Stable and Coordinating Contracts for a Supply Chain with Multiple Risk‐Averse Suppliers

We analyze a decentralized supply chain with a single risk‐averse retailer and multiple risk‐averse suppliers under a Conditional Value at Risk objective. We define coordinating contracts and show that the supply chain is coordinated only when the least risk‐averse agent bears the entire risk and the lowest‐cost supplier handles all production. However, due to competition, not all coordinating contracts are stable. Thus, we introduce the notion of contract core, which reflects the agents' “bargaining power” and restricts the set of coordinating contracts to a subset which is “credible.” We also study the concept of contract equilibrium, which helps to characterize contracts that are immune to opportunistic renegotiation. We show that, the concept of contract core imposes conditions on the share of profit among different agents, while the concept of contract equilibrium provide conditions on how the payment changes with the order quantity.     

Dynamic Procurement,Quantity Discounts,and Supply Chain Efficiency

We study a model with a single supplier and a single buyer who interact multiple times before the buyer sells her product in the end‐consumer market. We show that when the supplier uses a wholesale price contract, even under perfect foresight, the supplier, the buyer, and the end consumers benefit from multiple trading opportunities versus a one‐shot procurement agreement.     

Price,Rebate, and Returns Supply Contracts for Coordinating Supply Chains with Price‐Dependent Demands

Channel rebates and returns policies are common mechanisms for manufacturers to entice retailers to increase their order quantities and sales ultimately. However, when the underlying demand depends on the retail price, it has been known that channel coordination cannot be achieved if only one of these mechanisms is deployed. In this article, we show that a policy that combines the use of wholesale price, channel rebate, and returns can coordinate a channel with both additive and multiplicative price‐dependent demands. In addition to determining the sufficient conditions for the contract parameters associated with the equilibrium policy, we show that multiple equilibrium policies for channel coordination exist. We further explore how the equilibrium policy can be adjusted to achieve Pareto improvement. Other issues such as the maximum amount of expected profit that the manufacturer can share under the coordinated channel, the structural properties of the contracts under both the additive and multiplicative price‐dependent demand functions are also discussed.     

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.     

供应链柔性批量订货契约研究

为实现批量订货与柔性采购相结合的目标,用一定折扣换取一定的柔性,从而实现供应链内部的协调及风险的分摊。在供应链中,从卖方角度,希望买方以稳定的(最好是不变的)订货量订货,以保证稳定的销售,减小牛鞭效应的影响,为此,卖方将对超过约定订货量的部分商品收取额外费用(或取消价格折扣);另一方面,从买方角度,由于下游不稳定的市场需求,买方希望没有约定订货量的约束,而是根据实际的市场需求在当期确定订货量。双方折中的结果是,买方必须许诺一个基本的订货量,但拥有一定次数和范围的改变订货量的机会。针对这一问题,建立了一种带柔性的批量订货契约模型,并通过仿真验证了模型能够节约订货成本,实现供应链中风险的重新分配。     

Coordinating Sales and Raw Material Discounts in a Global Supply Chain

In this paper, the supplier of a key component to a global manufacturer offers a one‐time price discount; we study the firm's optimal response to the discount under two different strategies. In the first strategy, the firm does not pass along the discount to its customers (sales subsidiaries); the firm simply coordinates purchasing and production among the different factories to take advantage of this one‐time price discount. In the second strategy, the firm offers price discounts for its most profitable products in different sales subsidiaries to increase their demand. We carried out experiments for the two strategies based on a mathematical programming model, built around Toshiba's global notebook supply chain. Model constraints include, among others, material constraints, bill‐of‐materials, capacity and transportation constraints, minimum lot size constraints, and a constraint on minimum fill rate (service level constraint). Unlike most models of this type in the literature, which define variables in terms of single arc flows, we employ path variables, which allow for direct identification and manipulation of profitable and non‐profitable products.     

基于不对称需求信息的供应链最小订购量决策

在由一个供应商和一个零售商组成的两级分散供应链中,供应商通过制定最小订购量取得规模效应,保障自身利益。当零售商和供应商之间存在需求信息不对称时,即零售商掌握需求信息而供应商仅知道需求信息中价格敏感因子的分布,如何进行最小订购量决策成为供应商面临的一个重要问题。针对这一问题,从营销视角构建了基于Stackelberg博弈的利润最大化模型。假设供应商知道需求的价格敏感因子服从正态分布,通过严密的数学推导确定了模型中的最优最小订购量。将提出的最优最小订购量决策方法应用于云存储的销售供应链中,确定了云存储供应商销售的最优最小存储容量,阐释了方法的合理性与有效性。通过实验研究发现,最小订购量的设置提升了供应商的利润。所提方法对于考虑最小订购量的供应链协调研究具有积极的推动作用。     

考虑汇率变化和运输成本分担的跨国供应链数量折扣契约

建立了跨国供应链的数量折扣模型,模型中考虑了汇率、国际运输成本分担比例等因素。通过分析得到了协调跨国供应链的数量折扣契约,在该契约下供应商、销售商以及供应链系统的利润都得到改善。最后通过实例验证了模型和有关命题,分析了汇率变化对契约参数及供应链各方、供应链系统利润的影响,结果表明:①汇率变化下,数量折扣率和国际运输成本分担比例具有稳定性,变化较大的契约参数是订购量;②即使实现了供应链协调,随着人民币对美元的升值,不仅使中国供应商的利润下降,也使美国销售商以及供应链系统的利润下降。根据实例计算结果与分析,从供应链管理的角度认为,应该保持人民币对美元汇率的稳定。     

电子商务环境下双渠道供应链协调的补偿策略研究

构建了电子商务环境下由一个制造商与一个零售商组成的双渠道供应链模型,分析、比较了集中式决策与分散式决策下双渠道供应链的最优价格,从电子渠道与传统渠道合作的角度出发,研究了双渠道供应链协调的补偿策略,论证了这种补偿策略能够实现双渠道供应链协调,且在一定范围内可以保证双渠道供应链成员的双赢.最后通过算例分析,进一步检验了所设计的补偿策略对双渠道供应链协调的有效性.     

Controversial Role of GPOs in Healthcare‐Product Supply Chains

This paper examines the controversial role that Group Purchasing Organizations (GPOs) play in the supply chains for healthcare products. Among the controversies, perhaps the most fundamental one is whether or not GPOs reduce purchasing costs for their members. However, the fiercest controversy is around the “contract administration fees (CAFs)” that GPOs charge to manufacturers. We examine these and other controversies using a Hotelling duopoly model. Among our conclusions: GPOs increase competition between manufacturers and lower prices for healthcare providers. However, GPOs reduce manufacturers' incentives to introduce innovations to existing products. We also demonstrate that the existence of lower off‐contract prices is not, per se, evidence of anticompetitive behavior on the part of GPOs. Indeed, we demonstrate that, under certain circumstances, the presence of a GPO lowers off‐contract prices. We also examine the consequences of eliminating the “safe harbor” provisions that permit healthcare GPOs to charge CAFs to manufacturers, and conclude that it would not affect any party's profits or costs.     

基于价格折扣与交易信用组合契约的供应链协调策略

基于由单一制造商与单一零售商构成的两级供应链,文章通过设计价格折扣(即制造商给予消费者价格折扣)与交易信用(即零售商向制造商提前付款)组合契约,研究了分散化供应链中的库存控制与协作管理问题,得到了供应链各方成员最优的联合协调策略.研究表明,在市场需求缺乏价格弹性或者弹性系数不够大的情况下,制造商不愿意向消费者提供任何的价格折扣.此时,制造商需要向零售商提供交易信用(即允许零售商延期付款)激励以协调零售商的订货策略;而在需求比较富有价格弹性或者说需求对零售价格比较敏感的时候,制造商与零售商采用价格折扣与交易信用组合契约,能够实现整条供应链的协调以及双方利润的帕累托改善.最后,通过一个数值仿真验证了主要的结论.     

Coordinated Contract Decisions in a Make‐to‐Order Manufacturing Supply Chain: A Stochastic Programming Approach

One of the important objectives of supply chain S&OP (Sales and Operations Planning) is the profitable alignment of customer demand with supply chain capabilities through the coordinated planning of sales, production, distribution, and procurement. In the make‐to‐order manufacturing context considered in this paper, sales plans cover both contract and spot sales, and procurement plans require the selection of supplier contracts. S&OP decisions also involve the allocation of capacity to support sales plans. This article studies the coordinated contract selection and capacity allocation problem, in a three‐tier manufacturing supply chain, with the objective to maximize the manufacturer's profitability. Using a modeling approach based on stochastic programming with recourse, we show how these S&OP decisions can be made taking into account economic, market, supply, and system uncertainties. The research is based on a real business case in the Oriented Strand Board (OSB) industry. The computational results show that the proposed approach provides realistic and robust solutions. For the case considered, the planning method elaborated yields significant performance improvements over the solutions obtained from the mixed integer programming model previously suggested for S&OP.     

Coordination of Supply Chains with Risk‐Averse Agents

The extant supply chain management literature has not addressed the issue of coordination in supply chains involving risk‐averse agents. We take up this issue and begin with defining a coordinating contract as one that results in a Pareto‐optimal solution acceptable to each agent. Our definition generalizes the standard one in the risk‐neutral case. We then develop coordinating contracts in three specific cases: (i) the supplier is risk neutral and the retailer maximizes his expected profit subject to a downside risk constraint; (ii) the supplier and the retailer each maximizes his own mean‐variance trade‐off; and (iii) the supplier and the retailer each maximizes his own expected utility. Moreover, in case (iii), we show that our contract yields the Nash Bargaining solution. In each case, we show how we can find the set of Pareto‐optimal solutions, and then design a contract to achieve the solutions. We also exhibit a case in which we obtain Pareto‐optimal sharing rules explicitly, and outline a procedure to obtain Pareto‐optimal solutions.     

零售商退出风险的供应链冲击与协调契约分析

零售商退出会导致供应链合作关系的终止,冲击供应链合作运营的基础,供应链企业需要合作应对吗?本文以数量折扣契约下的协调供应链为研究框架,研究存在零售商退出风险时传统数量折扣契约的供应链运作,并构建改进契约下的供应链协调模型。通过理论推演与仿真分析发现,零售商退出风险对供应链运作可能造成巨大的冲击,同时也惊讶地发现,虽然数量折扣契约在冲击下不能协调运作,但运作效率非常高。建议契约调整成本不高的供应链可选择我们改进后的协调数量折扣契约。     

基于ARMA（1，1）需求的供应链历史订单量信息价值的分析

牛鞭效应和供应链成本是目前供应链管理中值得关注的两个问题,本文通过分析ARMA(1,1)需求条件下的供应链历史订单量信息对牛鞭效应和制造商平均成本的影响,得出历史订单量信息的充分利用可以减小牛鞭效应、降低供应链成本.本文研究表明,如果充分利用历史订单量信息,则需求信息共享对供应链的贡献就不会有目前所认为的那么显著,其中的部分贡献可以由历史订单量信息来承担.因此,历史订单量信息的充分利用可以在一定程度上减少为寻求供应链需求信息共享而付出的投资费用.     

Complexity as a Contract Design Factor: A Human‐to‐Human Experimental Study

Despite being theoretically suboptimal, simpler contracts (such as price‐only contracts and quantity discount contracts with limited number of price blocks) are commonly preferred in practice. Thus, exploring the tension between theory and practice regarding complexity and performance in contract design is especially relevant. Using human subject experiments, Kalkancı et al. (2011) showed that such simpler contracts perform effectively for a supplier interacting with a computerized buyer under asymmetric demand information. We use a similar set of experiments with the modification that a human supplier interacts with a human buyer. We show that human interactions strengthen the supplier's preference for simpler contracts. We find that suppliers have fairness concerns even when they interact with computerized buyers. These fairness concerns tend to be even stronger when suppliers interact with human buyers, particularly when the complexity of the contract is low. We also find that suppliers are more prone to random decision errors (i.e., bounded rationality) when interacting with human buyers. In the absence of social preferences, Kalkancı et al. identified reinforcement and bounded rationality as key biases that impact suppliers' decisions. In human‐to‐human experiments, we find evidence for social preference effects. However, these effects may be secondary to bounded rationality.     

The Impact of Information Sharing and Advance Order Information on a Supply Chain with Balanced Ordering

This paper considers a supply chain with one supplier and multiple retailers that face exogenous heterogeneous end‐customer demands, where all parties utilize base‐stock policies. Each retailer is restricted to order once in every order cycle and their orders are replenished in a balanced manner within the cycle. Our study investigates the impact of information sharing and advance order information (AOI) on the supply chain. We find that the supplier benefits from the two mechanisms via two important factors, the information about observed end‐customer demands and the decision on re‐establishing the replenishment sequence. We derive the supplier's optimal sequence for stochastically comparable end‐customer demands with AOI and propose a sequencing rule for the setting with information sharing. Our numerical study examines the cost impacts of two proposed mechanisms on the entire supply chain.     

Joint Mail‐In Rebate Decisions in Supply Chains Under Demand Uncertainty

We study the joint decisions of offering mail‐in rebates (MIRs) in a single‐manufacturer–single‐retailer supply chain using a game theoretic framework. Either party can offer an MIR to the end consumer if it is in his best interest. The consumer demand is stochastic and depends on the product price and the amount of MIRs. When the retail price is exogenous, we show the existence of a unique Nash equilibrium under both additive and multiplicative demand functions and characterize it completely. We show that any of the following four scenarios can be the equilibrium: both parties offer MIR, only one party offers MIR, none offers MIR. When the retail price is a decision variable for the retailer and the rebate redemption rate increases with the amount of MIR, we once again prove the existence of a unique Nash equilibrium where both the retailer and the manufacturer offer MIRs. Using a numerical study, we show that the average post‐purchase price of the product is higher not only than the perceived pre‐purchase price but also than the newsvendor optimal price without an MIR. This implies that an MIR makes a product look cheaper while the consumers actually pay more on average.     

Optimization and Coordination of Fresh Product Supply Chains with Freshness‐Keeping Effort

We consider a supply chain in which a distributor procures from a producer a quantity of a fresh product, which has to undergo a long‐distance transportation to reach the target market. During the transportation process, the distributor has to make an appropriate effort to preserve the freshness of the product, and his success in this respect impacts on both the quality and quantity of the product delivered to the market. The distributor has to determine his order quantity, level of freshness‐keeping effort, and selling price, by taking into account the wholesale price of the producer, the cost of the freshness‐keeping effort, the likely spoilage of the product during transportation, and the possible demand for the product in the market. The producer, on the other hand, has to determine the wholesale price based on its effect on the order quantity of the distributor. We develop a model to study this problem, and characterize each party's optimal decisions in both decentralized and centralized systems. We further develop an incentive scheme to facilitate coordination between the two parties. Computational results are reported to show the effects of freshness‐keeping efforts.     

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.