Operations Risk Management: Overview of Paul Kleindorfer's Contributions

This paper reviews Paul Kleindorfer's contributions to Operations Management (OM), with a special focus on his research on risk management. An annotated bibliography of selected other contributions reviews the breadth of topics that have occupied Kleindorfer's research attention over his now 45 + years of research. These include optimal control theory, scheduling theory, decision sciences, investment planning and peak load pricing, plus a number of important applications in network industries and insurance. In the area of operations risk management, we review recent work that Kleindorfer and his colleagues in the Wharton Risk Center have undertaken on environmental management and operations, focusing on process safety and environmental risks in the chemical industry. This work is directly related to Kleindorfer's work in the broader area of “sustainable operations”, which he, Kal Singhal and Luk Van Wassenhove recently surveyed as part of the new initiative at POMS to encompass sustainable management practices within the POMS community. Continuing in the area of supply chain risks, the paper reviews Kleindorfer's contributions to the development of an integrated framework for contracting and risk hedging for supply management. The emphasis on alignment of pricing, performance and risk management in this framework is presaged in the work undertaken by Kleindorfer and his co‐authors in the 1980s on after‐sales support services for high‐technology products. This work on supply chain risk, and its successors, is reviewed here in light of its growing importance in managing the unbundled and global supply chains characteristic of the new economy.     

Project risk management using multiple criteria decision-making technique and decision tree analysis: a case study of Indian oil refinery

This study proposes an integrated analytical framework for effective management of project risks using combined multiple criteria decision-making technique and decision tree analysis. First, a conceptual risk management model was developed through thorough literature review. The model was then applied through action research on a petroleum oil refinery construction project in the Central part of India in order to demonstrate its effectiveness. Oil refinery construction projects are risky because of technical complexity, resource unavailability, involvement of many stakeholders and strict environmental requirements. Although project risk management has been researched extensively, practical and easily adoptable framework is missing. In the proposed framework, risks are identified using cause and effect diagram, analysed using the analytic hierarchy process and responses are developed using the risk map. Additionally, decision tree analysis allows modelling various options for risk response development and optimises selection of risk mitigating strategy. The proposed risk management framework could be easily adopted and applied in any project and integrated with other project management knowledge areas.     

Integrating performance and risk aspects of supply chain design processes

Abstract

Supply chain design is a complex and relatively poorly structured process, involving choosing many decisional parameters and it usually requires consideration of numerous sources of uncertainty. Many conventional processes of supply chain design involve taking a deterministic approach, using point estimates, on important measures of supply chain effectiveness such as cost, quality, delivery reliability and service levels. Supply chain disruptions are often separately considered as risks, both in the research literature and in practice, meaning that a purely traditional risk management and risk minimization approach is taken. We have developed and applied an approach that combines the intellect and experience of the supply chain designer with the power of evaluation provided by a Monte Carlo simulation model, which uses decision analysis techniques to explicitly incorporate the full spectrum of uncertain quantities across the set of alternative supply chain designs being considered. After defining and setting out the general decision variables and uncertainty factors for 16 distinct supply chain design decision categories, we then apply that approach to combine the decision-makers’ heuristics with the probabilistic modeling approach, iteratively, to achieve the best of both elements of such an approach. This novel approach to fully integrating performance and risk elements of supply chain designs is then illustrated with a case study. Finally, we call for further developmental research and field work to refine this approach.     

基于EVA与经营风险偏好的供应链鲁棒优化模型

在由一个制造商和多个外部供应商构成的多产品、多阶段供应链中,将经济增加值（EVA）作为体现价值创造的绩效指标,并考虑决策者的经营风险偏好,采用已知概率的离散情景描述资本成本与需求的波动情况,利用鲁棒随机规划方法,建立了以价值创造为目标的供应链鲁棒优化模型。应用分析的结果表明,模型能够将供应链的绩效与风险管理结合起来,减少资本成本与需求不确定对目标值的影响,得到具有鲁棒性的最优解,而且越是风险厌恶型的决策者越会为了保持较低的经营风险而放弃较大的EVA值。同时,决策者可选择不同的权重系数侧重于解鲁棒或模型鲁棒,保证供应链运作的鲁棒性,实现价值创造的目标。     

Impact of strategic and operational risk management practices on firm performance: An empirical investigation

Increasingly, creating and delivering value through complex supply chain networks involves substantial risks. However, strategy development under business risk conditions is not well-understood. This cross-country research examines how, under conditions of supply chain network risk, firms develop effective risk management practices. Using a literature review and survey research of managers from global firms; we present a research model, and empirically test the hypothesized relationships. The results show that under conditions of uncertainty, management decision-making is more likely to be cautious until visible forms of risks emerge, and prudent response mechanisms are put in place. This study identifies the crucial role of supply chain exploration and exploitation practices, and their influence in development of network risk management practices, leading to competitive financial outcomes.     

A hybrid approach to configure eco-efficient supply chains under consideration of performance and risk aspects

Formal models that support multi-criteria decision making represent a strongly growing area in sustainable supply chain management research. However, uncertainties and risks are seldom considered in quantitative models for green supply chain (SC) design. The paper at hand suggests a hybrid approach to configure an eco-efficient SC for a new product under consideration of economic and environmental risks. Discrete-event simulation is applied to assess the financial, operational and environmental performance of different SC configuration options while the value-at-risk concept is adapted to evaluate related SC risks. The analytic hierarchy process is employed to solve the resulting multi-criteria decision problem of choosing the best option. The approach is illustrated at a case example of a fast moving consumer goods manufacturer.     

A framework for managing sustainable palm oil supply chain operations: a case of Indonesia

The challenges faced by the palm oil industry in Indonesia lie in the supply chain risk management, specifically in the integration of decision-making at the operational level. Problems at this level have become more apparent while the industry continues to face pressures as a consequence of the strict conditions imposed by, predominantly, international trading communities, and in some cases, by the environmental issues from domestic and overseas. As part of an effort to address the underlying problems, this paper aims to propose a conceptual framework that can be used to effectively manage the palm oil supply chain, by integrating risk assessment, performance measurement and supply chain optimisation, which will be compiled into a decision-making tool. The perceived benefits from the implementation of this framework include more realistic target planning, clearer prediction of risks and better visibility of the operating performance.     

供应链提前期风险空间传递机理与控制策略

针对供应链结构特性,本文分析了供应链提前期风险在链状供应链上的空间传递机理;根据风险因素作用的特点,将提前期风险划分为节点企业自身提前期风险、物流延期风险和传递风险。在此基础上,构建了供应链提前期风险空间传递模型和供应链提前期风险控制机理框架,并提出了关键的控制策略;最后通过算例分析验证了模型的有效性。     

供应链风险管理中的几个重要问题

供应链风险管理是供应链管理领域一个新的热点研究方向,吸引了来自于运作管理、财务管理和战略管理等领域的研究人员和企业管理人员的极大关注.文章对有关供应链风险管理定量分析的一些主要工作进行评述,并讨论这一领域的几个重要研究方向,希望引起国内学术界的重视.     

Disruptions in tightly coupled supply chain networks: the case of the US offshore oil industry

Managers have paid increasing attention to the exposure of their supply chains to disruptions and seek ways to mitigate supply chain vulnerability. The interconnectedness of tightly coupled supply chain networks makes this a challenging task, because interconnectedness and tight coupling of nodes in the network lead to an amplification of the actual risk exposure. This phenomenon can be attributed to the propagation of losses through the network, which exhibits certain dynamics. In order to investigate this mechanism, we studied the complex supply chain network of the oil industry in the Gulf of Mexico. Our results provide an estimate of the economic impact of eventual random and hurricane-related disruptions and can be used as a decision support tool for risk management of supply disruptions in interconnected supply chain networks.     

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.     

基于粗糙集与未确知模型的供应商风险评估方法研究

供应商是制造商材料的来源,供应商风险的发生可能导致原来井然有序的供应链无法正常运转,因此,供应商风险的预警与评估在供应链风险管理中占据着举足轻重的地位。本文提出一种基于粗糙集和未确知测度理论的供应商风险评估方法,该方法首先运用粗糙集理论对繁杂的供应商风险指标体系进行精简,并确定指标权重,然后运用未确知测度模型对供应商风险进行评估,从而使评估结果更加客观。最后在实证研究中以某汽车制造商企业供应商风险评估体系为例,阐明了该评估方法的科学有效性以及评估结果的合理性。     

Managing Disruption Risks in Supply Chains

There are two broad categories of risk affecting supply chain design and management: (1) risks arising from the problems of coordinating supply and demand, and (2) risks arising from disruptions to normal activities. This paper is concerned with the second category of risks, which may arise from natural disasters, from strikes and economic disruptions, and from acts of purposeful agents, including terrorists. The paper provides a conceptual framework that reflects the joint activities of risk assessment and risk mitigation that are fundamental to disruption risk management in supply chains. We then consider empirical results from a rich data set covering the period 1995–2000 on accidents in the U. S. Chemical Industry. Based on these results and other literature, we discuss the implications for the design of management systems intended to cope with supply chain disruption risks.     

An Integrated Framework for Environmental Multi‐Impact Spatial Risk Analysis

Quantitative risk analysis is being extensively employed to support policymakers and provides a strong conceptual framework for evaluating decision alternatives under uncertainty. Many problems involving environmental risks are, however, of a spatial nature, i.e., containing spatial impacts, spatial vulnerabilities, and spatial risk‐mitigation alternatives. Recent developments in multicriteria spatial analysis have enabled the assessment and aggregation of multiple impacts, supporting policymakers in spatial evaluation problems. However, recent attempts to conduct spatial multicriteria risk analysis have generally been weakly conceptualized, without adequate roots in quantitative risk analysis. Moreover, assessments of spatial risk often neglect the multidimensional nature of spatial impacts (e.g., social, economic, human) that are typically occurring in such decision problems. The aim of this article is therefore to suggest a conceptual quantitative framework for environmental multicriteria spatial risk analysis based on expected multi‐attribute utility theory. The framework proposes: (i) the formal assessment of multiple spatial impacts; (ii) the aggregation of these multiple spatial impacts; (iii) the assessment of spatial vulnerabilities and probabilities of occurrence of adverse events; (iv) the computation of spatial risks; (v) the assessment of spatial risk mitigation alternatives; and (vi) the design and comparison of spatial risk mitigation alternatives (e.g., reductions of vulnerabilities and/or impacts). We illustrate the use of the framework in practice with a case study based on a flood‐prone area in northern Italy.     

Multicriteria Decision Analysis: A Comprehensive Decision Approach for Management of Contaminated Sediments

Contaminated sediments and other sites present a difficult challenge for environmental decisionmakers. They are typically slow to recover or attenuate naturally, may involve multiple regulatory agencies and stakeholder groups, and engender multiple toxicological and ecotoxicological risks. While environmental decision-making strategies over the last several decades have evolved into increasingly more sophisticated, information-intensive, and complex approaches, there remains considerable dissatisfaction among business, industry, and the public with existing management strategies. Consequently, contaminated sediments and materials are the subject of intense technology development, such as beneficial reuse or in situ treatment. However, current decision analysis approaches, such as comparative risk assessment, benefit-cost analysis, and life cycle assessment, do not offer a comprehensive approach for incorporating the varied types of information and multiple stakeholder and public views that must typically be brought to bear when new technologies are under consideration. Alternatively, multicriteria decision analysis (MCDA) offers a scientifically sound decision framework for management of contaminated materials or sites where stakeholder participation is of crucial concern and criteria such as economics, environmental impacts, safety, and risk cannot be easily condensed into simple monetary expressions. This article brings together a multidisciplinary review of existing decision-making approaches at regulatory agencies in the United States and Europe and synthesizes state-of-the-art research in MCDA methods applicable to the assessment of contaminated sediment management technologies. Additionally, it tests an MCDA approach for coupling expert judgment and stakeholder values in a hypothetical contaminated sediments management case study wherein MCDA is used as a tool for testing stakeholder responses to and improving expert assessment of innovative contaminated sediments technologies.     

销售成本信息不对称下供应商风险规避的回购契约

在价格随机条件下,销售成本信息不对称且供应商规避风险时,本文探讨回购契约协调供应链的最优决策。在前提假设的基础上构建新的回购契约模型,求解并用算例进行仿真验证,考虑信息不对称与风险规避共同发生耦合作用后对供应链相关决策变量的影响。研究结果表明：在价格随机条件下,不管信息是否对称,只要供应商有风险规避意识,供应链相关决策变量均发生分岔突变;不管市场价格是否随机,也不管供应商是否风险规避,只要零售商隐瞒私人销售成本信息,就会给自己带来额外的收益,但会给供应商与整个供应链带来损害;供应链上的信息越不对称,在分岔突变区域,相关决策变量的振荡幅度越大。分岔突变现象是市场价格随机和供应商风险规避耦合作用后特有的现象;零售商能够利用信息不对称给自己带来额外的好处,但会损害供应商和供应链的利益;供应商防范零售商这种损人利己行为的最好对策,就是通过设计一种合作机制,以最低成本的方式来促使零售商将销售成本信息公开化;另外,供应商以平稳的心态(风险中性)应对外部风险,更有利于提高其自身决策的水平。     

中国核电站供应链及其风险研究

基于核燃料和设备的核电站供应链体系是实现核电站连续生产运行的基本保障,因核电站生命周期较长,随着核电企业运行时间的延续,四大核电供应链面临的矛盾,以及核电站上游环节供应链的诸多变化,如供应商倒闭、供应商价格锁定、设备和备件更新换代无法实现直接维修更换等,带来了众多的核电站供应链的风险。核电站要建立一套完善的主动供应链风险管理流程,以识别、分析、定义和规避供应链风险,确保核电站连续高效、安全运行目标的实现。     

Green supply chain performance measurement using the analytic hierarchy process: a comparative analysis of manufacturing organisations

The main purpose of this research is to develop and deploy an analytical framework for measuring the environmental performance of manufacturing supply chains. This work's theoretical bases combine and reconcile three major areas: supply chain management, environmental management and performance measurement. Researchers have suggested many empirical criteria for green supply chain (GSC) performance measurement and proposed both qualitative and quantitative frameworks. However, these are mainly operational in nature and specific to the focal company. This research develops an innovative GSC performance measurement framework by integrating supply chain processes (supplier relationship management, internal supply chain management and customer relationship management) with organisational decision levels (both strategic and operational). Environmental planning, environmental auditing, management commitment, environmental performance, economic performance and operational performance are the key level constructs. The proposed framework is then applied to three selected manufacturing organisations in the UK. Their GSC performance is measured and benchmarked by using the analytic hierarchy process (AHP), a multiple-attribute decision-making technique. The AHP-based framework offers an effective way to measure and benchmark organisations’ GSC performance. This study has both theoretical and practical implications. Theoretically it contributes holistic constructs for designing a GSC and managing it for sustainability; and practically it helps industry practitioners to measure and improve the environmental performance of their supply chain.     

Can a Participatory Approach Contribute to Food Chain Risk Analysis?

We consider food chain risks and specifically address stakeholder participation in the risk analysis process. We combine social and natural science perspectives to explore the participation process in relation to food risks and, in particular, to consider how some specific participation processes might be scientifically evaluated and how stakeholder participation in general might be incorporated into food risk decision making. We have built considerations based on three large integrative case studies that examine aspects of participatory processes. Here we use the case studies collectively to illustrate observations and beliefs concerning the nature of the interaction of stakeholders with established quantitative risk methodologies. This account is not supported by any large volume of analysis. The views in the report are expressed in relation to an accepted risk analysis framework and also with respect to probabilistic modeling of risks and are illustrated where possible with anecdotal reports of actual case study events.     

基于风险规避和公平偏好的供应链收益共享契约协调研究

在一个简单的二级供应链系统中,建立了供应商和零售商同时具有风险规避和公平偏好的收益共享契约协调模型,通过修正、扩展FS效用收益模型,先后考察并分析了分散决策和集中决策下供应链的协调状态,研究发现,供应商和零售商的风险规避系数和公平偏好系数及收益份额必须满足特定的条件,收益共享契约才能使系统供应链整体达到协调状态;在此基础上,对风险规避和公平偏好因素进行敏感度分析,得到供应商和零售商行为偏好系数对供应链及成员最优订货量的影响;最后进行演化博弈算例分析和结论验证,体现了该协调模型的有效性和实用性。由此说明供应商和零售商的风险规避和公平偏好因素同时作用会改变系统供应链协调时的最优订货量,并对决策人的决策行为产生很大的影响。