Statistical Treatment Rules for Heterogeneous Populations

An important objective of empirical research on treatment response is to provide decision makers with information useful in choosing treatments. This paper studies minimax‐regret treatment choice using the sample data generated by a classical randomized experiment. Consider a utilitarian social planner who must choose among the feasible statistical treatment rules, these being functions that map the sample data and observed covariates of population members into a treatment allocation. If the planner knew the population distribution of treatment response, the optimal treatment rule would maximize mean welfare conditional on all observed covariates. The appropriate use of covariate information is a more subtle matter when only sample data on treatment response are available. I consider the class of conditional empirical success rules; that is, rules assigning persons to treatments that yield the best experimental outcomes conditional on alternative subsets of the observed covariates. I derive a closed‐form bound on the maximum regret of any such rule. Comparison of the bounds for rules that condition on smaller and larger subsets of the covariates yields sufficient sample sizes for productive use of covariate information. When the available sample size exceeds the sufficiency boundary, a planner can be certain that conditioning treatment choice on more covariates is preferable (in terms of minimax regret) to conditioning on fewer covariates.     

信用评分模型的设计与决策分析

本文对商业银行信贷业务中的贷款者的信用问题,运用决策分析提出了信用评分的设计原理及临界分值的确定方法,给出了最优贷款策略的期望收益和风险的计算公式。最后,以一例说明之。     

Facts and Values in Risk Analysis for Environmental Toxicants

The U.S. Office of Science and Technology Policy describes toxic substance regulation as composed of two stages. Stage I (facts) uses empirical data and scientific judgment to characterize human exposure and risk. Stage II (values) uses social and political judgment to decide regulatory action based on significance of the risk, benefits of the agent, and costs of its control. This paper argues that such a view represents an unrealistic and unattainable goal. We present examples showing how values enter virtually every part of risk analysis, and we review work on the vagaries in human judgment concerning both facts and values. These issues indicate that U.S. regulatory policy needs reconsideration.     

Cognitive and Motivational Biases in Decision and Risk Analysis

Behavioral decision research has demonstrated that judgments and decisions of ordinary people and experts are subject to numerous biases. Decision and risk analysis were designed to improve judgments and decisions and to overcome many of these biases. However, when eliciting model components and parameters from decisionmakers or experts, analysts often face the very biases they are trying to help overcome. When these inputs are biased they can seriously reduce the quality of the model and resulting analysis. Some of these biases are due to faulty cognitive processes; some are due to motivations for preferred analysis outcomes. This article identifies the cognitive and motivational biases that are relevant for decision and risk analysis because they can distort analysis inputs and are difficult to correct. We also review and provide guidance about the existing debiasing techniques to overcome these biases. In addition, we describe some biases that are less relevant because they can be corrected by using logic or decomposing the elicitation task. We conclude the article with an agenda for future research.     

Fundamental and technical methods of ethics

Consequentialists and deontologists alike tacitly presume that moral decisions should be reached from basic assessments of theoretically set moral value. The presumption they share, I argue, is seriously mistaken. We need to distinguish two general methods of reaching moral decisions, that of the moral fundamentalist and that of the moral technician. Moral fundamentalists and technicians differ in their methods, but not in their aims. The distinction between the two general methods of ethics is particularly important for consequentialism. I maintain that a consequentialist may be without inconsistency a utilitarian fundamentalist and a deontological technician. I suggest that when we pay heed to our epistemic constraints, we have strong consequentialist grounds for adopting this unusual position.     

The Value of Animal Test Information in Environmental Control Decisions

Value of information (VOI)analytic techniques are used to evaluate the benefit of performing animal bioassays to provide information about the cancer potency of specific chemical compounds. These tools allow the identification of the conditions in which the cost of reducing uncertainty about potency, by performing a subchronic or chronic bioassay, is justified by the benefit of having improved information for making control decisions. The decision analytic results are readily scaled to apply to a range of human contact rates (exposures)and a variety of control strategies. The sensitivity of results to uncertainty about animal to human extrapolation and the design of the bioassay is explored. An evaluation of the possible gains in general understanding about the mechanisms of carcinogenicity resulting from chronic bioassays is beyond the scope of this approach.     

Design and Analysis of Hospital Admission Control for Operational Effectiveness

Variability in hospital occupancy negatively impacts the cost and quality of patient care delivery through increased emergency department (ED) congestion, emergency blockages and diversions, elective cancelations, backlogs in ancillary services, overstaffing, and understaffing. Controlling inpatient admissions can effectively reduce variability in hospital occupancy to mitigate these problems. Currently there are two major gateways for admission to a hospital: the ED and scheduled elective admission. Unfortunately, in highly utilized hospitals, excessive wait times make the scheduled gateway undesirable or infeasible for a subset of patients and doctors. As a result, this group often uses the ED gateway as a means to gain admission to the hospital. To better serve these patients and improve overall hospital functioning, we propose creating a third gateway: an expedited patient care queue. We first characterize an optimal admission threshold policy using controls on the scheduled and expedited gateways for a new Markov decision process model. We then present a practical policy based on insight from the analytical model that yields reduced emergency blockages, cancelations, and off‐unit census via simulation based on historical hospital data.     

Risk-Based Objectives for the Allocation of Chemical, Biological, and Radiological Air Emissions Sensors

This article addresses the problem of allocating devices for localized hazard protection across a region. Each identical device provides only local protection, and the devices serve localities that are exposed to nonidentical intensities of hazard. A method for seeking the optimal allocation Policy Decisions is described, highlighting the potentially competing objectives of maximizing local risk reductions and coverage risk reductions. The metric for local risk reductions is the sum of the local economic risks avoided. The metric for coverage risk reductions is adapted from the p-median problem and equal to the sum of squares of the distances from all unserved localities to their closest associated served locality. Three graphical techniques for interpreting the Policy Decisions are presented. The three linked graphical techniques are applied serially. The first technique identifies Policy Decisions that are nearly Pareto optimal. The second identifies locations where sensor placements are most justified, based on a risk-cost-benefit analysis under uncertainty. The third displays the decision space for any particular policy decision. The method is illustrated in an application to chemical, biological, and/or radiological weapon sensor placement, but has implications for disaster preparedness, transportation safety, and other arenas of public safety.     

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.     

Statistical Evaluation of the New Zealand Food Safety Authority Sampling Protocol for Imported Food

The New Zealand Food Safety Authority sampling protocol for compliance inspection of imported food products is evaluated for its ability to provide consumer protection. The sampling protocol involves both partial testing of imported consignments and complete skipping inspection of consignments based on the quality history. The risk posed by the strategies of partial testing and skipping inspection of imports is evaluated using the average outgoing quality limit and other performance measures. The cost dimension of sampling inspection is also considered. Suggestions for improvement, which include tightening the skipping inspection parameters, are made.     

Decision Analysis for Utilizing Hazardous Waste Site Assessments in Real Estate Acquisition

When a buyer needs to purchase commercial or industrial property, the decision of what real estate to purchase should be based on an assessment of the total costs of acquisition. In addition to the direct purchase cost, other possible costs include hazardous waste site assessment studies and clean up costs if the purchased site proves to be contaminated. This paper presents a decision analysis model for determining when and which type of hazardous waste assessment tests should be conducted and how the test output affects the choice of site. The model assumes there are two types of hazardous waste assessment, an historical use review (phase 1 test)and soil and water sampling (phase 2 test). Model inputs include the cost, sensitivity and specificity for each type of test, a site's purchase price, and a priori probability of contamination, along with the clean-up cost for a contaminated site. The analysis uses the results of a data survey of 17 environmental engineering firms in setting values on the model input requirements. The paper also reports on sensitivity analysis with the model for the purpose of providing decision-makers with explicit protocols for test utilization.     

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.     

Of Disasters and Dragon Kings: A Statistical Analysis of Nuclear Power Incidents and Accidents

We perform a statistical study of risk in nuclear energy systems. This study provides and analyzes a data set that is twice the size of the previous best data set on nuclear incidents and accidents, comparing three measures of severity: the industry standard International Nuclear Event Scale, the Nuclear Accident Magnitude Scale of radiation release, and cost in U.S. dollars. The rate of nuclear accidents with cost above 20 MM 2013 USD, per reactor per year, has decreased from the 1970s until the present time. Along the way, the rate dropped significantly after Chernobyl (April 1986) and is expected to be roughly stable around a level of 0.003, suggesting an average of just over one event per year across the current global fleet. The distribution of costs appears to have changed following the Three Mile Island major accident (March 1979). The median cost became approximately 3.5 times smaller, but an extremely heavy tail emerged, being well described by a Pareto distribution with parameter α = 0.5–0.6. For instance, the cost of the two largest events, Chernobyl and Fukushima (March 2011), is equal to nearly five times the sum of the 173 other events. We also document a significant runaway disaster regime in both radiation release and cost data, which we associate with the “dragon‐king” phenomenon. Since the major accident at Fukushima (March 2011) occurred recently, we are unable to quantify an impact of the industry response to this disaster. Excluding such improvements, in terms of costs, our range of models suggests that there is presently a 50% chance that (i) a Fukushima event (or larger) occurs every 60–150 years, and (ii) that a Three Mile Island event (or larger) occurs every 10–20 years. Further—even assuming that it is no longer possible to suffer an event more costly than Chernobyl or Fukushima—the expected annual cost and its standard error bracket the cost of a new plant. This highlights the importance of improvements not only immediately following Fukushima, but also deeper improvements to effectively exclude the possibility of “dragon‐king” disasters. Finally, we find that the International Nuclear Event Scale (INES) is inconsistent in terms of both cost and radiation released. To be consistent with cost data, the Chernobyl and Fukushima disasters would need to have between an INES level of 10 and 11, rather than the maximum of 7.     

Neighbors in Time: Development and Use of Some Values for Intergenerational Justice from the Jewish and Christian Religious Traditions

The overlapping understandings of Jewish and Christian traditions (the Traditions), both influencing and reincorporating Western culture from the Greeks to the present, underpin many of the ethical constructs of present society, in ways both obvious and subtle. The concept of justice is central to the ethical outlooks of both religious traditions. This article systematically develops values related to justice from within the Traditions and extends them to the question of intergenerational equity as proposed precepts for assessment and action. Many of the results seem familiar because they are deeply embedded in our culture. They are assertions that transcend time-the value of human life; an obligation to support the necessary interests of others, especially the powerless; the concepts of brotherhood, the common good, and stewardship of resources; and the transmission of knowledge, resources, and values through the vehicles of families and communities. Other ideas from within the Traditions, such as giving beyond the requirements of equity and the connection of human life with God whose abilities are unbounded by time, continue to draw people beyond the limits of culture. These outlooks are organized into 17 statements or proposals constitutive of this view of justice. These summary statements are used as the basis for comparing a system of principles proposed by a panel of the National Academy of Public Administration for intergenerational decision making with the views represented by the Traditions. This broaches a broader question of fairness in resource distribution. The article concludes with reference to some developed resources of the Traditions from which further insight can be drawn, and another illustration related to resource allocation. It is hoped that the article helps stimulate wider analysis of the values on which our decisions are made.     

Tiered Chemical Testing: A Value of Information Approach

In December 2000 the EPA initiated the Voluntary Children's Chemical Evaluation Program (VCCEP) by asking manufacturers to voluntarily sponsor toxicological testing in a tiered process for 23 chemicals selected for the pilot phase. The tiered nature of the VCCEP pilot program creates the need for clearly defined criteria for determining when information is sufficient to assess the potential risks to children. This raises questions about how to determine the "adequacy" of the existing information and assess the need to undertake efforts to reduce uncertainty (through further testing). This article applies a value of information analysis approach to determine adequacy by modeling how toxicological and exposure data collected through the VCCEP may be used to inform risk management decisions. The analysis demonstrates the importance of information about the exposure level and control costs in making decisions regarding further toxicological testing. This article accounts for the cost of delaying control action and identifies the optimal testing strategy for a constrained decisionmaker who, absent applicable human data, cannot regulate without bioassay data on a specific chemical. It also quantifies the differences in optimal testing strategy for three decision criteria: maximizing societal net benefits, ensuring maximum exposure control while net benefits are positive (i.e., benefits outweigh costs), and controlling to the maximum extent technologically feasible while the lifetime risk of cancer exceeds a specific level of risk. Finally, this article shows the large differences that exist in net benefits between the three criteria for the range of exposure levels where the optimal actions differ.     

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 the Quality of Safety and Risk Analysis in the Chemical Industry

Safety and risk analyses have often been criticized as incomplete and inaccurate. This criticism, however, lacks a sound basis, since there has been little scientific evaluation of the methods developed for safety and risk analysis. The aim of this paper is to present a proposal for establishing measures—reliability, validity, and coverage—to be used in the evaluation of the scientific quality of the hazard identification and accident modeling phases in safety and risk analysis. The paper also presents four main principles for the evaluation of the scientific quality, and a theoretical framework to be used in evaluation. The framework is illustrated with practical examples taken from the chemical industry.     

GIS支持下的防汛指挥决策支持系统的系统分析与设计

防汛指挥决策支持系统是一项重要的综合性非工程防洪减灾措施,是实现防汛指挥决策科学化和现代化的重要手段。本文对防汛指挥决策支持系统进行了系统分析,论述了GIS在防汛指挥支持系统中的作用,在此基础上重点探讨了GIS支持下的防汛指挥决策支持系统的系统设计,包括数据库设计、模型库设计、系统集成等方面的内容。     

基于不确定条件下的供应商参与协同设计决策分析

以供应商参与协同设计所承担任务比例,作为其参与程度的定量指标,考虑研发不确定性,从供应商角度出发寻求其最适合的参与程度。研究结果表明,对于供应商而言,其参与受双方相对边际利润和开发能力,以及新产品市场不确定性的限制。供应商参与分担制造商部分设计任务有一个最适当的比例,该比例与其自身边际利润及技术开发能力正相关,与制造商边际利润以及技术开发能力负相关,与产品市场成功概率负相关。