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.     

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.     

The Role of Decision Analysis in Risk Analysis: A Retrospective

In commemorating the 40th anniversary of Risk Analysis, this article takes a retrospective look at some of the ways in which decision analysis (as a “sibling field”) has contributed to the development both of the journal, and of risk analysis as a field. I begin with some early foundational papers from the first decade of the journal's history. I then review a number of papers that have applied decision analysis to risk problems over the years, including applications of related methods such as influence diagrams, multicriteria decision analysis, and risk matrices. The article then reviews some recent trends, from roughly the last five years, and concludes with observations about the parallel evolution of risk analysis and decision analysis over the decades—especially with regard to the importance of representing multiple stakeholder perspectives, and the importance of behavioral realism in decision models. Overall, the extensive literature surveyed here supports the view that the incorporation of decision-analytic perspectives has improved the practice of risk analysis.     

对方案有偏好的不确定语言多属性决策方法

研究了属性权重完全未知、属性值和对方案的偏好值以不确定语言变量形式给出的不确定语言多属性决策问题。首先,引入不确定语言变量的运算法则,以及不确定语言变量之间比较的可能度公式,给出了不确定语言变量间的距离的概念。针对属性权重完全未知的情形,给出了求解权重的公式。然后,利用不确定语言加权平均算子,对不确定语言决策信息进行加权集成,并利用可能度公式构造可能度矩阵(互补判断矩阵),继而利用互补判断矩阵排序公式对决策方案进行排序和择优。最后进行了实例分析。     

基于层次分析法在价值链分析中的应用研究

竞争者价值链之间的差异是竞争优势的一个关键来源,但是竞争价值链分析大多停留在定性分析阶段,只是提出了分析思路和模式,在定量化分析方面尚未有较为深入的进展。层次分析法是解决这类问题的行之有效的方法,本文尝试将层次分析法引入价值链分析中,通过对不同企业价值链活动的分析,得出竞争优势的优先排序,作为企业并购的决策依据。研究表明,本方法对企业并购的决策分析是比较有意义的。     

Assessing the Multidimensionality of Coastal Erosion Risks: Public Participation and Multicriteria Analysis in a Mediterranean Coastal System

The complex and multidimensional nature of coastal erosion risks makes it necessary to move away from single-perspective assessment and management methods that have conventionally predominated in coastal management. This article explores the suitability of participatory multicriteria analysis (MCA) for improving the integration of diverse expertises and values and enhancing the social-ecological robustness of the processes that lead to the definition of relevant policy options to deal with those risks. We test this approach in the Mediterranean coastal locality of Lido de Sète in France. Results show that the more adaptive alternatives such as "retreating the shoreline" were preferred by our selected stakeholders to those corresponding to "protecting the shoreline" and the business as usual proposals traditionally put forward by experts and policymakers on these matters. Participative MCA contributed to represent coastal multidimensionality, elicit and integrate different views and preferences, facilitated knowledge exchange, and allowed highlighting existing uncertainties.     

多属性相对变权决策模型及方法

为克服多因素变权决策方法以及多属性决策Choquet积分模型没有科学反映多属性决策过程中决策者点依赖偏好关联行为的技术缺陷,在借鉴摆幅置权方法和网络分析法技术要点的基础上,运用数据包络分析的相对评价思维,提出一种全新的评价与决策方法即多属性相对变权决策方法。相对于多因素变权决策方法,新方法可以直接反映决策者的点依赖偏好结构,从而可以克服前者在反映点依赖偏好关联行为上所存在的源于决策分析者的武断随意性;相对于多属性决策Choquet积分模型,新方法可以反映决策者的点依赖偏好关联行为,并且在多数实际决策场合可以较有效地规避Choquet积分模型在决策参数判断上的指数复杂性难题。案例应用验证表明：新方法可以给出与决策者关于偏好依赖关联定性看法及客观事实非常相符的选择结论,可以更好地反映决策者的具体偏好。     

Water Quality Failures in Distribution Networks—Risk Analysis Using Fuzzy Logic and Evidential Reasoning

The evaluation of the risk of water quality failures in a distribution network is a challenging task given that much of the available data are highly uncertain and vague, and many of the mechanisms are not fully understood. Consequently, a systematic approach is required to handle quantitative-qualitative data as well as a means to update existing information when new knowledge and data become available. Five general pathways (mechanisms) through which a water quality failure can occur in the distribution network are identified in this article. These include contaminant intrusion, leaching and corrosion, biofilm formation and microbial regrowth, permeation, and water treatment breakthrough (including disinfection byproducts formation). The proposed methodology is demonstrated using a simplified example for water quality failures in a distribution network. This article builds upon the previous developments of aggregative risk analysis approach. Each basic risk item in a hierarchical framework is expressed by a triangular fuzzy number, which is derived from the composition of the likelihood of a failure event and the associated failure consequence . An analytic hierarchy process is used to estimate weights required for grouping noncommensurate risk sources. The evidential reasoning is proposed to incorporate newly arrived data for the updating of existing risk estimates. The exponential ordered weighted averaging operators are used for defuzzification to incorporate attitudinal dimension for risk management. It is envisaged that the proposed approach could serve as a basis to benchmark acceptable risks in water distribution networks.     

Ecological Risk Ranking: Development and Evaluation of a Method for Improving Public Participation in Environmental Decision Making

This article reports an extension of the Carnegie Mellon risk-ranking method to incorporate ecological risks and their attributes. On the basis of earlier risk-perception studies, we identified a set of 20 relevant attributes for describing health, safety, and environmental hazards in standardized risk summary sheets. In a series of three ranking sessions, 23 laypeople ranked 10 such hazards in a fictional Midwestern U.S. county using both holistic and multiattribute ranking procedures. Results were consistent with those from previous studies involving only health and safety hazards, providing additional evidence for the validity of the method and the replicability of the resulting rankings. Holistic and multiattribute risk rankings were reasonably consistent both for individuals and for groups. Participants reported that they were satisfied with the procedures and results, and indicated their support for using the method to advise real-world risk-management decisions. Agreement among participants increased over the course of the exercise, perhaps because the materials and deliberations helped participants to correct their misconceptions and clarify their values. Overall, health and safety attributes were judged more important than environmental attributes. However, the overlap between the importance rankings of these two sets of attributes suggests that some information about environmental impacts is important to participants' judgments in comparative risk-assessment tasks.     

Estimation of Error and Bias in Bayesian Monte Carlo Decision Analysis Using the Bootstrap

Bayesian Monte Carlo (BMC) decision analysis adopts a sampling procedure to estimate likelihoods and distributions of outcomes, and then uses that information to calculate the expected performance of alternative strategies, the value of information, and the value of including uncertainty. These decision analysis outputs are therefore subject to sample error. The standard error of each estimate and its bias, if any, can be estimated by the bootstrap procedure. The bootstrap operates by resampling (with replacement) from the original BMC sample, and redoing the decision analysis. Repeating this procedure yields a distribution of decision analysis outputs. The bootstrap approach to estimating the effect of sample error upon BMC analysis is illustrated with a simple value-of-information calculation along with an analysis of a proposed control structure for Lake Erie. The examples show that the outputs of BMC decision analysis can have high levels of sample error and bias.     

Prioritising indicators in improving supply chain performance using fuzzy AHP: insights from the case example of four Indian manufacturing companies

Abstract

In this contribution, we aim to prioritise the indicators to enhance the organisational supply chain’s (SC) effectiveness from an industrial perspective. It will help industries to develop strategies for managing the SC effectively and ensuring improvement in performance continuously. To achieve this, this work proposes to use a two-phase research methodology. First, 36 SC performance improvement indicators are recognised from a literature survey and from field and industrial expert’s inputs. Secondly, a structural model is proposed using the fuzzy analytical hierarchy process (AHP) to prioritise the indicators strategically to improve the SC performance. The fuzzy AHP method helps determine the priority of concerns of the identified indicators under fuzzy surroundings. Inputs in this research are taken from four ancillary Indian plastic manufacturing firms. Research findings indicate that collaborations and information exchange dimension indicators obtained the highest priority in improving SC performance. The model proposed is considered very useful for the SC managers/practitioners/decision-makers to understand better and distinguish the essential SC performance improvement indicators and to take systematic decisions specifically to improve the performance of business in a SC context. Sensitivity analysis was conducted to examine the priority ranking of the indicators.     

一类新的SBO及其在GM(1,1)中的应用研究

利用缓冲算子提高数据序列光滑性是提高灰色GM(1,1)模型预测精度的重要途径之一。在对缓冲算子和已有强化缓冲算子研究的基础上,构造了一类新的强化缓冲算子(strengthening buffer operator,SBO),有效地解决了冲击扰动数据序列在建模预测过程中常常出现的定量预测结果与定性分析结论不符的问题,实例分析结果表明:这类新的强化缓冲算子能显著提高数据预测模型的预测精度。     

多目标条件下企业碳配额分配和政府公平——基于(p,α)比例公平的视角

本文在企业和政府主从博弈框架下,研究政府兼顾社会福利和减排成本的多目标条件下企业最优碳配额分配方式,并采用（p,α）比例公平建立了最优分配与政府公平态度之间的对应关系,进一步分析企业间减排效率差异对碳配额最优分配以及政府所持公平态度的影响。采用遗传算法模拟结果显示,在政府最大化社会福利和最小化减排总成本的多目标下,政府始终给予高效率减排企业更多的配额,在企业间减排效率差异较小和较大的行业,减排效率对最优配额分配和政府所持公平态度的影响是完全不同的。当行业内企业减排效率差异较小时,随减排效率差异的增加,低效率企业所得配额逐渐减少,政府公平性逐渐降低;当企业减排效率差异较大时,情况刚好相反,低效率企业的配额逐渐增加,政府变得越来越注重公平。除此之外,政府公平性并不意味着低效率企业得到更多的碳配额,当企业间减排效率差异增加到某一区间,随减排效率差异的增加,低效率企业所得配额逐渐减小,而政府公平逐渐增加。我们的结论为相关部门多目标下的最优碳配额分配决策以及分析政府的公平性提供了有益参考。     

基于ECA规则的工作流时间约束分析

本文着重研究了工作流中各活动间的定量时序关系,提出了一种分析工作流中时间约束的方法。该方法针对基于ECA规则的工作流,通过建立及分析工作流的约束图,对工作流中活动间定量时序约束的一致性进行了分析,从而保证了工作流的正常运行。     

Farmer Knowledge and Risk Analysis: Postrelease Evaluation of Herbicide-Tolerant Canola in Western Canada

The global controversy regarding the use of genetically modified (GM) crops has proved to be a challenge for "science-based" risk assessments. Although risk analysis incorporates societal perspectives in decision making over these crops, it is largely predicated on contrasts between "expert" and "lay" perspectives. The overall objective of this study is to explore the role for farmers' knowledge, and their decade-long experience with herbicide-tolerant (HT) canola, in the risk analysis of GM crops. From 2002 to 2003, data were collected using interviews ( n = 15) and mail surveys ( n = 370) with farmers from Manitoba and across Canada. The main benefits associated with HT canola were management oriented and included easier weed control, herbicide rotation, and better weed control, whereas the main risks were more diverse and included market harm, technology use agreements (TUAs), and increased seed costs. Benefits and risks were inversely related, and the salient factor influencing risk was farmer experiences with HT canola volunteers, followed by small farm size and duration using HT canola. These HT volunteers were reported by 38% of farmers, from both internal (e.g., seedbank, farm machinery, etc.) and external (e.g., wind, seed contamination, etc.) sources, and were found to persist over time. Farmer knowledge is a reliable and rich source of information regarding the efficacy of HT crops, demonstrating that individual experiences are important to risk perception. The socioeconomic nature of most risks combined with the continuing "farm income crisis" in North America demonstrates the need for a more holistic and inclusive approach to risk assessment associated with HT crops and, indeed, with all new agricultural technology.     

我国外汇市场与股票市场间波动溢出效应实证研究——基于小波多分辨的多元BEKK-GARCH(1,1)模型分析

汇率机制和股权分置改革加强了我国汇市与股市一体化程度, 近期人民币升值压力不断演化和几大经济危机爆发进一步增强了两个市场间的关联性。本文采用小波多分辨分析与多元BEKK-GARCH(1, 1)模型相结合方式研究了国内汇市与股市之间的波动溢出关系, 实证结果不仅表明两大市场存在显著的波动溢出效应, 还发现在不同交易周期下存在着不同的波动溢出效应, 短期来看股市向汇市有单向传递效应, 随周期变长发展为双向溢出, 其中又以汇市向股市波动溢出效应更为显著, 长期则仅有小幅度溢出效应存在于股市向汇市波动传递过程中。     

中国风电固定上网电价政策的实物期权理论与实证分析

本文使用实物期权方法研究中国目前实施的风电固定上网电价政策。首先说明风电项目投资的实物期权原理,并建立风电固定上网电价政策实物期权模型。然后,从理论上证明了风电最优投资电价与上网电价波动率成正比(固定上网电价理论依据,即政府为了最大限度激励投资者,使得上网电价波动率等于0);最优投资电价与上网电价期望增长率成正比(固定上网电价调整理论依据)。最后,选取河北张北油篓沟元山子风电场工程项目进行实证分析,通过上网电价期望增长率调整的数值分析得到中国风电上网电价平均每年降低幅度应该为1%左右。本文为我国可再生能源电价调整提供参考。     

Probability and Possibility‐Based Representations of Uncertainty in Fault Tree Analysis

Expert knowledge is an important source of input to risk analysis. In practice, experts might be reluctant to characterize their knowledge and the related (epistemic) uncertainty using precise probabilities. The theory of possibility allows for imprecision in probability assignments. The associated possibilistic representation of epistemic uncertainty can be combined with, and transformed into, a probabilistic representation; in this article, we show this with reference to a simple fault tree analysis. We apply an integrated (hybrid) probabilistic‐possibilistic computational framework for the joint propagation of the epistemic uncertainty on the values of the (limiting relative frequency) probabilities of the basic events of the fault tree, and we use possibility‐probability (probability‐possibility) transformations for propagating the epistemic uncertainty within purely probabilistic and possibilistic settings. The results of the different approaches (hybrid, probabilistic, and possibilistic) are compared with respect to the representation of uncertainty about the top event (limiting relative frequency) probability. Both the rationale underpinning the approaches and the computational efforts they require are critically examined. We conclude that the approaches relevant in a given setting depend on the purpose of the risk analysis, and that further research is required to make the possibilistic approaches operational in a risk analysis context.     

Risk Analysis, Life Cycle Assessment—The Common Challenge of Dealing with the Precautionary Frame (Based on the Toxicity Controversy in Sweden and the Netherlands)

Life cycle impact assessment (LCIA) and comparative risk assessment (RA) use the same building blocks for analyzing fate and potential effects of toxic substances. It is tacitly assumed that emission-effect calculations can give uniform and decisive answers in debates on toxicity problems. For several decades, mainstream policy sciences have taken a different starting point when analyzing decision making on complex, controversial societal issues. Such controversies in essence are thought to be caused by the fact that different actor coalitions adhere to a different, but in scientific terms equally reasonable, conceptualization or "framing" of the problem. A historical, argumentative analysis of the Dutch chlorine debate and the Swedish PVC debate shows that this is also true in the discussions on toxic substances. Three frames have been identified, which were coined the "risk assessment frame," "the strict control frame," and the "precautionary frame." These frames tacitly disagree about the extent of knowledge/ignorance about the impacts of substances, the robustness/fallibility of emission-reduction schemes, and the robustness/vulnerability of nature. The latter frame, adhered to by environmentalists, seeks to judge substances mainly on their inherent safety. Under the current institutional arrangements and practices, RA and LCIA are executed mainly in line with the philosophy expressed by the risk assessment frame. This article gives various suggestions for dealing with framing in debates on toxic substances. One of the options is elaborated in somewhat more detail, i.e., the development of multiple indicators and calculation schemes for RA and LCIA that reflect the different frames. An outline is given for a possible indicator system reflecting the precautionary principle.