Use of Multicriteria Decision Analysis to Support Weight of Evidence Evaluation

Weight of evidence (WOE) methods are key components of ecological and human health risk assessments. Most WOE applications rely on the qualitative integration of diverse lines of evidence (LOE) representing impact on ecological receptors and humans. Recent calls for transparency in assessments and justifiability of management decisions are pushing the community to consider quantitative methods for integrated risk assessment and management. This article compares and contrasts the type of information required for application of individual WOE techniques and the outcomes that they provide in ecological risk assessment and proposes a multicriteria decision analysis (MCDA) framework for integrating individual LOE in support of management decisions. The use of quantitative WOE techniques is illustrated for a hypothetical but realistic case study of selecting remedial alternatives at a contaminated aquatic site. Use of formal MCDA does not necessarily eliminate biases and judgment calls necessary for selecting remedial alternatives, but allows for transparent evaluation and fusion of individual LOE. It also provides justifiable methods for selecting remedial alternatives consistent with stakeholder and decision‐maker values.     

Fostering Innovation in Contaminated Sediments Management Through Multicriteria Technology Assessment and Public Participation

Management of contaminated sediments is problematic and costly. Several new technologies are under development that may in some cases reduce costs and environmental or ecological impacts. However, there are significant barriers to implementing new technologies, including the increased management complexity, the potential for introducing antagonistic or incommensurate objectives that are unfamiliar to stakeholders or regulators, and the difficulty of capturing private, commercial benefits from environmental improvements that may primarily benefit the public. This article identifies several innovative contaminated sediments technologies, discusses the difficulty of proving or quantifying the benefits of new technologies, and presents an agenda for research that would foster partnerships between scientific, government, and public communities of interest for the purpose of improving innovative technology assessment and environmental decision making.     

Multicriteria Decision Framework for Cybersecurity Risk Assessment and Management

Risk assessors and managers face many difficult challenges related to novel cyber systems. Among these challenges are the constantly changing nature of cyber systems caused by technical advances, their distribution across the physical, information, and sociocognitive domains, and the complex network structures often including thousands of nodes. Here, we review probabilistic and risk-based decision-making techniques applied to cyber systems and conclude that existing approaches typically do not address all components of the risk assessment triplet (threat, vulnerability, consequence) and lack the ability to integrate across multiple domains of cyber systems to provide guidance for enhancing cybersecurity. We present a decision-analysis-based approach that quantifies threat, vulnerability, and consequences through a set of criteria designed to assess the overall utility of cybersecurity management alternatives. The proposed framework bridges the gap between risk assessment and risk management, allowing an analyst to ensure a structured and transparent process of selecting risk management alternatives. The use of this technique is illustrated for a hypothetical, but realistic, case study exemplifying the process of evaluating and ranking five cybersecurity enhancement strategies. The approach presented does not necessarily eliminate biases and subjectivity necessary for selecting countermeasures, but provides justifiable methods for selecting risk management actions consistent with stakeholder and decisionmaker values and technical data.     

What Can Decision Analysis Do for Invasive Species Management?

Decisions about management of invasive species are difficult for all the reasons typically addressed by multiattribute decision analysis: uncertain outcomes, multiple and conflicting objectives, and many interested parties with differing views on both facts and values. This article illustrates how the tools of multiattribute analysis can improve management of invasive species, with an emphasis on making explicit the social values and preferences that must inform invasive species management. Risk assessment protocols developed previously for invasive species management typically suffer from two interacting flaws: (1) separating risk assessment from risk management, thus disrupting essential connections between the social values at stake in invasive species decisions and the scientific knowledge necessary to predict the likely impacts of management actions, and (2) relying on expert judgment about risk framed in qualitative and value-laden terms, inadvertently mixing the expert's judgment about what is likely to happen with personal preferences. Using the values structuring and probability-modeling elements of formal decision analysis can remedy these difficulties and make invasive species management responsive to both good science and public values. The management of feral pigs in Hawaiian ecosystems illustrates the need for such an integrated approach.     

Nuclear Risk Management on Stage: A Decision Analysis Perspective on the UK's Committee on Radioactive Waste Management

In 2003, the UK government set up a broad-based Committee on radioactive waste management (CoRWM) to look at the UK's policy on radioactive waste management with a view to jumpstarting a stalled policy process. The committee's brief was to come up with a set of recommendations that would protect the public and the environment, and be capable of inspiring public confidence. After consulting widely with the public and stakeholders, and drawing on advice from scientists and other experts, CoRWM arrived at a remarkably well-received set of recommendations. On the basis of our experiences of working on CoRWM's multi-criteria decision analysis of different management options, study of CoRWM documentation, and interviews with committee members, we describe the explicit and implicit principles that guided CoRWM. We also give an account of the process by which CoRWM arrived at its conclusions, covering four phases: framing, shortlisting, option assessment, and integration; and four cross-cutting activities: public and stakeholder engagement (PSE), science and engineering input, ethics and social science input, and learning from overseas practice. We finish by outlining some of the key developments in the UK's radioactive waste management process, which followed on from the publication of CoRWM's report, and present our reflections for the benefit of the risk and decision analysts of future committees that, like CoRWM, are charged with recommending to government on the management of technically complex and risky technologies, drawing on extensive public and stakeholder consultation.     

Multi-criteria decision support and evaluation of strategies for nuclear remediation management

Environmental emergency situations can differ in many ways, for instance according to their causes and the dimension of their impacts. Yet, they share the characteristic of sudden onset and the necessity for a coherent and effective emergency management. In this paper we consider decision support in the event of a nuclear or radiological accident in Europe. RODOS, an acronym for real-time on-line decision support system, is a decision support system designed to provide support from the early phases through to the medium and long-term phases. This work highlights the role of multi-criteria decision analysis (MCDA) within RODOS in ensuring the transparency of decision processes within emergency and remediation management. Special emphasis is placed on the evaluation of alternative remediation or countermeasure strategies using the multi-criteria decision support tool Web-HIPRE in scenario focused decision making workshops involving different stakeholder and expert groups. Decision support is enhanced by a module that generates natural language explanations to facilitate the understanding of the evaluation process, therefore contributing to the direct involvement of the decision makers, with the aim of increasing their confidence in the results of the analyses carried out, forming an audit trail for the decision making process and improving the acceptability of the system as a whole.     

Use of risk assessment and life cycle assessment in decision making: a common policy research agenda.

Quantitative risk assessment (RA) and life cycle assessment (LCA) are both analytical tools used to support decision making in environmental management. They have been developed and used by largely separate groups of specialists, and it is worth considering whether there is a common research agenda that may increase the relevance of these tools in decision-making processes. The validity of drawing comparisons between use of the tools is established through examining key aspects of the two approaches for their similarities and differences, including the nature of each approach and contextual and methodological aspects. Six case studies involving use of each approach in public decision making are described and used to draw out concerns about using RA and LCA in this context. The following categories of concern can be distinguished: philosophical approach of the tools; quantitative versus qualitative assessment; stakeholder participation; the nature of the results; and the usefulness of the results in relation to time and financial resource requirements. These can be distilled into a common policy research agenda focusing on: the legitimacy of using tools built on a particular perspective in decision making; recognition and role of value judgments in RA and LCA; treatment of uncertainty and variability; the influence of analytical tools in focusing attention on particular aspects of a decision-making situation; and understandability of the results for nonspecialists. It is concluded that it is time to bring together the experiences of RA and LCA specialists and benefit from cross-fertilization of ideas.     

Integrating multicriteria decision analysis and scenario planning—Review and extension

Scenario planning and multiple criteria decision analysis (MCDA) are two key management science tools used in strategic planning. In this paper, we explore the integration of these two approaches in a coherent manner, recognizing that each adds value to the implementation of the other. Various approaches that have been adopted for such integration are reviewed, with a primary focus on the process of constructing preferences both within and between scenarios. Biases that may be introduced by inappropriate assumptions during such processes are identified, and used to motivate a framework for integrating MCDA and scenario thinking, based on applying MCDA concepts across a range of “metacriteria” (combinations of scenarios and primary criteria). Within this framework, preferences according to each primary criterion can be expressed in the context of different scenarios. The paper concludes with a hypothetical but non-trivial example of agricultural policy planning in a developing country.     

A Multicriteria Decision Analysis Model and Risk Assessment Framework for Carbon Capture and Storage

Multicriteria decision analysis (MCDA) has been applied to various energy problems to incorporate a variety of qualitative and quantitative criteria, usually spanning environmental, social, engineering, and economic fields. MCDA and associated methods such as life‐cycle assessments and cost‐benefit analysis can also include risk analysis to address uncertainties in criteria estimates. One technology now being assessed to help mitigate climate change is carbon capture and storage (CCS). CCS is a new process that captures CO₂ emissions from fossil‐fueled power plants and injects them into geological reservoirs for storage. It presents a unique challenge to decisionmakers (DMs) due to its technical complexity, range of environmental, social, and economic impacts, variety of stakeholders, and long time spans. The authors have developed a risk assessment model using a MCDA approach for CCS decisions such as selecting between CO₂ storage locations and choosing among different mitigation actions for reducing risks. The model includes uncertainty measures for several factors, utility curve representations of all variables, Monte Carlo simulation, and sensitivity analysis. This article uses a CCS scenario example to demonstrate the development and application of the model based on data derived from published articles and publicly available sources. The model allows high‐level DMs to better understand project risks and the tradeoffs inherent in modern, complex energy decisions.     

Evaluation of Multicriteria Decision Analysis Algorithms in Food Safety: A Case Study on Emerging Zoonoses Prioritization

Decision making in food safety is a complex process that involves several criteria of different nature like the expected reduction in the number of illnesses, the potential economic or health-related cost, or even the environmental impact of a given policy or intervention. Several multicriteria decision analysis (MCDA) algorithms are currently used, mostly individually, in food safety to rank different options in a multifactorial environment. However, the selection of the MCDA algorithm is a decision problem on its own because different methods calculate different rankings. The aim of this study was to compare the impact of different uncertainty sources on the rankings of MCDA problems in the context of food safety. For that purpose, a previously published data set on emerging zoonoses in the Netherlands was used to compare different MCDA algorithms: MMOORA, TOPSIS, VIKOR, WASPAS, and ELECTRE III. The rankings were calculated with and without considering uncertainty (using fuzzy sets), to assess the importance of this factor. The rankings obtained differed between algorithms, emphasizing that the selection of the MCDA method had a relevant impact in the rankings. Furthermore, considering uncertainty in the ranking had a high influence on the results. Both factors were more relevant than the weights associated with each criterion in this case study. A hierarchical clustering method was suggested to aggregate results obtained by the different algorithms. This complementary step seems to be a promising way to decrease extreme difference among algorithms and could provide a strong added value in the decision-making process.     

Decision Making Under Uncertainty—An Example for Seismic Risk Management

Decision-making techniques are used to select the "best" alternatives under multiple and often conflicting criteria. Multicriteria decision making (MCDM) necessitates to incorporate uncertainties in the decision-making process. The major thrust of this article is to extend the framework proposed by Yager^{( 1 )} for multiple decisionmakers and fuzzy utilities (payoffs). In addition, the concept of expert credibility factor is introduced. The proposed approach is demonstrated for an example of seismic risk management using a heuristic hierarchical structure. A step-by-step formulation of the proposed approach is illustrated using a hypothetical example and a three-story reinforced concrete building.     

Tiered Approach to Resilience Assessment

Regulatory agencies have long adopted a three‐tier framework for risk assessment. We build on this structure to propose a tiered approach for resilience assessment that can be integrated into the existing regulatory processes. Comprehensive approaches to assessing resilience at appropriate and operational scales, reconciling analytical complexity as needed with stakeholder needs and resources available, and ultimately creating actionable recommendations to enhance resilience are still lacking. Our proposed framework consists of tiers by which analysts can select resilience assessment and decision support tools to inform associated management actions relative to the scope and urgency of the risk and the capacity of resource managers to improve system resilience. The resilience management framework proposed is not intended to supplant either risk management or the many existing efforts of resilience quantification method development, but instead provide a guide to selecting tools that are appropriate for the given analytic need. The goal of this tiered approach is to intentionally parallel the tiered approach used in regulatory contexts so that resilience assessment might be more easily and quickly integrated into existing structures and with existing policies.     

Accounting information for managerial decision-making in shareholder management versus stakeholder management

With global challenges like climate change and, of course, the crisis of capital markets in the recent past stakeholder oriented management receives enhanced attention whereas shareholder value management is increasingly criticized for its undesirable external effects on stakeholders other than owners. Regardless of whether these criticisms are well founded or not, the question arises how accounting-related techniques for supporting managerial decision-making differ in shareholder and stakeholder value management. Accounting information can affect managerial decision-making in two ways: directly as input to decisions or indirectly by influencing the behavior of managers. This article reviews the contributions and limitations of information that prominent accounting-related techniques of shareholder management and stakeholder management provide for managerial decision-making. In a comparative perspective we find that the approaches in shareholder value management are much more advanced. In particular the two roles of information in shareholder value management are manifest in accounting-related techniques which are focused on increasing firm value. The value driver models or residual income-based performance measures may serve as examples. In comparison, accounting-related techniques to support managerial decision-making in stakeholder management are not as well advanced. So far we have approaches which concentrate on selective stakeholder groups and only partially address the multi-dimensionality of stakeholder value creation. From a conceptual perspective our findings indicate that stakeholder value creation requires a more integrated approach for answering the question whether stakeholder value is created or diminished. As a consequence, if stakeholder-orientation is taken seriously, the time has come to pay more attention to related accounting techniques.     

Rethinking Risk Assessment for Public Utility Safety Regulation

To aid in their safety oversight of large‐scale, potentially dangerous energy and water infrastructure and transportation systems, public utility regulatory agencies increasingly seek to use formal risk assessment models. Yet some of the approaches to risk assessment used by utilities and their regulators may be less useful for this purpose than is supposed. These approaches often do not reflect the current state of the art in risk assessment strategy and methodology. This essay explores why utilities and regulatory agencies might embrace risk assessment techniques that do not sufficiently assess organizational and managerial factors as drivers of risk, nor that adequately represent important uncertainties surrounding risk calculations. Further, it describes why, in the special legal, political, and administrative world of the typical public utility regulator, strategies to identify and mitigate formally specified risks might actually diverge from the regulatory promotion of “safety.” Some improvements are suggested that can be made in risk assessment approaches to support more fully the safety oversight objectives of public regulatory agencies, with examples from “high‐reliability organizations” (HROs) that have successfully merged the management of safety with the management of risk. Finally, given the limitations of their current risk assessments and the lessons from HROs, four specific assurances are suggested that regulatory agencies should seek for themselves and the public as objectives in their safety oversight of public utilities.     

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.     

Decision‐Making Analytics Using Plural Resilience Parameters for Adaptive Management of Complex Systems

It is critical for complex systems to effectively recover, adapt, and reorganize after system disruptions. Common approaches for evaluating system resilience typically study single measures of performance at one time, such as with a single resilience curve. However, multiple measures of performance are needed for complex systems that involve many components, functions, and noncommensurate valuations of performance. Hence, this article presents a framework for: (1) modeling resilience for complex systems with competing measures of performance, and (2) modeling decision making for investing in these systems using multiple stakeholder perspectives and multicriteria decision analysis. This resilience framework, which is described and demonstrated in this article via a real‐world case study, will be of interest to managers of complex systems, such as supply chains and large‐scale infrastructure networks.     

Cognitive Mapping Tools: Review and Risk Management Needs

Risk managers are increasingly interested in incorporating stakeholder beliefs and other human factors into the planning process. Effective risk assessment and management requires understanding perceptions and beliefs of involved stakeholders, and how these beliefs give rise to actions that influence risk management decisions. Formal analyses of risk manager and stakeholder cognitions represent an important first step. Techniques for diagramming stakeholder mental models provide one tool for risk managers to better understand stakeholder beliefs and perceptions concerning risk, and to leverage this new understanding in developing risk management strategies. This article reviews three methodologies for assessing and diagramming stakeholder mental models—decision‐analysis‐based mental modeling, concept mapping, and semantic web analysis—and assesses them with regard to their ability to address risk manager needs.     

Flood Risk Management: US Army Corps of Engineers and Layperson Perceptions

Recent severe storm experiences in the U.S. Gulf Coast illustrate the importance of an integrated approach to flood preparedness planning that harmonizes stakeholder and agency efforts. Risk management decisions that are informed by and address decision maker and stakeholder risk perceptions and behavior are essential for effective risk management policy. A literature review and two expert models/mental models studies were undertaken to identify areas of importance in the flood risk management process for layperson, non‐USACE‐expert, and two USACE‐expert groups. In characterizing and mapping stakeholder beliefs about risks in the literature onto current risk management practice, recommendations for accommodating and changing stakeholder perceptions of flood risks and their management are identified. Needs of the U.S. Army Corps of Engineers (USACE) flood preparedness and response program are discussed in the context of flood risk mental models.     

基于公众偏好大数据分析的大群体应急决策质量动态演化研究

针对突发事件大群体应急决策质量及其影响因素的问题，探讨了公众参与视角下突发事件演化的全生命周期，以及各阶段下公众风险感知对应急决策质量的影响，并以“8·12天津港爆炸”为背景案例进行分析。首先，阐述了公众偏好大数据的获取及处理方式，并以此对“8·12天津港爆炸”案例的公众偏好大数据进行预处理和可视化；其次，通过TF-IDF算法提取并量化公众风险感知，建立大群体应急决策质量打分函数，衡量不同阶段的应急决策质量；最后，基于“8·12天津港爆炸”案例的微博数据进行大群体应急决策质量的动态演化分析，得出研究结论和启示。实证表明，所提的模型与方法具有较新颖的研究视角，能够为大数据背景下的应急响应和政府决策提供理论支持和方法辅助。