Ordinal utility models of decision making under uncertainty

This paper studies two models of rational behavior under uncertainty whose predictions are invariant under ordinal transformations of utility. The quantile utility model assumes that the agent maximizes some quantile of the distribution of utility. The utility mass model assumes maximization of the probability of obtaining an outcome whose utility is higher than some fixed critical value. Both models satisfy weak stochastic dominance. Lexicographic refinements satisfy strong dominance.The study of these utility models suggests a significant generalization of traditional ideas of riskiness and risk preference. We define one action to be riskier than another if the utility distribution of the latter crosses that of the former from below. The single crossing property is equivalent to a minmax spread of a random variable. With relative risk defined by the single crossing criterion, the risk preference of a quantile utility maximizer increases with the utility distribution quantile that he maximizes. The risk preference of a utility mass maximizer increases with his critical utility value.     

Priority Setting for the Distribution of Localized Hazard Protection

We address the problem of distributing safety-enhancing devices across a region, where each identical device provides for only local protection of the population. The devices protect nonidentical sectors of the population. The sectors of population are exposed to nonidentical intensities of hazard. A method for the screening and prioritizing of needs for the protective devices is described. An approach of risk-benefit-cost analysis under uncertainty is recommended as follows. Measures of hazard intensity and population exposure are identified. Exogenous parameters that influence assessments of risks, benefits, and costs are identified. Uncertainties of the exogenous parameters are propagated by interval analysis. Several tiers of the plausibility of need for protection are identified. The tiers are useful in setting priorities for the distribution of the safety devices. The method is demonstrated in an engineering application to roadway lighting, but has implications for disaster preparedness, anti-terrorism, transportation safety, and other arenas of public safety.     

基于σ/ Q 的库存控制中安全库存的优选策略

研究了单项目库存控制问题中的安全库存选择策略,评论了安全库存的决定要素,讨论 了基于以上要素的成本构成。进一步讨论了安全库存策略在理论和实践应用中的矛盾,提出 了一种实践中容易操作的安全库存的直观求解方法,以利于管理者实际运用,有效克服运作环 境的不确定性     

Treatment Choice With Trial Data: Statistical Decision Theory Should Supplant Hypothesis Testing

Abstract

A central objective of empirical research on treatment response is to inform treatment choice. Unfortunately, researchers commonly use concepts of statistical inference whose foundations are distant from the problem of treatment choice. It has been particularly common to use hypothesis tests to compare treatments. Wald’s development of statistical decision theory provides a coherent frequentist framework for use of sample data on treatment response to make treatment decisions. A body of recent research applies statistical decision theory to characterize uniformly satisfactory treatment choices, in the sense of maximum loss relative to optimal decisions (also known as maximum regret). This article describes the basic ideas and findings, which provide an appealing practical alternative to use of hypothesis tests. For simplicity, the article focuses on medical treatment with evidence from classical randomized clinical trials. The ideas apply generally, encompassing use of observational data and treatment choice in nonmedical contexts.     

Community Resilience and Decision Theory Challenges for Catastrophic Events

Extreme and catastrophic events pose challenges for normative models of risk management decision making. They invite development of new methods and principles to complement existing normative decision and risk analysis. Because such events are rare, it is difficult to learn about them from experience. They can prompt both too little concern before the fact, and too much after. Emotionally charged and vivid outcomes promote probability neglect and distort risk perceptions. Aversion to acting on uncertain probabilities saps precautionary action; moral hazard distorts incentives to take care; imperfect learning and social adaptation (e.g., herd‐following, group‐think) complicate forecasting and coordination of individual behaviors and undermine prediction, preparation, and insurance of catastrophic events. Such difficulties raise substantial challenges for normative decision theories prescribing how catastrophe risks should be managed. This article summarizes challenges for catastrophic hazards with uncertain or unpredictable frequencies and severities, hard‐to‐envision and incompletely described decision alternatives and consequences, and individual responses that influence each other. Conceptual models and examples clarify where and why new methods are needed to complement traditional normative decision theories for individuals and groups. For example, prospective and retrospective preferences for risk management alternatives may conflict; procedures for combining individual beliefs or preferences can produce collective decisions that no one favors; and individual choices or behaviors in preparing for possible disasters may have no equilibrium. Recent ideas for building “disaster‐resilient” communities can complement traditional normative decision theories, helping to meet the practical need for better ways to manage risks of extreme and catastrophic events.     

The arithmetic of outcome editing in financial and social domains

Outcome editing refers to a set of mental rules that people apply when deciding whether to evaluate multiple outcomes jointly or separately, which subsequently affects choice. In a large-scale online survey (n = 2062) we investigate whether individuals use the same outcome editing rules for financial outcomes (e.g., a lottery win) and social outcomes (e.g., a party with friends). We also test the role of numeric ability in explaining outcome editing. Our results show that people’s preferences for combining or separating events depend on whether those events are in the financial or the social domain. Specifically, individuals were more likely to segregate social outcomes than monetary outcomes, except for when all outcomes were negative. Moreover, numeric ability was associated with preferences for outcome editing in the financial domain but not in the social domain. Our findings extend the understanding of the arithmetic operations underlying outcome editing and suggest that people rely more on calculations when making choices involving multiple financial outcomes and more on feelings when making choices involving social outcomes.     

Defender–Attacker Decision Tree Analysis to Combat Terrorism

We propose a methodology, called defender–attacker decision tree analysis, to evaluate defensive actions against terrorist attacks in a dynamic and hostile environment. Like most game‐theoretic formulations of this problem, we assume that the defenders act rationally by maximizing their expected utility or minimizing their expected costs. However, we do not assume that attackers maximize their expected utilities. Instead, we encode the defender's limited knowledge about the attacker's motivations and capabilities as a conditional probability distribution over the attacker's decisions. We apply this methodology to the problem of defending against possible terrorist attacks on commercial airplanes, using one of three weapons: infrared‐guided MANPADS (man‐portable air defense systems), laser‐guided MANPADS, or visually targeted RPGs (rocket propelled grenades). We also evaluate three countermeasures against these weapons: DIRCMs (directional infrared countermeasures), perimeter control around the airport, and hardening airplanes. The model includes deterrence effects, the effectiveness of the countermeasures, and the substitution of weapons and targets once a specific countermeasure is selected. It also includes a second stage of defensive decisions after an attack occurs. Key findings are: (1) due to the high cost of the countermeasures, not implementing countermeasures is the preferred defensive alternative for a large range of parameters; (2) if the probability of an attack and the associated consequences are large, a combination of DIRCMs and ground perimeter control are preferred over any single countermeasure.     

基于RFID技术的双供应链投资决策研究

本文考虑零售商主导的分别由一个供应商和一个零售商组成的两条竞争型供应链中,当两个供应商都未投资RFID技术、只有一个供应商投资RFID技术以及两个供应商同时投资RFID技术时,考虑供应商成本结构的差异,对比分析供应链的投资决策。由于模型解析解过于复杂,本文通过算例分析,着重考虑产品的替代率、RFID标签价格以及库存可获得率三个因素对供应链成员利润的影响。结果表明两条供应链对RFID技术的投资决策会因成本结构和产品替代率的不同而发生变化,其中在两个供应商生产成本差异较大且产品竞争强度较低时,生产成本较高的供应商更愿意投资RFID技术,而生产成本较低的供应商不愿意投资RFID技术,两个零售商则希望使用RFID技术,所以此时仅会有一条供应链上的成员达成一致,决定投资使用RFID技术。     

Step-wise group screening designs with errors in observations

The performance of step-wise group screening In terms of the expected number of runs and the expected number of incorrect decisions, Is considered. A method for obtaining optimal step-wise designs Is presented, for the cases in which the direction of each defective factor is assumed to be known a-priori and the observations are subject to error.     

A robustness framework for monitoring real options under uncertainty

This paper presents a problem structuring methodology to assess real option decisions in the face of unpredictability. Based on principles of robustness analysis and scenario planning, we demonstrate how decision-aiding can facilitate participation in projects setting and achieve effective decision making through the use of real options reasoning. We argue that robustness heuristics developed in earlier studies can be practical proxies for real options performance, hence indicators of efficient flexible planning. The developed framework also highlights how to integrate real options solutions in firms’ strategic plans and operating actions. The use of the methodology in a location decision application is provided for illustration.