Impact of equity and equality on stability and collusion in a decentralized network

We consider a firm that procures a product from a regular supplier whose production is subject to both supply disruption and random yield risks and a backup supplier whose production capacity requires reservation in advance. Under both deterministic and stochastic demand, we study the impact of the two types of supply risks on the firm’s optimal procurement decisions and the importance of correctly identifying the source of supply risks. We find that if the overall supply risk is unchanged but its main source shifts from random yield to supply disruption, the firm should order more from the regular supplier and reserve less capacity from the backup supplier. Ignoring the existence of supply disruption leads to under-utilization of the regular supplier and over-utilization of the backup supplier. Moreover, we examine the option value of the reserved capacity that is affected by the uncertainty of customer demand. We find that the option value increases/decreases in demand uncertainty if the reservation capacity is exercised after/before demand is realized.     

Impact of product pricing and timing of investment decisions on supply chain co-opetition

In supply chain co-opetition, firms simultaneously compete and co-operate in order to maximize their profits. We consider the nature of co-opetition between two firms: The product supplier invests in the technology to improve quality, and the purchasing firm (buyer) invests in selling effort to develop the market for the product before uncertainty in demand is resolved. We consider three different decision making structures and discuss the optimal configuration from each firm’s perspective. In case 1, the supplier invests in product quality and sets the wholesale price for the product. The buyer then exerts selling effort to develop the market and following demand potential realization, sets the resale price. In case 2, the supplier invests in product quality followed by the buyer’s investment in selling effort. Then, after demand potential is observed, the supplier sets the wholesale price and the buyer sets the resale price. Finally, in case 3, both firms simultaneously invest in product quality and selling effort, respectively. Subsequently, observing the demand potential, the supplier sets the wholesale price and the buyer sets the resale price. We compare all configuration options from both the perspective of the supplier and the buyer, and show that the level of investment by the firms depends on the nature of competition between them and the level of uncertainty in demand. Our analysis reveals that although configuration 1 results in the highest profits for the integrated channel, there is no clear dominating preference on system configuration from the perspective of both parties. The incentives of the co-opetition partners and the investment levels are mainly governed by the cost structure and the level of uncertainty in demand. We examine and discuss the relation between system parameters and the incentives in desiging the supply contract structure.     

Inventory systems with stochastic demand and supply: Properties and approximations

We model a retailer whose supplier is subject to complete supply disruptions. We combine discrete-event uncertainty (disruptions) and continuous sources of uncertainty (stochastic demand or supply yield), which have different impacts on optimal inventory settings. This prevents optimal solutions from being found in closed form. We develop a closed-form approximate solution by focusing on a single stochastic period of demand or yield. We show how the familiar newsboy fractile is a critical trade-off in these systems, since the optimal base-stock policies balance inventory holding costs with the risk of shortage costs generated by a disruption.     

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.     

The effect of testing equipment shift on optimal decisions in a repetitive testing process

Repetitive testing process is commonly used in the final testing stage of semiconductor manufacturing to ensure high outgoing product quality and to reduce testing errors. The decision on testing lot size and the number of testing repetitions ultimately determines the effectiveness of the testing process. Setting the retest rule is often difficult in practice due to uncertainties in the incoming product quality and testing equipment condition. In this paper, we study a repetitive testing process where the testing equipment may shift randomly to an inferior state. We develop a cost model that helps us to make optimal decisions on retesting rule. Through numerical analysis, we provide practical insights about the effects of testing equipment shift rate, testing errors, and different costs such as cost of testing and cost of rejecting conforming products on the optimal decision and the system performance. We find that significant penalty may result if the potential testing equipment shift is ignored.     

Ordering and pricing decisions in a two-echelon supply chain with asymmetric demand information

This article examines coordinated decisions in a decentralized supply chain that consists of one supplier and one retailer, and faces random demand of a single product with a short life cycle. We consider a setting where the retailer has accurate demand information while the supplier does not. Such a problem with asymmetric demand information can be viewed as an extension of the newsboy problem in which both the supplier and the retailer possess the same demand information. Combining the mechanism of sharing demand information and that of quantity discount and return policy enables us to develop three coordinated models in contrast with the basic and uncoordinated model. We are able to show the ordinal relationship among the retailer’s optimal order quantities in these four models under a general form of random demand, and compare the supply chain profits and conduct sensitivity analysis analytically in four models under uniform random demand. We also provide numerical results under normal random demand that bear a resemblance to those under uniform random demand.     

Joint pricing and inventory replenishment decisions with returns and expediting

We study a single-item periodic-review model for the joint pricing and inventory replenishment problem with returns and expediting. Demand in consecutive periods are independent random variables and their distributions are price sensitive. At the end of each period, after the demand is realized, a buyer can return excess stocks to a supplier. Or, if there are stockouts, the buyer can place an expediting order at the supplier to reduce the amount of shortage. Unfilled demands are fully backlogged. We characterize the optimal dynamic policy that determines the pricing, inventory replenishment, and adjustment decisions in each period so that the total expected discounted profit is maximized. For a very general stochastic demand function, we can show that the optimal replenishment policy is a modified base-stock policy, the optimal pricing policy is a modified base-stock-list-price policy, and the optimal policy for inventory adjustment follows a dual-threshold policy. We further study the operational effect of returns and expediting. Analytical and numerical results demonstrate that returns and expediting lead to a significant profit increase in a number of situations, including limited supply capacity, sufficient flexibility of the expediting order, high demand uncertainty, and a price-sensitive market.     

Component ordering strategies in assembly systems with uncertain capacity and random yield

Sourcing components in a complex global supplier network may lead to a high degree of supply uncertainty. Events, such as unexpected production defects or insufficient supplier capacity, can cause unexpected shortages of required components and halt the assembly of final products. Accordingly, the assembly enterprises must effectively manage various supply uncertainties in their component ordering decisions to avoid such component shortfalls. These issues have guided this research to investigate the optimal ordering strategies of an assembler facing the following two types of supply uncertainty: the uncertain production capacity of a standard component (component 1) and the random production yield of a core component (component 2). The assembler makes the component ordering decisions before these supply uncertainties are realized. We characterize the optimal ordering decision and find that the assembler should order components 1 and 2 according to a fixed ratio, which only depends on the random yield of component 2 and the production cost of component 1, but not on the uncertain capacity of component 1. A case study is presented to further explore the intertwined effects of these two uncertainties in an assembly system. Finally, the model is extended to consider a secondary option of buying additional component 1 s after observing some or all of the supply uncertainties, and this secondary option endows the firm with different capabilities in counteracting the supply uncertainties.     

Quantifying supply chain ineffectiveness under uncoordinated pricing decisions

We analyze a multiple-stage supply chain model of a seasonal product with pricing decisions. We develop closed-form expressions for the optimal expected profits of different stages. The results enable us to quantify the loss of supply chain profits if uncoordinated pricing decisions are made by supply chain agents.     

竞争环境下随机产出供应商的融资策略研究

考虑由一个制造商和两个竞争性供应商组成的供应链系统,其中一个供应商存在资金短缺的问题,自有资金不足以完成正常生产任务,需要通过融资获得资金完成生产。针对供应链内部和外部两种融资模式,分别构建了供应链成员的收益模型,计算了不同融资方式下的决策结果,并在此基础上对两种融资模式进行了比较分析。结果表明,资金短缺的供应商生产不确定性较低时,供应链成员所能获得的利润较高,并且内部融资下资金短缺的供应商生产积极性高于外部融资。同时发现,对融资方式偏好的不一致将导致制造商利润损失,此时制造商可以采取一定的激励措施引导供应商选择合适的融资方式以提高整体收益。     

存货质押融资模式下的供应链协调

针对供应商、零售商和银行组成的供应链金融系统,研究了存货质押融资模式下的供应链协调。零售商作为中小企业,资金有限,需要向银行申请贷款,然而零售商信用较低难以获得融资。供应商作为供应链的核心企业,采用含有回购价格和回购比例的回购契约为零售商提供担保,使得零售商融资得以实现。分析了不确定需求下供应链金融系统,供应链以及零售商的最优决策,给出了融资情况下供应链协调的条件,指出了在供应链协调情况下批发价格和回购策略对供应链收益分配的影响,说明了回购的作用:一方面使零售商易于获得银行融资,另一方面使供应链协调得以实现,指出了质押率、贷款利率和零售商自有资金等参数对最优决策的影响。数值算例验证了理论分析结果。     

资金约束下三层供应链的融资和定价决策研究

实际生活中,供应链的资金管理是极其复杂多变的,现有学者关于供应链定价问题研究多以简单的二层供应链为基础,脱离了实际可用性。本文将二层供应链拓展成三层供应链,以单一供应商、单一生产商和单一零售商组成的三层供应链为研究对象,在市场风险中性的假设条件下,探究在供应商拥有不同初始资金约束情形下的供应链融资与最优定价决策,弥补了原先模型使用范围的狭隘性。通过模型的建立与数值分析显示,当供应商存在资金约束时,供应链融资能够使整条供应链上参与者的最优利润增加,从而创造价值。     

Random yield supply chain with a yield dependent secondary market

This paper considers a simple supply chain with one supplier and one retailer where the supplier’s production is subject to random yield and the retailer faces uncertain demand. There exists a secondary market for acquiring or disposing products by the supplier. We study both the centralized and decentralized systems. In the decentralized system, a no risk sharing contract and a risk sharing minimum commitment contract are analyzed. The supply chain with the risk sharing contract is further analyzed with a constant secondary market price and a yield dependent secondary market price. We present both the supplier’s and the retailer’s optimal strategies and provide insights for managers when making decisions under random yield risk and demand uncertainty. We find that the secondary market generally has a positive impact on supply chain performance and the actual effect of random yield risk on the supply chain performance depends on cost parameters and supply chain contract settings. Under certain conditions, reducing yield randomness may weaken the double marginalization effect and improve the chain performance. From the numerical study, we also show that there exists an optimal commitment level for the supply chain.     

Optimizing Supply Shortage Decisions in Base Stock Distribution Operations

This paper addresses policies and agreements between suppliers and customers for handling supply shortages in base-stock systems under uncertain demand. We investigate the impacts that backlogging and expediting decisions have on inventory and transportation costs in these systems and develop a model for deciding whether a supplier should completely backlog, completely expedite, or employ some combination of backlogging and expediting shortages. Our results indicate that practical cases exist where some combination of both expediting and backlogging supply shortages outperforms either completely expediting or backlogging all shortages. Including transportation costs in our model provides incentive to employ `hybrid' policies that partially expedite and partially backlog excess demands within a given period. Our model demonstrates how inventory policy decisions directly impact transportation costs and provides a heuristic approach for jointly minimizing expected inventory and transportation costs.     

Supply chain design under uncertainty using sample average approximation and dual decomposition

We present a supply chain design problem modeled as a sequence of splitting and combining processes. We formulate the problem as a two-stage stochastic program. The first-stage decisions are strategic location decisions, whereas the second stage consists of operational decisions. The objective is to minimize the sum of investment costs and expected costs of operating the supply chain. In particular the model emphasizes the importance of operational flexibility when making strategic decisions. For that reason short-term uncertainty is considered as well as long-term uncertainty. The real-world case used to illustrate the model is from the Norwegian meat industry. We solve the problem by sample average approximation in combination with dual decomposition. Computational results are presented for different sample sizes and different levels of data aggregation in the second stage.     

Mitigating supply risk: an approach with quantity flexibility procurement

This paper considers a buyer that procures from its major supplier whose production is subject to random yield risk. To mitigate supply risk, the buyer can procure from another reliable supplier who provides quantity flexibility (QF) contract. Under both deterministic and stochastic demand, we study the buyer’s optimal procurement decisions. We analyze the structural properties of optimal solutions and identify the conditions under which the quantity flexibility procurement policy should be used. We also examine the effect of supply risk, flexibility, wholesale price and demand risk on the procurement decisions. We find that the higher supply risk and demand risk reduce the buyer’s profit but have different impact on the buyer’s order policy. For the QF supplier, it may not obtain more orders by providing larger flexibility to the buyer, on the contrary, doing this may benefit the risky supplier. For the QF supplier or risky supplier, given its competitor’s wholesale price, it can increase its order share by lower wholesale price.     

供需不确定条件下考虑双边努力的供应链组合契约设计

本文研究供需同时不确定条件下考虑双边努力的供应链契约设计问题,在一个供应商和一个零售商组成的二级供应链系统中,供应商的努力影响产量的不确定性,零售商的努力影响市场需求的不确定性。首先,利用Stackerberg主从博弈模型计算了分散决策时零售商、供应商的最优期望利润,并将计算结果与集中决策时供应链整体的最优期望利润进行对比。由于双重边际效应的存在,分散决策时供应链的最优期望利润小于集中决策时供应链的最优期望利润。基于此,本文设计了回购和成本分担组合契约来协调该供应链,计算了回购价格和成本分担系数的表达式,得到了回购和成本分担契约下供应商和零售商的最优期望利润。结果表明,在特定条件下,该组合契约不仅可以协调供应链,还可以实现供应链利润的任意分配。最后,通过数值计算,分析了供需双方的决策变量和期望利润随契约参数的变化情况。     

基于双边匹配-动态博弈的碳减排技术投资决策

在Cap-and-Trade规制下,本文通过匹配-博弈机制研究双寡头制造商(寡头)碳减排技术投资决策问题,考虑了碳交易(CET)过程。从纵向角度,构建寡头与碳减排技术供应商(供应商)的双边匹配模型,研究寡头最佳碳减排技术选择、供应商最佳投资者选择问题;从横向角度,以产量为决策变量,以供应商技术研发人员的努力程度为辅助变量,构建双寡头Stackelberg动态博弈模型,以确定最优产量和碳减排技术投资决策,有效实现碳减排。最后,通过数值模拟实验加以论证。研究发现,第一,寡头-供应商匹配对的整体期望效用与CET价格存在正相关关系;第二,寡头环境绩效对自身技术应用效率较敏感,而对对手技术应用效率不敏感;第三,CET实施与否会直接影响寡头-供应商匹配对效用最大化目标的实现。     

Fuzzy-valued linguistic soft set theory and multi-attribute decision-making application

In this work, we propose the theory of fuzzy linguistic soft set (FLSS) to represent the uncertainty and multi-angle of view when decision makers evaluate an object during decision-making. FLSS integrates fuzzy set theory, linguistic variable and soft set theory. It allows decision makers to utilize linguistic variables to evaluate an object and utilize fuzzy values to describe the corresponding grade of their support of their decisions. Meanwhile, because of the flexibility of soft set, decision makers can use more than one pair of fuzzy-linguistic evaluations to express their opinions from multiple perspectives directly, if necessary. Therefore, it is more flexible and practical than traditional fuzzy set or 2-dimension uncertainty linguistic variable. We also develop a generalized weighted aggregation operator for FLSSs to solve corresponding decision-making issues. Finally, we give a numerical example to verify the practicality and effectiveness of the proposed method.     

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。