供应商管理库存及其协调研究
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摘要
随着经济的发展和环境的变化,企业与企业间的竞争已转变为供应链与供应链间的竞争。供应链管理中,库存管理模式的优化已成为制约供应链性能的关键环节。供应商管理库存模式已引起企业界和学术界的关注。
     本文对供应商管理库存的理论基础、增值机理、实施条件及基于价格外生、价格内生、需求与努力相关、数量运输的供应商管理库存协调等问题进行了系统研究,主要内容如下:
     (1)供应商管理库存的理论基础
     提出了供应商管理库存的定义,系统论述了供应链管理、准时制和零库存、快速反应和有效客户反应、业务流程重组、信息技术、合作竞争、核心竞争力和外包、交易成本及委托代理等理论对供应商管理库存产生及其发展的影响。
     (2)供应商管理库存的增值机理
     从客户和供应商视角,分析经济增加值要素,如:销售收入、销售成本、费用、库存、其他流动资产和固定资产等对供应商管理库存的价值增值机理,并提出相应的措施。
     (3)供应商管理库存的实施
     运用交易成本理论分析实施供应商管理库存的关键经济决定因素。以下游企业为例,探讨三种情形下实施供应商管理库存的边界条件:①不考虑专业化、规模经济与核心能力提升;②考虑专业化与规模经济、但不考虑核心能力提升;③同时考虑专业化、规模经济与核心能力提升。
     以上游企业双方为例,探讨报童环境下实施供应商管理库存的条件。通过分析与比较传统库存管理和供应商管理库存模式中供应商和零售商的期望收益,给出实施供应商管理库存的“帕累托改进”或“卡尔多——希克斯改进”条件。
     (4)基于价格外生的供应商管理库存协调
     当零售价格为外生变量时,提出价格补贴机制和收益共享机制协调供应商管理库存。分别构建两种机制的传统模型、Stackelberg博弈模型和NASH协商模型,并进行数值分析。
     (5)基于价格内生的供应商管理库存协调
     当零售价格为内生变量,市场需求与零售价格为相乘型需求时,建立收益共享机制的Stackelberg博弈模型、NASH协商模型和收益共享与返利组合机制模型协调供应商管理库存;当零售价格为内生变量,市场需求与零售价格为相加型需求时,建立收益共享机制的Stackelberg博弈模型、NASH协商模型协调供应商管理库存,并给出最优参数的确定方法。
     (6)基于需求与努力相关的供应商管理库存协调
     当需求与努力水平之间为相加型或相乘型需求时,分别构建集成供应商管理库存供应链和三种博弈结构(双方同时决策的NASH静态博弈、零售商领导的Stackelberg博弈、供应商领导的Stackelberg博弈)下供应商管理库存供应链模型,确定并比较模型中的努力水平和库存水平,提出零售商承担部分滞销成本,供应商承担部分努力成本的方法协调供应商管理库存,并给出最优参数的确定方法。
     (7)基于数量运输的供应商管理库存协调及其与基于时间运输的供应商管理库存协调的比较
     以平均期望成本最小为目标建立基于数量运输的供应商管理库存协调模型,采用离散算法求解最优发货次数、发货数量和目标库存水平。针对基于时间运输的供应商管理库存协调中最优目标库存水平为零和不为零的情形,运用演绎和数值分析方法比较基于时间运输与基于数量运输的VMI协调中平均期望成本及成本节约率的大小。
With economic development and environmental change, the competition among enterprises has turned into the competition among supply chains. In supply chain management, the optimization of inventory management mode has become the indispensable process in determing the property of supply chain. The Vendor-managed inventory (VMI) mode has aroused the great attention in the enterprise and academic fields.
     The paper studies on issues as the theoretical foundation, appreciation mechanism and implementation conditions of VMI, VMI coordination based on exogenous price, endogenous price, supply-effort interrelation and quantity-transportation. Detailed studies are listed as follows:
     (1) Theoretical Basis of Vendor-Managed Inventory
     Proposing the definition of VMI, the paper systematically discourses on a variety of theories like Supply Chain Management, Just in Time and Zero Inventory, Quick Response and Effective Consumer Response, Business Process Reengineering, Information Technology, Cooperative Competition, Core Competency and Outsourcing, Transaction Cost and Principal Agent, all of which can support and boost the birth and development of VMI.
     (2) Appreciation Mechanism of Vendor-Managed Inventory
     Based on the customer and supplier perspectives, the value addition of VMI has been concretely analysed through using Economic Value Added factors like sales revenue, sales cost, inventory, other liquid assets and capital assets, with the corresponding measures being proceeded.
     (3) Implementation of Vendor-Managed Inventory
     Using the transaction cost theory, the decisive economic factors of VMI implementation have been analysed. Acted as the downstream enterprise, the discussions on the boundary conditions of VMI realization have been included. Those conditions are realised under such circumstances in which specialization, scale economy and core competency promotion are not taken into account, or the first two factors are considered yet without core competency promotion, or with all of the three factors being taken into account.
     Acted as both of the upstream ane downstream enterprises, the paper also analyzes and compares the expected profits of suppliers and retailers in the supply chains of Retailer-managed inventory and VMI models, both of which are under newsvendor circumstances. It provides the conditions of Pareto improvement or Kaldor-Hicks improvement involved in the VMI.
     (4) Vendor-Managed Inventory Coordination Based on Exogenous Price
     AS price is exogenous variable, the paper puts forward price subsidiarymechanism and revenue sharing mechanism to coordinate VMI. It sets up the two mechanisms of the traditional models, Stackelberg models and NASH negotiation models. It makes the corresponding numeric examples.
     (5) Vendor-Managed Inventory Coordination Based on Endogenous Price
     AS price is endogenous variable, the relation of demand and price being the multiplicative demand situation, the paper builds up revenue sharing mechanism of Stackelberg model and NASH negotiation model, and revenue sharing and profit return mechanism assembling model. While price is endogenous variable, the relation of demand and price being additive demand situation, it builds up revenue sharing mechanism of Stackelberg model and NASH negotiation model. It provides the confirmation approaches of optimal parameters in the models.
     (6) Vendor-Managed Inventory Coordination Based on Demand and Effort Interrelation
     In the relation of demand and effort level being additive or multiplicative demand situations, the models of integrated supply chain and three game structured VMI supply chains (NASH static game playing in which decision making is mutual, Stackelberg game structure dominated by retailers and Stackelberg game structure dominated by suppliers) have been created. The effort level and inventory level of every model are determined and compared. The coordination approach is proposed, in which retailers undertake part of the unmarketable costs and suppliers partake some of the promotion costs, with the settlement of confirmation approaches about optimal parameters.
     (7)Vendor-Managed Inventory Coordination Based on Quantity-Based Transportation and Comparisons between Quantity-Based Transportation and Time-Based Transportation Policy
     According to the object of least average expectancy cost, the VMI coordination model built on quantity-based transportation has been established. The discrete algorithm is used to settle the optimal delivery frequency, delivery quantity and target inventory level. In regards to the two VMI coordination situations of time-based transportation, in which the optimal target inventory levels being zero and non-zero, the comparisons of average expectancy cost and cost saving rates between the VMI coordination of time-based transportation and quantity-based transportation have been made through deductive inference and numerical example.
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