供应中断风险下供应链恢复能力投资决策及协调

摘要： 〖HTSS〗为了减缓供应商生产运营中断对制造商带来的供应中断风险,制造商需要在突发事件前优化供应链恢复能力投资水平。引入CVaR来刻画供应链在突发事件下的应急目标,建立了一定置信水平控制下的供应链恢复能力投资的决策模型,进而揭示了制造商风险规避程度对供应链最优恢复能力投资水平的影响。分权供应链下,制造商运用基于绩效的契约来激励供应商投资合适的恢复能力,以协调供应链。结论表明,CVaR可以恰当描述供应链恢复的能力投资行为,当风险规避程度越高,供应链最优恢复能力投资越多;当单位中断时间的惩罚系数的条件期望值等于单位中断时间的商誉成本的条件期望值时,供应链进入协调状态。     

基于情景分析的供应链风险识别——某全球性公司案例分析

通过对于运营环境的发散性的思考,强调对于未来可能面对的各种突发情景(不论概率大小)都要建立起思想上的准备和相应的措施.本文尝试将该工具融入对于日益复杂的供应链风险管理中.在对供应链风险的情景分析基础之上,提出了一套包括供应链风险的背景设定、风险因子识别、情景开发、供应链薄弱环节识别和风险组合构建的识别流程,并结合一个全球性公司案例,分析了其全球供应链风险的情景识别.     

考虑供应链中断风险的制造商风险应对方案研究

针对存在供应链中断风险的制造商风险应对问题,基于分层决策、综合决策两种不同的供应链风险管理决策方式,分析了由保留冗余产能、储备库存和启用备选制造商等风险应对策略所构成的中断风险应对方案。在此基础上,以供应链期望收益最大为目标,构建了考虑供应链中断风险的制造商风险应对方案决策模型。最后,通过实例分析验证了所给出方法的可行性与有效性,并探讨了决策方式和备选制造商生产延迟时间对最优中断风险应对方案的影响。     

零售商风险厌恶下的订货时机分析

由一个风险厌恶型零售商和一个风险中性制造商组成的供应链中,分析了供应链三种订货时机:预先订货、延迟订货、柔性订货,结果显示供应链将处于制造商不偏好的订货时机;调查了零售商风险厌恶对制造商的影响,发现在一定条件下零售商将削减订货量至少一半,制造商利润将减少至少一半;设计了利润保证契约这一供应链协调机制,发现通过该契约,制造商生产量将提高到原来的两倍以上,还对该契约的实施条件进行了全面分析。     

供应链运作风险影响供应链绩效的实证研究

从实证研究的角度研究了供应链运作风险对供应链绩效的影响.将供应链运作风险归纳为供应风险、需求风险、制造过程风险和信息风险四类,选择供应链可靠性、柔性、服务质量和财务绩效四个变量描述供应链绩效,构建了一个反映二者关系的概念模型.通过对国内制造业企业的问卷调研,利用结构方程模型软件LISREL8.70对模型进行了统计检验,得到了研究结果.研究结果表明:制造过程风险和信息风险对供应链绩效有显著的直接影响;供应风险和需求风险对供应链绩效无显著的直接影响,但通过与制造过程风险和信息风险的相关关系间接影响供应链绩效.研究结论为制造企业实际的供应链风险管理提供理论借鉴.     

延迟区分战略有效性的测度分析

延迟区分战略是近年来提出的供应链管理方面的一个崭新战略，具有提高供应链的敏捷性，降低成本提高收益，准确快速反市场个性化需求等竞争优势。章以延迟区分战略的基本理论为基础，架构了延迟区分战略供应链模型和评价指标体系，并运用模糊综合评价方法对该战略实施效果进行评价，可供我国企业管理借鉴。     

《中断风险与供应链绩效模型研究》

该书为了明确中断风险对供应链网络整体绩效的影响,对中断风险下不同复杂程度的供应链网络进行建模,并通过相应的绩效分析方法对中断风险的影响进行定量分析研究,在此基础上讨论中断风险的有关管理问题。该书应用模型对串型和装配型供应链网络进行建模,并分别     

供应链流程一体化战略模型

从流程再造的角度分析了供应链流程一体化的三个特征：面向客户价值、组织结构的扁平化和打破企业界面。在文中所提到的8条供应链关键业务流程的范围内,可以根据供应链的属性和所处的外部环境的不同识别其关键流程。在对供应链关键流程和对关键流程起关键作用的企业进行识别的基础上,通过使用三种不同的整合战略,即全程整合战略、监控战略和考核战略．可以实现供应链流程一体化。     

随机需求下的产量与定价博弈论供应链模型

用博弈论方法对单制造商、单分销商、短生命周期产品的供应链系统进行分析,对它们所常采用的预测定货、延迟定货和柔性定货等三种定货方式进行了定量定性分析,建立了博弈论模型,并且找到了实现定货最优的阀值。     

柔性供应链的优化及供应商响应时间分析

针对Ricardo提出的柔性供应链结构,赋予其新的涵义：在顾客订单分离点之前,采用模块化技术,以获得规模经济效益;在订单分离点之后,采用延迟生产,以获得范围经济效益。同时以柔性供应链各节点的成本和客户服务水平为优化参数,建立多目标函数优化模型,并借助于MATLAB的GAOT,利用遗传算法求解。最后在优化结果的基础上,研究了柔性供应链的供应商响应时间(Supplier Response Time,SRT),描述了目标SRT与安全库存、客户服务水平的关系及相互影响。     

A coordination theoretic model for three level supply chains using contracts

Typically, supply chain members are dependent on each other to manage various resources and information. The conflicting objectives and lack of coordination between supply chain members may often cause uncertainties in supply and demand. The basic elements of coordination theory like interdependency, coherency and mutuality may help in effective flow of information and material between the dependent supply chain members. Supply chain contract can be an effective coordination mechanism to motivate all the members to be a part of the entire supply chain. There are different types of supply chain contracts such as buy back and quantity flexibility contracts. Supply chain performance may be substantially improved by properly designing the contracts to share risks and rewards. The objective of this paper is to explore the applicability of coordination elements through an analytical model in three-level (Manufacturer-distributor-retailer) serial supply chains using contracts. The model evaluates the impact of supply chain contracts on various performance measures. The impact of some contract may be on some specific performance measure only, which helps managers to choose the type of contract if there is an objective of improving certain performance measure before hand. In three-level supply chains, the contracts are designed at two distinct interfaces: Manufacturer-distributor and distributor-retailer. The model demonstrates the complexity in evaluating the decision variables of three level supply chains. The proposed model is a novel approach to apply coordination theory at various levels of supply chain. The model also presents how the coordination elements are related to each other in various coordination cases.     

Evaluation mechanism for structural robustness of supply chain considering disruption propagation

This paper aims to develop a novel evaluation mechanism for assessing the structural robustness of a supply chain considering disruption propagation. Disruption propagation means that the impact of risks propagates to the whole supply chain along the connected structure. Based on the propagation model, a structural robustness evaluation mechanism is devised by integrating two quantitative metrics, average path length and in degree-out degree. To validate the proposed mechanism, the result of the quantitative assessment of the structural robustness on random networks is compared with the probability of network disruption due to the random risk. From the results of the statistical verifications and sensitivity analysis, it can be said that the proposed mechanism is better at explaining the robustness of a supply chain. In other words, all components of a network, such as nodes and arcs, and their relationships should be considered altogether, in order to more accurately measure the robustness. It may be possible to apply the proposed mechanism to the very first step of designing the supply chain. Especially, in the case of it being hard to redesign a supply chain structure after practically launching and operating the designed network, the proposed mechanism may be utilised to verify whether the planned supply chain is robust to risks or not.     

Internet of Things (IoT)–blockchain-enabled pharmaceutical supply chain resilience in the post-pandemic era

During the COVID-19 pandemic, the current operating environment of pharmaceutical supply chain (PSC) has rapidly changed and faced increasing risks of disruption. The Internet of Things (IoT) and blockchain not only help enhance the efficiency of PSC operations in the information technology domain but also address complex related issues and improve the visibility, flexibility, and transparency of these operations. Although IoT and blockchain have been widely examined in the areas of supply chain and logistics management, further work on PSC is expected by the public to enhance its resilience. To respond to this call, this paper combines a literature review with semi-structured interviews to investigate the characteristics of PSC, the key aspects affecting PSC, and the challenges faced by PSC in the post-pandemic era. An IoT–blockchain-integrated hospital-side oriented PSC management model is also developed. This paper highlights how IoT and blockchain technology can enhance supply chain resilience and provides a reference on how PSC members can cope with the associated risks.     

Literature review on disruption recovery in the supply chain*

Recent research underlines the crucial role of disruption events and recovery policies in supply chains. Despite a wealth of literature on supply chain design with disruption considerations, to the best of our knowledge there is no survey on supply chain with disruptions and recovery considerations. We analyse state-of-the-art research streams on supply chain design and planning with both disruptions and recovery considerations with the aim of relating the existing quantitative methods to empirical research. The paper structures and classifies existing research streams and application areas of different quantitative methods subject to different disruption risks and recovery measures. We identify gaps in current research and delineate future research avenues. The results of this study are twofold: operations and supply chain managers can observe which quantitative tools are available for different application areas; on the other hand, limitations and future research needs for decision-support methods in supply chain risk management domains can be identified.     

Mitigating global supply chain risks through corporate social responsibility

This paper presents a decision model that captures supply-side disruption risks, social risks, and demand-side uncertainty within an integrated global supply chain and corporate social responsibility (CSR) modelling and analysis framework. The global supply chain decision-makers must decide on the level of investment in CSR activities and the choice of trading partners (manufacturer or retailer) given their CSR consciousness and perceived riskiness in order to maximise profit and minimise their overall risk. The model incorporates individual attitudes towards disruption risks among the manufacturers and the retailers, with the demands for the product associated with the retailers being random. The model allows one to investigate the effects of heterogeneous CSR activities in a global supply chain and to compute the resultant equilibrium pattern of product outputs, transactions, product prices, and levels of social responsibility activities. The results show that CSR activities can potentially be used to mitigate global supply chain risk.     

Entropy-based model for the ripple effect: managing environmental risks in supply chains

Due to increasing diversity and growing size of modern industrial supply chains, today problems of identification, assessment and mitigation of disruption risks become challenging goals of the supply chain risk management. In this paper, we focus on environmental (ecological) risks in supply chains which represent threats of adverse effects on living organisms, facilities and environment by effluents, emissions, wastes, resource depletion, etc. arising due to supply chain’s activities. Harmful environmental disruptions may ripple through the supply chain components like a wave. The paper presents the entropy-based optimisation model for reducing the supply chain model size and assessing the economic loss caused by the environmental risks subject to the ripple effect. A main advantage of the suggested entropy-based approach is that it permits to essentially simplify the hierarchical tree-like model of the supply chain, at the same time retaining the basic knowledge about main risk sources.     

New flexibility drivers for manufacturing,supply chain and service operations

Increasing product proliferation, customisation, competition and customer expectations, as well as supply side disruptions, pose significant challenges to firm operations. Such challenges require improved efficiency and resilience in manufacturing, service and supply chain systems. New and innovative flexibility concepts and models offer a prospective route to such operational improvements. Several emerging issues in flexibility, such as risk and uncertainty management, environmental sustainability, optimal strategies under competition, optimal operations with strategic consumer behaviours are being examined in this regard. This overview provides a concise review of these critical research issues, and discusses related papers featured in this special issue. Four major flexibility drivers are classified: disruption risks, resilience and the ripple effect in the supply chain; digitalisation, smart operations and e-supply chains; sustainability and closed-loop supply chains; and supplier integration and behavioural flexibility.     

A hybrid risks-informed approach for the selection of supplier portfolio

In conventional supplier selection approaches, cost consideration is usually emphasised and it renders a vulnerable supply chain with various risks. This article aims to develop a quantitative approach for modelling both supply chain operational risks and disruption risks to support decision-making with regard to order allocation and risk mitigation. We introduce two types of risk evaluation models: value-at-risk (VaR) and conditional value-at-risk (CVaR). Specifically, VaR is used to measure operational risks caused by improper selection and operations of a supplier portfolio to the stochastic demand, which may frequently occur but result in relatively small losses to supply chains; CVaR is used to evaluate disruption risks that are less frequent and tend to cause significant damage. After incorporating risk factors into a probability-based multi-criteria optimisation model, different methods and parameters are compared and tested to determine the factors that may influence the supplier selection process. Computational examples by simulation are presented to illustrate the approach and how decision-makers make trade-offs between costs and hybrid risks.     

A two-period model for selection of resilient multi-tier supply portfolio

A two-period decision-making model is developed for selection of resilient supply portfolio in a multi-tier supply chain under disruption risks. The planning horizon is divided into two aggregate periods: before and after the disruption. The resilience of the supply chain is achieved by selection ahead of time primary supply portfolio and by pre-positioning of risk mitigation inventory of parts at different tiers that will hedge against all disruption scenarios. Simultaneously, recovery and transshipment portfolios are determined for each disruption scenario and decisions on usage the pre-positioned inventory are made to minimise expected cost or maximise expected service level. Some properties of optimal solutions, derived from the proposed model provide additional managerial insights. The findings also indicate that the developed portfolio approach with an embedded network flow structure leads to computationally efficient stochastic mixed integer program with a strong LP relaxation.     

Supply chain resilience for single and multiple sourcing in the presence of disruption risks

This paper investigates the use of sourcing strategies to achieve supply chain resilience under disruptions. The coping strategies considered are single and multiple sourcing, backup supplier contracts, spot purchasing, and collaboration and visibility. Collaboration and visibility, which affect suppliers’ recovery capabilities and a buyer’s warning capability, have not been similarly modelled in the past. A scenario-based mathematical model is developed such that it considers objectives under uncertainties including disruption risks and operational risks. A broad numerical study examines its output for various risk attitudes in a decision-maker, ranging from risk neutral to risk averse. The sensitivity of procurement strategies to other key parameters such as recovery and warning capabilities is examined. One of the major findings is that buyer’s warning capability plays a vital role in enhancing supply chain resilience. We seek to build on these efforts to further support disruption planning and mitigation and to obtain a deeper understanding of the relationship between supply chain characteristics and resilience.