复杂装备“主制造商——核心供应商”协同研制的知识投入影响要素研究

以复杂装备"主制造商—核心供应商"二级供应链为对象,构建主制造商成本补贴下的Stackelberg博弈模型,研究主制造商最佳知识投入、最佳成本补贴和核心供应商的最佳知识投入,以及主制造商和核心供应商的信息集成能力、知识投入和主制造商给予的成本补贴的关系.结果表明:核心供应商的知识投入与主制造商给予的成本补贴成正比,主制造商的知识投入与成本补贴无关.主制造商对核心供应商成本补贴与自身信息集成能力成正比,与核心供应商信息集成能力成反比.主制造商的知识投入与自身信息集成能力成正比,与核心供应商无关.核心供应商知识投入与主制造商信息集成能力、核心供应商信息集成能力都成正比.并通过仿真验证了以上结论.     

考虑促销努力与生产努力的供应链召回努力策略研究

考虑一条由单个供应商和单个制造商组成的二级供应链,面对产品召回事件,供应商和制造商都可以通过召回努力来降低召回事件发生的概率。本文研究了供应链最优召回努力策略,研究发现双方的召回努力与初始期望单位召回成本和潜在市场规模有关。当潜在市场规模和初始期望单位召回成本都较小时,双方均选择部分召回努力,当潜在市场规模和初始期望单位召回成本都较大时,双方均选择全部召回努力,否则,供应商选择全额召回努力而制造商选择部分召回努力。由于制造商的促销努力与供应商的生产努力是企业扩大市场规模常用的策略,因此,本文还研究了这两种策略分别对供应链召回努力策略的影响。我们发现这两种策略都能降低双方采取全额召回努力时潜在市场规模的门槛,激励双方增加召回努力,降低产品召回概率并增加供应链成员的利润。特别的,我们还对比了这两种策略对双方召回努力的影响,发现当促销努力成本系数与生产努力成本系数都较小时,两种策略对召回努力的影响相同,当生产努力成本系数足够大时,考虑促销努力时双方的召回努力水平更高,否则,考虑生产努力时双方的召回努力水平更高。     

供应中断风险下采购与定价决策分析

供应中断是供应链上的企业可能面临的问题,运用合理的采购策略可以帮助企业有效缓解供应中断风险。本文研究了供应中断下供应商和制造商之间的纵向竞争和两个制造商之间的横向竞争问题。供应商制定批发价,两个制造商采用不同的采购策略进行产量博弈,其中一个制造商采用紧急双源订货策略,另一个采用可靠单源订货策略。论文采用了多阶段博弈模型,分析了制造商之间的合谋与竞争两种行为,求出了供应商和制造商的最优决策,比较了这两种行为对供应商和制造商的影响。通过数值分析,讨论了成本参数和可靠性参数对于最优订货量的影响以及对于采用不同订货策略的制造商期望利润的影响。     

第一密封价格逆向拍卖机制博弈研究

在供应商对拟投标项目成本估计独立、不同分布的条件下,通过建立不公开保留价的第一价格逆向拍卖机制博弈模型,推导了供应商的最优报价策略,博弈均衡存在时采购者最优保留价满足的条件,发现供应商的报价高于他的成本估计,进一步得到了与该采购机制资源配置效率有关的结论:参与投标的人数越多供应商报价溢出成本部分越少;成本越低的供应商期望支付越大.这对于现实采购拍卖的政策建议为:设法让更多供应商参与竞标,能有效选择优势供应商、降低采购成本、增加社会福利.     

考虑低碳偏好和产出随机的供应链两级碳减排策略

考虑消费者低碳偏好和制造商的产出随机性,以包含一个供应商和一个制造商的低碳供应链为研究对象,供应商和制造商均需进行碳减排技术研发投入.通过构建供应商主导、制造商追随情形下的Stackelberg博弈模型,讨论低碳供应链的两级主体碳减排策略.研究结果表明,消费者对原材料和产成品的低碳偏好对供应商和制造商的碳减排研发投入均有促进作用,且均有利于供应商和制造商提高利润水平,但对制造商利润的影响更加直接和明显;制造商的产出随机性对供应商和制造商的碳减排水平以及利润均产生不利影响,并且抑制制造商的生产积极性.     

基于多Agent的Supply-Hub库存策略建模与仿真研究北大核心

Supply-Hub是一种能较好地解决装配式供应链协同运作问题的供应链运作模式,其库存参数设置对于平衡上游供应商与下游制造商之间的利益,吸弓l供应商加入Supply-Hub非常关键.建立了由两个供应不同零部件的供应商向制造商补货时的供应商多周期成本模型,采用多Agent仿真方法,研究了三种情形下(s,S)库存策略参数的变动对供应商及制造商的影响,以期为Supply-Hub运营商合理确定库存策略参数提供一定参考.     

基于多Agent的Supply-Hub库存策略建模与仿真研究

Supply-Hub是一种能较好地解决装配式供应链协同运作问题的供应链运作模式,其库存参数设置对于平衡上游供应商与下游制造商之间的利益,吸弓l供应商加入Supply-Hub非常关键.建立了由两个供应不同零部件的供应商向制造商补货时的供应商多周期成本模型,采用多Agent仿真方法,研究了三种情形下(s,S)库存策略参数的变动对供应商及制造商的影响,以期为Supply-Hub运营商合理确定库存策略参数提供一定参考.     

基于现货市场的供应链博弈模型

构建了现货市场价格及市场需求均不确定的供应链博弈模型,分析了风险中性供应商的批发价决策、风险厌恶制造商的采购决策,证明博弈均衡存在且唯一。通过解析分析及数值实验探讨了风险态度、现货价格和需求波动及其相关性对供应链博弈的影响。结果表明:1)制造商因规避风险会减小采购,这降低了供应链总效用;2)现货市场存在时制造商会减小向供应商采购的数量,这降低了供应商的利润,但提高了供应链总效用;3)现货价格与市场需求的相关关系让供应商掌握主动,但会降低制造商及整个供应链的绩效。     

Supply Hub下基于时间窗的供应链协同研究

以装配系统为研究对象,建立了随机零部件补货提前期下两个供应商对单制造商的准时供货模型.在制造商采取货齐付款的结算方式及交货时间窗模式下,研究了两个供应商的最优交货提前期决策.研究结果表明:一是交货时间窗策略能有效降低供应商的成本,而且时间窗越长,供应商的成本越低,但仅仅依靠单一的交货时间窗策略不能完全协调整个供应链;二是通过调整供应商延迟交货的惩罚成本,如增大对供应商的延迟交货惩罚,可实现供应链的协调.     

不对称信息下产能预定协调机制研究

在按单装配供应链中非关键组件采购成本是制造商私人信息的情况下,就制造商向关键组件供应商预定产能的过程建立动态博弈模型,重点研究如何从第三方的角度协调制造商的产能预定决策,并分析信息不对称对协调机制的影响.研究结果表明:一个菜单式预定合同不仅能诱导制造商披露真实成本信息,还能使供应链达到协调.     

Contracting with an urgent supplier under cost information asymmetry

We investigate a contract setting problem faced by a manufacturer who can procure major modules from an overseas supplier, as well as a local supplier. The overseas supplier is prime and offers quality products, whereas the local supplier is viewed only as a backup, and its products are inferior in quality. As the local supplier needs to put in additional effort to fulfill the urgent orders, it is difficult for the manufacturer to estimate this urgent supplier’s production cost. This asymmetric cost information becomes an obstacle for the manufacturer in managing the urgent supplier. In this paper, we study two types of contingent contracts. One is the common price-only contract, and the other is a contract menu consisting of a transfer payment and a lead time quotation. We construct a Stackelberg game model and evaluate how the involvement of an urgent supplier with private cost information affects performances of the prime supplier and the manufacturer in different scenarios (with or without the urgent supplier, under different contingent contracts). We also conduct numerical experiments to show how the parameters of the contracts affect profits of the manufacturer.     

Retailer��s optimal sourcing strategy by using one major supplier and one emergent supplier

Fast-changing market demand, short product life cycle, and unpredictable events have been enforcing companies in a supply chain to respond to customers’ needs as quickly as possible. While many firms are still seeking a better inventory management within the general business environment, this paper develops an ordering decision support model within a business environment with more unpredictable events. To reduce the uncertainty, a retailer adopts a double sourcing policy with one major supplier and one emergent supplier. Through a two-period dynamic programming model formulation and the simulations based on design of experiments, we analyzed the effects of factors such as penalty cost, backup ratio, purchasing cost ratio, and demand correlation coefficient on retailer’s ordering policy and expected profit. Detailed sensitivity analysis is further conducted based on combinations of penalty cost and backup ratio. Results show that the use of an emergent supplier help increase the retailer’s expected profits. It not only increases the retailer’s upstream sourcing flexibility, but also increases the retailer’s service level with a lower inventory level. As penalty cost or backup ratio increases, the contribution of emergent supplier increases.     

Single versus multiple supplier sourcing strategies

Successful supply chain management necessitates an effective sourcing strategy to combat uncertainties in both supply and demand. In particular, supply disruption results in excessive downtime of production resources, upstream and downstream supply chain repercussions, and eventually a loss in the market value of the firm. In this paper we analyze single period, single product sourcing decisions under demand uncertainty. Our approach integrates product prices, supplier costs, supplier capacities, historical supplier reliabilities and firm specific inventory costs. A unique feature of our approach is the integration of a firm specific supplier diversification function. We also extend our analysis to examine the impact of minimum supplier order quantities. Our results indicate that single sourcing is a dominant strategy only when supplier capacities are large relative to the product demand and when the firm does not obtain diversification benefits. In other cases, we find that multiple sourcing is an optimal sourcing strategy. We also characterize a non-intuitive trade-off between supplier minimum order quantities, costs, and supplier reliabilities. Finally, we examine the robustness of our results through an extensive numerical analysis of the key parameters of our model.     

A comparison of two sourcing tactics for a new component

We compare two sourcing tactics for a manufacturer to purchase a new component to be used in a one-time production run of a new product with uncertain and price-elastic demand. One alternative is to issue a request-for-quote (RFQ), which is where the manufacturer requests a price-quantity schedule from suppliers. The manufacturer uses this information to determine a production quantity and the number of components to purchase from each supplier. The other alternative is to post a bid specifying how the manufacturer’s purchase quantity will depend on the supplier’s component price. The suppliers use this information to compete on quantity.We find that relative to RFQ, which is more challenging for the manufacturer to characterize the supplier response due to the possibility of supplier interaction, the benefit to the manufacturer from posting a bid increases with the number of suppliers due to increased intensity of competition. If the new component is from an emerging industry where there is little mutual awareness among candidate suppliers, then regardless of number of suppliers, expected manufacturer profit is higher under RFQ. Posting a bid is more likely to benefit the manufacturer when the new component is from a more established industry with a high degree of awareness among candidate suppliers.     

Sourcing under incomplete information and negative capacity-cost correlation

We study a sourcing problem where a buyer reserves capacity from a set of suppliers. The suppliers have finite capacity and their unit production cost is a decreasing function of their capacity, implying scale economies. The capacity of each supplier and therefore the cost is his private information. The buyer and other suppliers only know the probability distribution of the supplier’s capacity. The buyer’s demand is random and she has to decide how much capacity to reserve in advance from a subset of suppliers and how much to source from marketplace. In this study we determine the buyer’s optimum reservation quantity and the size of the supply base. We find the presence of such capacity cost correlation leads to supply base reduction.     

A periodic-review inventory system with a capacitated backup supplier for mitigating supply disruptions

We consider a periodic-review inventory system with two suppliers: an unreliable regular supplier that may be disrupted for a random duration, and a reliable backup supplier that can be used during a disruption. The backup supplier charges higher unit purchasing cost and fixed order cost when compared to the regular supplier. Because the backup supplier is used at unplanned moments, its capacity to replenish inventory is considered limited. Analytical results partially characterize the structure of the optimal order policy: a state-dependent (X(i), Y(i)) band structure (with corresponding bounds of X(i) and Y(i) to be given), where i represents the status of the regular supplier. Numerical studies illustrate the structure of the optimal policy and investigate the impacts of major parameters on optimal order decisions and system costs.     

Modeling sourcing strategies to mitigate part obsolescence

Part obsolescence is a common problem across industries, from avionics and military sectors to most original equipment manufacturers serving industrial markets. When a part supplier announces that a part will become obsolete, the OEM can choose from a number of sourcing options. In practice, the three most commonly adopted mitigation strategies are: (1) a lifetime, or life-of-type (LOT), buy from the original supplier; (2) part substitution, which finds a suitable alternative; and (3) line redesign, which modifies the production line to accommodate a new part. We first develop a framework incorporating fixed cost, variable cost, leadtime, demand uncertainty and the discount rate to directly compare and characterize these three sourcing strategies in a static context. We next formulate an integrated sourcing approach that starts with a bridge buy and may continue with part substitution or line redesign when the originals parts are depleted. Through numerical studies, we identify the joint impact of the problem parameters on the static and integrated sourcing strategies and the optimal choice among them. While the integrated sourcing approach outperforms the static ones in many cases it is not a dominant strategy.     

A continuous-review inventory model with random disruptions at the primary supplier

We consider a continuous-review inventory problem for a retailer facing constant customer demand for a single product. This retailer is assumed to follow the well known and widely used order-up-to policy in making replenishment decisions, and can order from two suppliers who differ in reliability and costs. Supplier 1, the primary supplier, is cheaper, but is subject to random disruptions. Supplier 2, the backup supplier or the contingent source, is more expensive, but is perfectly reliable. If Supplier 1 is available when the inventory level at the retailer reaches the reorder point, the retailer orders from Supplier 1. Otherwise, it will wait for a while to see if Supplier 1 can recover from the disruption quickly. If so, it will still get replenishment from Supplier 1 to take advantage of its lower charge. However, the retailer will reroute to the backup supplier if Supplier 1 still does not recover from the disruption when the cap of waiting (the maximal waiting time of the retailer if Supplier 1 is disrupted) is reached. We analytically study the optimal sourcing and replenishment decisions at the retailer, and the impacts of various problem parameters on the optimal decisions. We also conduct extensive numerical experiments to compare different sourcing and replenishment decisions the retailer can make and get further managerial insights into the problem.     

Optimal Contract Design of Supplier-Led Outsourcing Based on Pontryagin Maximum Principle

This paper provides a supplier-led outsourcing model to maximize the supplier’s profits based on a principal-agent framework with both asymmetric cost information and uncertain market demand information described by continuous random variables. The salvage value of the unsold product is processing-cost dependent. By converting the proposed model, which is a dynamic optimization problem, to an optimal control problem, we obtain the analytical form of the optimal supplier outsourcing contract composed of the wholesale price and the transfer payment by applying Pontryagin’s maximum principle. It is shown that the optimal contract is directly related to the supplier’s beliefs about the manufacturer’s unit cost and the salvage value function. The Pontryagin’s maximum principle-based solution method serves as a powerful tool to support the decision making for the best sourcing strategy, and it provides analytical insights for outsourcing management. Finally, numerical examples are presented to illustrate the validness of the theoretical results.