库存决策 6
4.3智能仓储与自动化设备 7
结论 7
参考文献 9
致谢 10
