Risk Uncertainty and Supply Chain Decisions: A Real Options Perspective

Supply chain risk uncertainty can create severe repercussions, thus it is not surprising that research interest in supply chain risk has been growing. While extant inquiry is informative, there is a lack of investigations that center on supply chain investment decisions when facing high levels of risk uncertainty. Given the potential dollar value involved in these decisions, an understanding of how these supply chain decisions are made is of significant theoretical and practical importance. Real options theory, with its focus on decision making under conditions of uncertainty, is an appealing theoretical lens for this endeavor. In essence, real options theory asserts that managerial decisions center on creating and then exercising or not exercising certain opportunities. To date, theorizing about and investigations of real options have used firms as their focus. Not yet examined are real options within supply chains that cross firm boundaries and drive much of the competitive activity in the modern economy. Accordingly, we extend real options theory to the supply chain context by examining how different types of options are approached relative to supply chain project investments. Specifically, we theorize how the options will be related to perceived value under conditions of high supply chain risk uncertainty. Overall, our investigation builds knowledge by extending real options theory to the supply chain context and by providing evidence suggesting some options operate differently in supply chains than they do in firms.     

需求不确定条件下的制造商订单分配模型

制造商的订单分配作为供应链模型微观层面的重要组成部分,对提升整个供应链效率有很大影响,但需求层面的不确定因素加大了订单分配的难度。以按比例分配为原则,讨论在需求不确定条件下完全信息与不完全信息两类多供应商-单制造商的订单分配模型。重点研究完全信息条件下各方的分散决策和集中决策,由于后者能避免各参与方对其他决策方的边际影响,所以能够实现供应链总利润的最大化;其次又将不完全信息引入模型,讨论制造商如何通过折算因子结合已有信息对供应商的私人信息进行估计,进而做出决策。最后以需求服从正态分布为例对两类模型进行验证。     

Traceability and Risk Analysis Strategies for Addressing Counterfeit Electronics in Supply Chains for Complex Systems

Within the microelectronics industry, there is a growing concern regarding the introduction of counterfeit electronic parts into the supply chain. Even though this problem is widespread, there have been limited attempts to implement risk‐based approaches for testing and supply chain management. Supply chain risk management tends to focus on the highly visible disruptions of the supply chain instead of the covert entrance of counterfeits; thus counterfeit risk is difficult to mitigate. This article provides an overview of the complexities of the electronics supply chain, and highlights some gaps in risk assessment practices. In particular, this article calls for enhanced traceability capabilities to track and trace parts at risk through various stages of the supply chain. Placing the focus on risk‐informed decision making through the following strategies is needed, including prioritization of high‐risk parts, moving beyond certificates of conformance, incentivizing best supply chain management practices, adoption of industry standards, and design and management for supply chain resilience.     

Decision Making and Cognition in Multi‐Echelon Supply Chains: An Experimental Study

Supply chain performance often depends on the individual decisions of channel members. Even when individuals have access to relevant information, order variation tends to increase when moving up the supply chain, a phenomenon known as the bullwhip effect. While prior research has investigated several structural/environmental factors which can mitigate the bullwhip effect, the underlying behavioral factors contributing to it are an open question. Using a production and distribution decision‐making simulation representing a four‐stage serial supply chain, we find that the cognitive profile of decision makers contributes to the bullwhip effect. We found that the specific decision tendency to underweight the supply line is linked to an individual's level of cognitive reflection. Furthermore, performance differs for entire supply chains and for specific echelons, and holds under standard mitigation efforts. The findings have implications for supply chain design, education, and industry.     

Supply chain relationship quality and its impact on firm performance

Abstract

This paper examines the impact of supply chain relationship quality (SCRQ) on firm performance (FP) through the mediators of supply chain management processes (SCMP) and supply chain performance (SCP). In the literature, these linkages have been examined separately; in contrast, this study takes a holistic perspective on the antecedents of FP. The model was tested using survey data from manufacturing companies. Variance-based structural equation modelling revealed that both SCMP and SCP lead to FP, unlike SCRQ. On the other hand, SCRQ affects SCMP. Drawing on the resource-based view, consistency in SCRQ can lead to not only efficient and effective supply chain management but also improvements in FP and SCP. This research has practical implications, providing supply chain decision makers with insights on enhancing FP. Supply chain decision makers will be able to benefit from the findings of our study by improving supply chain relationships with supply chain members and ensuring FP. This research also highlights how effective management of SCRQ, SCMP and SCP can provide better FP and a competitive advantage.     

Information sharing in supply chains

Supply chain is defined as a system of suppliers, manufacturers, distributors, retailers and customers where material, financial and information flows connect participants in both directions. Most supply chains are composed of independent agents with individual preferences. It is expected that no single agent has the power to optimise the supply chain. Supply chain management is now seen as a governing element in strategy and as an effective way of creating value for customers. The so-called bullwhip effect, describing growing variation upstream in a supply chain, is probably the most famous demonstration that decentralised decision making can lead to poor supply chain performance. Information asymmetry is one of the most powerful sources of the bullwhip effect. Information sharing of customer demand has an impact on the bullwhip effect. Information technology has lead to centralised information, shorter lead times and smaller batch sizes. The analysis of causes of the bullwhip effect has lead to suggestions for reducing the bullwhip effect in supply chains by strategic partnership. Supply chain partnership leads to increased information flows, reduced uncertainty, and a more profitable supply chain. The cooperation is based on contacts and formal agreements. Information exchange is very important issue for coordinating actions of units. New business practices and information technology make the coordination even closer. Information sharing and strategic partnerships of units can be modelled by different network structures.     

风险规避型供应链的收益共享机制研究

探讨了由风险规避型零售商与风险规避型供应商组成的两级供应链协作激励问题.首先研究了Stackelberg主从对策模型下风险规避型零售商与风险规避型供应商的决策行为,并分析了双方的风险规避系数对双方决策行为的影响.然后,研究了垂直一体化模型下风险规避型供应链的决策行为,同样分析了双方风险规避系数对供应链决策行为的影响程度.最后,提出采用收益共享契约机制来协调该供应链.并通过数值实验进一步分析供应商与零售商的风险规避系数对双方的决策行为及收益共享系数的影响程度.     

The Severity of Supply Chain Disruptions: Design Characteristics and Mitigation Capabilities

Supply chain disruptions and the associated operational and financial risks represent the most pressing concern facing firms that compete in today's global marketplace. Extant research has not only confirmed the costly nature of supply chain disruptions but has also contributed relevant insights on such related issues as supply chain risks, vulnerability, resilience, and continuity. In this conceptual note, we focus on a relatively unexplored issue, asking and answering the question of how and why one supply chain disruption would be more severe than another. In doing so, we argue, de facto, that supply chain disruptions are unavoidable and, as a consequence, that all supply chains are inherently risky. Employing a multiple‐method, multiple‐source empirical research design, we derive novel insights, presented as six propositions that relate the severity of supply chain disruptions (i) to the three supply chain design characteristics of density, complexity, and node criticality and (ii) to the two supply chain mitigation capabilities of recovery and warning. These findings not only augment existing knowledge related to supply chain risk, vulnerability, resilience, and business continuity planning but also call into question the wisdom of pursuing such practices as supply base reduction, global sourcing, and sourcing from supply clusters.     

A numerical analysis of supply chain performance under split decision rights

We examine periodic review supply chain models where order quantity and shipping frequency are both decision variables and decision-making rights are split between supply chain agents. We address two general questions: (1) when does decentralized decision making result in the greatest loss in supply chain performance; and (2) what effect does the distribution of channel power have on performance loss. We characterize optimal policies where possible in each scenario and we use numerical analysis to generate insights. We find that performance losses from decentralized control are somewhat limited in our results due to risk pooling and that the magnitude of performance loss is strongly influenced by the relative holding and penalty costs, but somewhat invariant to demand uncertainty. Furthermore, we find that concentrating channel power with the supplier can lead to supply chain profits that are very close to a centralized scenario, but also results in lower customer service levels.     

基于决策者风险规避特性的供应链需求信息共享价值分析

在随机需求条件下,利用条件风险估值(conditional value-at-risk,CVaR)的风险度量准则建立了供应链的需求信息共享决策模型,着重分析了零售商的风险规避程度以及市场需求的不确定性信息对供应链各决策者以及供应链整体信息共享价值的影响。研究结果表明,需求信息共享价值与零售商的风险规避程度、市场不确定性大小以及市场不确定信息所预测的市场需求变化情况有关。数值分析结果表明,零售商越害怕市场的不确定性风险,需求信息共享越有利于提升分散供应链的运作效率;但当市场信息反映出未来的市场需求是消极且零售商接近风险中性时,供应链的需求信息共享价值反而小于零,此时没有进行信息共享的必要。     

基于期权合约的供应链协同决策研究

本文在市场需求和价格不稳定的双重背景下,研究以风险规避为目的的供应商如何在供应链管理中运用期权合约实现利润最大化的途径问题。供应商通过在二级供应链中引入实物期权,在购买方需求不确定时可以将其引致的风险转移向供应方,而供应方的风险通过来自期权合约的额外收益在最大程度上被平衡。本文在分析考虑期权因素的决策模型中,研究市场需求以随机分布状态变化时,构建具有期权合约的最优利润最大化模型问题。数值算例验证了期权合约策略模型的可行性。本研究在一定程度上完善了供应链中期权合约的风险规避模型,为供应链企业风险管理的决策依据提供了有用的实践参考价值。     

Decision knowledge sharing: flexible supply chains in KM context

Supply chain excellence has a real impact on business strategy. Building supply chains as flexible systems represents one of the most exciting opportunities to create value and one of the most challenging tasks for the policy makers. It requires integrated decision making amongst autonomous chain partners with effective decision knowledge sharing between them. The key to success lies in knowing which decision has more impact on the overall performance and this can be achieved by appropriate knowledge sharing. In this context, knowledge management (KM) can be used as an effective approach to achieve knowledge sharing and decision synchronisation in supply chains. Flexible supply chains (FSC_s) are more complex and involve multiple autonomous players with varying technical cultures (affects knowledge mindsets), managerial background (affects decision knowledge) and supply chain management (SCM) exposures (affects knowledge sharing attitudes). Thus there is a need to develop demo models that can encourage chain managers towards collaborative knowledge sharing in the supply chains. This paper presents the application of one such model based on decision knowledge sharing (DKS) for improved supply chain management. A simulation model of a flexible supply chain based on DKS framework is developed for demo purposes. The key results are highlighted along with industry implications. The cost based performance of DKS at different levels of flexibility is studied. Thus a careful analysis of the chain with a focus on collaborative decisions is useful to ensure success. This paper addresses this interesting and challenging domain.     

考虑风险规避的资金约束供应链最优信用契约设计

本文针对零售商的资金约束问题,研究了风险规避的供应商如何通过设计信用契约影响零售商的融资结构。构建了包含供应商、零售商以及银行在内的供应链融资模型,给出了供应商的最优信用契约决策、零售商的最优库存决策以及银行的最优利率决策。进一步分析了供应商的风险规避程度对最优信用契约决策的影响。研究表明：当供应商的风险规避程度低于某个临界值时,供应商偏好提供全额信用,从而零售商的融资结构为单一的交易信用融资;而当供应商的风险规避程度高于该临界值时,供应商偏好提供部分信用,从而零售商的融资结构为组合融资。最后,通过数值算例验证了本文的结论。本研究一定程度上丰富了现有供应链金融的理论研究,为供应链核心企业与银行的决策提供了依据与参考。     

Modeling Supply Chain Dynamics: A Multiagent Approach*

A global economy and increase in customer expectations in terms of cost and services have put a premium on effective supply chain reengineering. It is essential to perform risk-benefit analysis of reengineering alternatives before making a final decision. Simulation provides an effective pragmatic approach to detailed analysis and evaluation of supply chain design and management alternatives. However, the utility of this methodology is hampered by the time and effort required to develop models with sufficient fidelity to the actual supply chain of interest. In this paper, we describe a supply chain modeling framework designed to overcome this difficulty. Using our approach, supply chain models are composed from software components that represent types of supply chain agents (e.g., retailers, manufacturers, transporters), their constituent control elements (e.g., inventory policy), and their interaction protocols (e.g., message types). The underlying library of supply chain modeling components has been derived from analysis of several different supply chains. It provides a reusable base of domain-specific primitives that enables rapid development of customized decision support tools.     

产需不确定下基于零售商风险规避的三级供应链组合契约模型

针对产需不确定下单一供应商、制造商和风险规避的零售商组成的三级供应链系统,建立了分散和集中情况下的最优决策模型。通过设计风险共担和GL组合契约实现了三级供应链的协调。讨论了风险规避零售商的最优订购决策,分析了风险规避对供应链期望效益的影响。比较了风险规避和风险中性两种情况下零售商的最优决策。探讨了组合契约的协调问题及契约参数之间的关系。研究表明供应链的期望利润随着产需不确定的增加而减少,风险规避下零售商的期望利润低于风险中性时的期望利润,零售商的期望利润随着风险规避程度的加大而减少,零售商最优订购量随风险规避程度的增加而变化。最后数值算例验证了模型和契约协调的有效性。     

供应链生产能力的柔性决策研究

面对不确定性的市场需求,能力的选择和分配是供应链设计中的重要问题.本文应用实物期权方法研究供应链中制造商的生产能力决策,给出柔性条件下的能力决策规则.结果表明,较高(低)的能力投资成本、风险较大(小)的市场和较低(高)的缺货成本将使得制造商推迟(提前)其扩大生产能力决策的实施.     

A two-stage stochastic programming approach for identifying optimal postponement strategies in supply chains with uncertain demand

In the course of globalization, applying mass-customization strategies has led to a high diversity of variants in many economic sectors. Thus, customer demands are often less predictable, and handling increasing inventory stocks as well as avoiding shortfalls have become particularly important. All these complexity drivers result in higher supply chain risks. Postponement strategies have been proposed as a suitable approach to address these problems. Although the concept of postponement and its impact on the supply chain are theoretically well discussed, optimally configuring the entire production and distribution activities is still challenging. We present a two-stage stochastic mixed-integer linear programming model, which comprises an integrated production and distribution planning approach, and considers postponement concepts. In comparison to earlier approaches that examine postponement strategies, our model supports the decision maker under demand uncertainty and considers lead times, penalty costs for shortfalls, as well as inventory-keeping decisions over a tactical planning horizon. This allows an integrated investigation of both form and logistics postponement concepts. Moreover, we consider the decision maker’s risk attitude identifying non-dominated profitable and risk-averse strategies. We illustrate the benefits of the model by using a case study from the apparel industry, and present the results of a sensitivity analysis with respect to varying demand uncertainty and demand correlations as well as different preferences regarding risk aversion. Furthermore, we carry out performance and quality benchmarks and compare the results of a standard mixed-integer linear programming solver, a parallel nested Benders approach and a sample average approximation technique.     

A sustainable second-generation biodiesel supply chain network design problem under risk

This paper presents a multi-objective possibilistic programming model to design a second-generation biodiesel supply chain network under risk. The proposed model minimizes the total costs of biodiesel supply chain from feedstock supply centers to customer centers besides minimizing the environmental impact (EI) of all involved processes under a well-to-wheel perspective. Non-edible feedstocks are considered for biodiesel production. Variable cultivation cost of non-edible feedstock is assumed to be non-linear and dependent upon the amount of cultivated area. New formulation of possibilistic programming method is developed which is able to minimize the total mean and risk values of problems with possibilistic-based uncertainty. To solve the proposed multi-objective model, a hybrid solution approach based on flexible lexicographic and augmented ɛ-constraint methods is proposed which is capable to find appropriate efficient solutions from the Pareto-optimal set. The performance of the proposed possibilistic programming method as well as the developed solution approach are evaluated and validated through conducting a real case study in Iran. The outcome of this study demonstrates that high investment cost is required for improving the environmental impact and risk of sustainable biodiesel supply chain network design under risk. Decision maker preferences are required for suitable trade-off among total costs, risk values and environmental impact.     

Supply chain management: A just-in-time perspective

Just-in-time (JIT) has been a widely recognized production philosophy alternative since the early 1980s. JIT principles and techniques have been widely adopted in many manufacturing firms. More recently, supply chain management has evolved as a discipline focusing on the design, planning and control of processes linking the initial raw materials to the ultimate consumption of the finished product. Supply chain efficiency is dependent on the efficiencies of the individual manufacturing organizations and the ability to connect along the supply chain. In this paper supply chain management from a JIT perspective is investigated, focusing on the linking mechanisms between successive companies and the collective efficiency of the supply chain.