Risk Analysis and Risk Management: An Historical Perspective

This paper reviews the history of risk analysis and risk management, giving special emphasis to the neglected period prior to the 20th century. The overall objective of the paper is to: (1) dampen the prevailing tendency to view present-day concerns about risk in an ahistorical context; (2) shed light on the intellectual antecedents of current thinking about risk; (3) clarify how contemporary ideas about risk analysis and societal risk management differ significantly from the past; and (4) provide a basis for anticipating future directions in risk analysis and management.     

An Approach for Balancing Health and Ecological Risks at Hazardous Waste Sites

Human health and ecological risks must be balanced at hazardous waste sites in order to ensure that remedial actions prevent unacceptable risks of either type. Actions that are designed to protect humans may fail to protect nonhuman populations and ecosystems or may damage ecosystems. However, there is no common scale of health and ecological risk that would allow comparisons to be performed. This paper presents an approach to addressing this problem based on classifying all risks (i.e., health and ecological risks due contaminants and remediation) as insignificant ( de minimis ), highly significant ( de manifestis ), or intermediate. For health risks the classification is based on standard criteria. However, in the absence of national guidance concerning the acceptability of ecological risks, new ecological criteria are proposed based on an analysis of regulatory precedents. Matrices and flow charts are presented to guide the use of these risk categories in remedial decision making. The assessment of mercury contamination of the East Fork Poplar Creek is presented as an example of the implementation of the approach.     

Intelligent Adversary Risk Analysis: A Bioterrorism Risk Management Model

The tragic events of 9/11 and the concerns about the potential for a terrorist or hostile state attack with weapons of mass destruction have led to an increased emphasis on risk analysis for homeland security. Uncertain hazards (natural and engineering) have been successfully analyzed using probabilistic risk analysis (PRA). Unlike uncertain hazards, terrorists and hostile states are intelligent adversaries who can observe our vulnerabilities and dynamically adapt their plans and actions to achieve their objectives. This article compares uncertain hazard risk analysis with intelligent adversary risk analysis, describes the intelligent adversary risk analysis challenges, and presents a probabilistic defender–attacker–defender model to evaluate the baseline risk and the potential risk reduction provided by defender investments. The model includes defender decisions prior to an attack; attacker decisions during the attack; defender actions after an attack; and the uncertainties of attack implementation, detection, and consequences. The risk management model is demonstrated with an illustrative bioterrorism problem with notional data.     

Nano Risk Analysis: Advancing the Science for Nanomaterials Risk Management

Scientists, activists, industry, and governments have raised concerns about health and environmental risks of nanoscale materials. The Society for Risk Analysis convened experts in September 2008 in Washington, DC to deliberate on issues relating to the unique attributes of nanoscale materials that raise novel concerns about health risks. This article reports on the overall themes and findings of the workshop, uncovering the underlying issues for each of these topics that become recurring themes. The attributes of nanoscale particles and other nanomaterials that present novel issues for risk analysis are evaluated in a risk analysis framework, identifying challenges and opportunities for risk analysts and others seeking to assess and manage the risks from emerging nanoscale materials and nanotechnologies. Workshop deliberations and recommendations for advancing the risk analysis and management of nanotechnologies are presented.     

A general guideline for management of risk from carcinogens

A simple relationship is formulated that helps to discriminate between acceptable and unacceptable individual lifetime risks (RL) to populations that are exposed to chemical carcinogens. The relationship is an empirical one and is developed using objective risk data as well as subjective risk levels that have found substantial acceptance among those concerned with carcinogenic risk assessment issues. The expression sets acceptable levels of lifetime carcinogenic risk and is a function of the total population exposed to the carcinogen. Its use in risk assessment and risk management provides guidance in distinguishing those carcinogens that should be regulated because of the health hazard they pose from those whose regulation may not be needed.     

An Adversarial Risk Analysis Framework for Cybersecurity

Risk analysis is an essential methodology for cybersecurity as it allows organizations to deal with cyber threats potentially affecting them, prioritize the defense of their assets, and decide what security controls should be implemented. Many risk analysis methods are present in cybersecurity models, compliance frameworks, and international standards. However, most of them employ risk matrices, which suffer shortcomings that may lead to suboptimal resource allocations. We propose a comprehensive framework for cybersecurity risk analysis, covering the presence of both intentional and nonintentional threats and the use of insurance as part of the security portfolio. A simplified case study illustrates the proposed framework, serving as template for more complex problems.     

Significant Factors of Aviation Insurance and Risk Management Strategy: An Empirical Study of Taiwanese Airline Carriers

Aviation insurance premiums have become a heavy burden for the airline industry since September 11, 2001. Although the industry must constantly balance its operations between profitability and safety, the reality is that airlines are in the business of making money. Therefore, their ability to reduce cost and manage risk is a key factor for success. Unlike past research, which used subjective judgment methods, this study applied quantitative historical data (1999–2000) and gray relation analysis to identify the primary factors influencing ratemaking for aviation insurance premiums. An empirical study of six airlines in Taiwan was conducted to determine these factors and to analyze the management strategies used to deal with them. Results showed that the loss experience and performance of individual airlines were the key elements associated with aviation insurance premiums paid by each airline. By identifying and understanding the primary factors influencing ratemaking for aviation insurance, airlines will better understand their relative operational strengths and weaknesses, and further help top management identify areas for further improvement. Knowledge of these factors combined with effective risk management strategies, may result in lower premiums and operating costs for airline companies.     

A Comparative Analysis of PRA and Intelligent Adversary Methods for Counterterrorism Risk Management

In counterterrorism risk management decisions, the analyst can choose to represent terrorist decisions as defender uncertainties or as attacker decisions. We perform a comparative analysis of probabilistic risk analysis (PRA) methods including event trees, influence diagrams, Bayesian networks, decision trees, game theory, and combined methods on the same illustrative examples (container screening for radiological materials) to get insights into the significant differences in assumptions and results. A key tenent of PRA and decision analysis is the use of subjective probability to assess the likelihood of possible outcomes. For each technique, we compare the assumptions, probability assessment requirements, risk levels, and potential insights for risk managers. We find that assessing the distribution of potential attacker decisions is a complex judgment task, particularly considering the adaptation of the attacker to defender decisions. Intelligent adversary risk analysis and adversarial risk analysis are extensions of decision analysis and sequential game theory that help to decompose such judgments. These techniques explicitly show the adaptation of the attacker and the resulting shift in risk based on defender decisions.     

Risk Management of Domino Effects Considering Dynamic Consequence Analysis

Domino effects are low‐probability high‐consequence accidents causing severe damage to humans, process plants, and the environment. Because domino effects affect large areas and are difficult to control, preventive safety measures have been given priority over mitigative measures. As a result, safety distances and safety inventories have been used as preventive safety measures to reduce the escalation probability of domino effects. However, these safety measures are usually designed considering static accident scenarios. In this study, we show that compared to a static worst‐case accident analysis, a dynamic consequence analysis provides a more rational approach for risk assessment and management of domino effects. This study also presents the application of Bayesian networks and conflict analysis to risk‐based allocation of chemical inventories to minimize the consequences and thus to reduce the escalation probability. It emphasizes the risk management of chemical inventories as an inherent safety measure, particularly in existing process plants where the applicability of other safety measures such as safety distances is limited.     

项目风险分析与管理

本文在分析比较传统风险分析方法的基础上,提出了一个更为有效的风险分析方法,即“交叉分析-蒙特卡罗模拟”综合模型。并利用此模型对H集团的某技改投资项目进行了案例分析。在此基础上,提出了建立项目风险防范预警系统的风险管理模式。     

Multiattribute Risk Analysis in Nuclear Emergency Management

Radiation protection authorities have seen a potential for applying multiattribute risk analysis in nuclear emergency management and planning to deal with conflicting objectives, different parties involved, and uncertainties. This type of approach is expected to help in the following areas: to ensure that all relevant attributes are considered in decision making; to enhance communication between the concerned parties, including the public; and to provide a method for explicitly including risk analysis in the process. A multiattribute utility theory analysis was used to select a strategy for protecting the population after a simulated nuclear accident. The value-focused approach and the use of a neutral facilitator were identified as being useful.     

The SAM Framework: Modeling the Effects of Management Factors on Human Behavior in Risk Analysis

Complex engineered systems, such as nuclear reactors and chemical plants, have the potential for catastrophic failure with disastrous consequences. In recent years, human and management factors have been recognized as frequent root causes of major failures in such systems. However, classical probabilistic risk analysis (PRA) techniques do not account for the underlying causes of these errors because they focus on the physical system and do not explicitly address the link between components' performance and organizational factors. This paper describes a general approach for addressing the human and management causes of system failure, called the SAM (System-Action-Management) framework. Beginning with a quantitative risk model of the physical system, SAM expands the scope of analysis to incorporate first the decisions and actions of individuals that affect the physical system. SAM then links management factors (incentives, training, policies and procedures, selection criteria, etc.) to those decisions and actions. The focus of this paper is on four quantitative models of action that describe this last relationship. These models address the formation of intentions for action and their execution as a function of the organizational environment. Intention formation is described by three alternative models: a rational model, a bounded rationality model, and a rule-based model. The execution of intentions is then modeled separately. These four models are designed to assess the probabilities of individual actions from the perspective of management, thus reflecting the uncertainties inherent to human behavior. The SAM framework is illustrated for a hypothetical case of hazardous materials transportation. This framework can be used as a tool to increase the safety and reliability of complex technical systems by modifying the organization, rather than, or in addition to, re-designing the physical system.     

软件项目风险管理中的敏感性分析研究

采用实证研究方式,应用EXPERT COCOMO模型与功能点分析模型(FPA)对某公司的M IS系统开发过程中所存在的风险进行分析。在对敏感性分析原理进行阐述之后,对某公司的管理信息系统的功能点进行了分析,并对其中所存在的风险进行了识别和量化,然后分别对分析能力(ACAP)、编程能力(PCAP)、可复用性(RU SE)3个主要风险因素的变动对项目的所产生的影响进行了敏感性分析。可望对管理信息系统开发决策中的风险分析有所帮助。     

Cyber Risk Management for Critical Infrastructure: A Risk Analysis Model and Three Case Studies

Managing cyber security in an organization involves allocating the protection budget across a spectrum of possible options. This requires assessing the benefits and the costs of these options. The risk analyses presented here are statistical when relevant data are available, and system‐based for high‐consequence events that have not happened yet. This article presents, first, a general probabilistic risk analysis framework for cyber security in an organization to be specified. It then describes three examples of forward‐looking analyses motivated by recent cyber attacks. The first one is the statistical analysis of an actual database, extended at the upper end of the loss distribution by a Bayesian analysis of possible, high‐consequence attack scenarios that may happen in the future. The second is a systems analysis of cyber risks for a smart, connected electric grid, showing that there is an optimal level of connectivity. The third is an analysis of sequential decisions to upgrade the software of an existing cyber security system or to adopt a new one to stay ahead of adversaries trying to find their way in. The results are distributions of losses to cyber attacks, with and without some considered countermeasures in support of risk management decisions based both on past data and anticipated incidents.     

Foundational Issues in Risk Assessment and Risk Management

This is a perspective article on foundational issues in risk assessment and management. The aim is to discuss the needs, obstacles, and challenges for the establishment of a renewed, strong scientific foundation for risk assessment and risk management suited for the current and future technological challenges. The focus is on (i) reviewing and discussing the present situation and (ii) identifying how to best proceed in the future, to develop the risk discipline in the directions needed. The article provides some reflections on the interpretation and understanding of the concept of “foundations of risk assessment and risk management” and the challenges therein. One main recommendation is that different arenas and moments for discussion are needed to specifically address foundational issues in a way that embraces the many disciplinary communities involved (from social scientists to engineers, from behavioral scientists to statisticians, from health physicists to lawyers, etc.). One such opportunity is sought in the constitution of a novel specialty group of the Society of Risk Analysis.     

Major Hazard Information Policy in the European Community: Implications for Risk Analysis

The main impetus to the development of information about major industrial hazards in the European Community comes from the so-called Seveso Directive, which defines an information network and requires the generation and transmission of information as the basis for accident prevention and risk management. This important policy development, which calls for the formal identification and analysis of major hazards and the communication of risk information to members of the public, presents new opportunities and challenges to risk analysis and research in Europe. This paper briefly reviews the accidents that gave rise to the Directive and shaped its content, and then summarizes its requirements. The status of its implementation in the EC Member States is discussed, with special emphasis given to the comparison of safety analysis practices, the Major Accident Reporting System (MARS), and risk communication. Some new research directions stimulated by the Directive are identified.     

Dealing with the White Death: Avalanche Risk Management for Traffic Routes

This article discusses mitigation strategies to protect traffic routes from snow avalanches. Up to now, mitigation of snow avalanches on many roads and railways in the Alps has relied on avalanche sheds, which require large initial investments resulting in high opportunity costs. Therefore, avalanche risk managers have increasingly adopted organizational mitigation measures such as warning systems and closure policies instead. The effectiveness of these measures is, however, greatly dependent on human decisions. In this article, we present a method for optimizing avalanche mitigation for traffic routes in terms of both their risk reduction impact and their net benefit to society. First, we introduce a generic framework for assessing avalanche risk and for quantifying the impact of mitigation. This allows for sound cost-benefit comparisons between alternative mitigation strategies. Second, we illustrate the framework with a case study from Switzerland. Our findings suggest that site-specific characteristics of avalanche paths, as well as the economic importance of a traffic route, are decisive for the choice of optimal mitigation strategies. On routes endangered by few avalanche paths with frequent avalanche occurrences, structural measures are most efficient, whereas reliance on organizational mitigation is often the most appropriate strategy on routes endangered by many paths with infrequent or fuzzy avalanche risk. Finally, keeping a traffic route open may be very important for tourism or the transport industry. Hence, local economic value may promote the use of a hybrid strategy that combines organizational and structural measures to optimize the resource allocation of avalanche risk mitigation.     

Risk Preferences,Probability Weighting,and Strategy Tradeoffs in Wildfire Management

Wildfires present a complex applied risk management environment, but relatively little attention has been paid to behavioral and cognitive responses to risk among public agency wildfire managers. This study investigates responses to risk, including probability weighting and risk aversion, in a wildfire management context using a survey‐based experiment administered to federal wildfire managers. Respondents were presented with a multiattribute lottery‐choice experiment where each lottery is defined by three outcome attributes: expenditures for fire suppression, damage to private property, and exposure of firefighters to the risk of aviation‐related fatalities. Respondents choose one of two strategies, each of which includes “good” (low cost/low damage) and “bad” (high cost/high damage) outcomes that occur with varying probabilities. The choice task also incorporates an information framing experiment to test whether information about fatality risk to firefighters alters managers' responses to risk. Results suggest that managers exhibit risk aversion and nonlinear probability weighting, which can result in choices that do not minimize expected expenditures, property damage, or firefighter exposure. Information framing tends to result in choices that reduce the risk of aviation fatalities, but exacerbates nonlinear probability weighting.     

Perspectives on Risk Management

The development of the techniques of risk assessment and management are considered, noting the early emphasis on quantitative approaches. The basic strategies available to governments for risk management—educational, economic, and regulatory—are discussed. Six specific issues are considered with reference to the Canadian experience and the lessons learned. These are: the separation of risk assessment from risk management; the uncertainties of science; the weakness of numerical comparisons; too great a trust in education; the Great White Father Syndrome; and regulatory perils. This examination shows a number of inadequacies in the application of risk management techniques. It is suggested that knowledge of the limitations of quantitative assessment in its application to decision-making together with the involvement of those affected by the risk in the decision-making processes will lead to greater success.