不对称信息下具有需求预测更新的供应链合同协调研究

在具有需求预测更新的计划模型中,信息不对称和双重定价问题仍然在困扰着上下游企业间的关系。本文在报童模型和贝叶斯分析模型的基础上对不对称信息下具有需求预测更新的供应链系统进行了描述,并分析了信息不对称和双重定价问题。而后通过运用委托代理理论的激励原理设计最小订货比例合同,激励零售商共享其私人信息来消除双方的信息不对称,通过设计补贴合同来消除双重边际化造成的低效率,进而实现供应链上下游企业间的协调运作。最后通过运用百佳汽车公司与一汽大众供应链系统的运营数据,计算了两个合同的参数,进一步证明了最小订货比例合同和补贴合同的有效性。     

预测精度和成本双时变的短生命周期产品供应链优化与协调

对于提前期可压缩的短生命周期产品供应链,压缩提前期可以提高销售商的需求预测精度,但增加了制造商的生产成本,因而供应链面临何时订货、订多少,以及如何实现Pareto改进的挑战。通过建立数学模型并求解,分析了分散系统和集中系统的最优决策,进一步开发了一个激励方案以实现供应链成员之间的协调。研究结果表明:具有订货回馈与惩罚的动态批发价契约能够有效协调双时变参数供应链,契约参数α在一定范围内取值可实现供需双方共赢。     

两级供应链订货批量联合决策

本文针对单供应商和单零售商的两级非一体化供应链，分析了供需双方的订货批量、生产批量优化问题，比较分析了分散决策和联合决策过程，证明了联合决策能降低供应商和整个供应链的成本，但是会增加零售商的成本。     

供应链中基于信息更新的订货时间及价格联合决策研究

文章考虑在信息可更新的情况下,由一个制造商和一个零售商组成的供应链中订货时间及价格的联合决策问题.在模型中,制造商为零售商提供多次订货时间选择及相应的订货价格,而零售商可以在销售季节开始前自由选择订货时间并享受相应的价格.文章以不同订货时间对信息更新程度的影响为着眼点,将订货时间作为内生决策变量,突破了已有文献中仅限于两次订货时间选择的局限,分别从集中决策和分散决策两个角度建立供应链节点企业的利润模型,并在分散决策情况下引入收益共享契约,寻找帕累托改进.最后通过数值试验证明了该模型的有效性.     

随机供求下二级农产品供应链期权合同协调研究

提出了完全竞争市场下的单个供应商与零售商构成的两级农产品供应链模型,其中,供应商仅有一次投产机会且产出随机,零售商面临随机的市场需求。零售商在供应商投产之前下订单,在销售季节来临时零售商更新市场需求信息,并确定最终期权购买量;当供应商无法满足零售商订货,将通过现货市场等渠道补足。研究发现,期权合同能够增大供应链整体利润,并通过仿真分析了各参数对期权合同协调效果的影响,该项研究成果对农产品供应链的协调具有一定指导作用。     

考虑批发价格更新的易逝品的零售商订货策略

易逝品的供应链管理作为供应链管理的一个重要分支,日益受到关注和重视。易逝品供应链管理的一个核心问题就是:制造商如何吸引零售商尽早订货和零售商如何针对制造商的吸引措施来进行合理订货。本文研究考虑批发价格更新的易逝品的零售商的订货策略,制造商通过为零售商提供不同批发价格的两次订货机会,来实现制造商和零售商的共赢。通过对开始时刻和批发价格更新后的系统进行建模和讨论,得到了制造商提供的两次不同的批发价格应满足的条件和零售商应该采取的优化的订货与调整策略。     

需求预测更新情形下的供应链Stackelberg博弈与协调研究

在贝叶斯需求预测更新的情形下,从供需博弈角度探讨了易逝品供应链库存管理的基本问题:什么时间订、订多少以及订货价格如何决定。建立了制造商为主方、零售商为从方的供需Stackelberg博弈模型,其中制造商在低价多量与高价少量之间权衡,零售商在低成本低预测精度与高成本高预测精度之间进行权衡。分析了模型最优解的存在性,设计了两层规划的分段迭代算法,并通过数值例子说明了模型与算法的有效性。进一步,针对Stackelberg博弈中出现的双重边际效应,提出了实现供应链协调的契约形式,论证了实现供应链协调的条件。     

基于Bayes需求预测更新的供应链合作策略研究

在预测误差与提前期成对数线性关系,赶工成本与提前期成分段线性关系条件下,研究了基于Bayes需求预测更新的易逝品供应链合作策略问题.通过建立零售商独立决策的优化模型,讨论了模型最优解的存在性,论证了供应链合作的必要性.进一步提出了三参数的供应链风险分担契约来协调分散决策的供应链,分析了实现供应链渠道协调的条件.并通过数值分析和参数的灵敏度分析说明了上述结论以及算法.分析结果表明,这种供应链契约不仅能够实现供应链利润最大化,而且能够通过契约参数的调整,按照供应链成员增值能力的大小灵活划分供应链成员之间的利润分配比例.     

供应链库存分散决策研究

本文研究两级供应链库存问题,供应链包含一个客户和一个生产商.通过建立客户订货库存模型和生产商生产库存模型得到供应链库存模型.采用分散决策方法获得最优解,即最佳订货量和最佳订货次数.在此基础上,使用算例对最优解进行了数值分析.     

双向期权在供应链协调中的应用

本文分析了在由批发价格合同和双向期权合同组成的合同菜单下零售商的最优订货策略,并给出了能够协调供应链的合同菜单形式。本文所给出的合同菜单形式具有独立于随机需求的概率分布的性质,从而具有很好的适用性和鲁棒性。     

不确定需求情境下的供应链预测契约设计

以报童模型为基础,研究了在由单一生厂商和零售商组成的供应链系统中,生产商如何通过契约设计来影响零售商的需求预测行为,使其收益最大化的问题。文章基于静态博弈模型对此问题进行了分析,发现在整合供应链情境下,当需求预测成本较小时选择预测能够获得更高的期望收益;在分散式供应链情境下,当生产商选择预测契约时,预测成本最终由生产商承担,且其期望收益为预测成本的减函数,而选择无预测契约时则为预测成本的非减函数;最后通过生产商期望收益对比,给出了最优策略。     

A Supply Chain with a Service Requirement for Each Market Signal

We study a single‐period two‐stage service‐constrained supply chain with an information update. The buyer has two procurement opportunities with the second one after observing a market signal, which updates the demand forecast. He also commits to a service level after observing the market signal. We derive his optimal ordering decisions and show that the critical market signal, the optimal first‐stage order quantity, and the optimal expected profit are monotone with respect to the target service level. We also discuss the impact of the forecast quality on the optimal decisions. We show that the optimal first‐stage order quantity may not be monotone with respect to information accuracy, as is in the case without the service constraint. In addition, we extend our analysis to the situation when an order cancellation is allowed upon the observation of the market signal. We also compare the results obtained for the problems with and without an order cancelation. Finally, we discuss the supply chain coordination issue and find that a buyback contract can also coordinate the supply chain in the presence of the service constraint.     

基于需求信息更新和短缺量延期供给的易逝品供应链期权契约研究

为了降低供给与需求的不匹配,引入期权契约讨论三阶段生产和订购策略:零售商在第1阶段发出固定订单;然后在第1阶段和第2阶段之间更新需求预测,并在第2阶段调整固定订购量同时购买期权;第3阶段满足市场需求,对销售季末短缺量以执行期权和紧急订购相结合的方式实行延期供给。契约参数包含期权购买价格、执行价格和延期供给对应的批发价,三者线性相关;期权契约下,制造商不存在投机动力。根据易逝品的特征,对生产和订购模型进行仿真计算和分析,结果表明:供应链及其成员的利润都得到帕累托改进,系统利润增量的分配随期权购买价格发生变化。     

具有两阶段生产模式和需求信息更新的供应链契约研究

针对二级供应链,在基于Stackelberg博弈的批发价契约中,分析了折扣价格与零售商最优提前订购量的关系及对契约双方期望收益的影响;设计了价格折扣与回购联合的协调契约,分析了供应链系统的最优提前生产量、供应链协调条件及协调契约下制造商和零售商的期望收益变化,并在协调契约不满足制造商的个体理性约束时,提出采用不对称Nash谈判模型设计两阶段生产与订购的回购契约,在保证供应链系统整体绩效最优的条件下,使制造商和零售商利润都能得到满意增长。研究表明,三级供应链实行两阶段订购的必要条件是分销商与零售商的最优提前订购量相等,与二级供应链相比,价格折扣契约下三级供应链效率更低,但价格折扣与回购联合的契约同样能协调三级供应链,该协调契约满足零售商与分销商激励相容约束。     

基于条件风险值理论的供应链优化与协调模型研究

本文将近年来发展起来的金融风险控制工具--条件风险值,引入具有风险规避特性的供应链优化与协调问题的研究.建立了随机需求下由具有不同风险规避特性的单个供应商与单个零售商组成的两级供应链的条件风险值模型和基于条件风险值的最优订购量模型及协调供应链的收入共享契约模型,并对模型进行了分析,揭示了供应商和零售商的风险规避程度对最优订购量、批发价格及供应链协调的影响.最后通过一个算例对模型进行了仿真,仿真结果进一步验证了本文的研究结论.     

Optimizing Customer Forecasts for Forecast‐Commitment Contracts

We study a “Forecast‐Commitment” contract motivated by a manufacturer's desire to provide good service in the form of delivery commitments in exchange for reasonable forecasts and a purchase commitment from the customer. The customer provides a forecast for a future order and a guarantee to purchase a portion of it. In return, the supplier commits to satisfy some or all of the forecast. The supplier pays penalties for shortfalls of the commitment quantity from the forecast, and for shortfalls of the delivered quantity from the customer's final order (not exceeding the commitment quantity). These penalties allow differential service among customers. In Durango‐Cohen and Yano (2006), we analyzed the supplier's problem for a given customer forecast. In this paper, we analyze the customer's problem under symmetric information, both when the customer is honest and when he strategically orders more than his demand when doing so is advantageous. We show that the customer gains little from lying, so the supplier can use his control over the contract parameters to encourage honesty. When the customer is honest, the contract achieves (near‐)coordination of the supply chain in a great majority of instances, and thus provides both excellent performance and flexibility in structuring contracts.     

Pay‐Back‐Revenue‐Sharing Contract in Coordinating Supply Chains with Random Yield

We consider coordination issues in supply chains where supplier's production process is subject to random yield losses. For a simple supply chain with a single supplier and retailer facing deterministic demand, a pay back contract which has the retailer paying a discount price for the supplier's excess units can provide the right incentive for the supplier to increase his production size and achieve coordination. Building upon this result, we consider coordination issues for two other supply chains: one with competing retailers, the other with stochastic demand. When retailers compete for both demand and supply, they tend to over‐order. We show that a combination of a pay back and revenue sharing mechanism can coordinate the supply chain, with the pay back mechanism correcting the supplier's under‐producing problem and the revenue sharing mechanism correcting the retailers' over‐ordering problem. When demand is stochastic, we consider a modified pay‐back‐revenue‐sharing contract under which the retailer agrees to not only purchase the supplier's excess output (beyond the retailer's order), but also share with the supplier a portion of the revenue made from the sales of the excess output. We show that this contract, by giving the supplier additional incentives in the form of revenue share, can achieve coordination.     

Mechanisms to Induce Buyer Forecasting: Do Suppliers Always Benefit from Better Forecasting?

In this study, we consider a supplier's contract offerings to a buyer who may obtain improved forecasts for her demand over time. We investigate how the supplier can take advantage of the buyer's better forecasts and what kind of contracts he should offer to the buyer in order to maximize his profits. We model a natural forecast evolution where the buyer can obtain a more accurate forecast closer to the selling season. We assume there is information asymmetry between the buyer and the supplier at all times in that the buyer understands her demand better than the supplier. Three types of contracts that the supplier can offer are considered: (1) one where a contract is offered before the buyer has a chance to obtain improved forecasts, (2) one where a contract is offered after the buyer has obtained improved forecasts, and (3) a contingent (dynamic) contract which offers an initial contract to the buyer before she obtains improved forecasts, followed by a later contract (contingent on the initial contract) offered after improved forecasts have been obtained. We consider two scenarios: (1) where the supplier is certain that the buyer can obtain more accurate forecasts over time, and (2) where the supplier is uncertain about the buyer's forecasting capability (or forecasting cost). In the first scenario, we show that among the three types of contracts, the contingent contract is always the most profitable for the supplier. Furthermore, using the contingent contract, the supplier always benefits from higher accuracy of the buyer's demand forecasts. In the second scenario, we explicitly model the supplier's level of certainty about the buyer's capability of obtaining better forecasts, and explore how the supplier can design contracts to induce the buyer to obtain better forecasts when she is capable.