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。     

大数据在重大行政决策中的应用及其法治化

大数据在重大行政决策领域的应用,属于技术理性与决策规则的有机融合。凭借信息来源与技术革新,大数据可赋予传统决策向数字化转型的新动能。大数据的应用贯穿于重大行政决策始终,在市场监管、环境保护等多类事项中所发挥的实践优势较为明显,能够推动决策的高效化、提升决策的精准度、增强决策机关之间的联动。然而,大数据应用可能会引发决策安全的隐忧、个人数据存在的空间被挤压以及决策失误的责任承担等难题。对前述问题提出对策的过程,实乃数据治理向治理数据的转变,此阶段不能欠缺法律法规的引导,应尝试从决策数据安全体系的法治保障、个人数据的法律保护、决策责任追究机制的科学建构等层面去推动大数据应用的法治化。     

Driven by politics: agenda setting and policy-making in Hungary 2010–2014

Studies on media and politics generally find an effect of the media on the symbolic policy agenda. Analysing data from the Hungarian Comparative Agendas Project, we demonstrate that this effect is extremely weak in the Hungarian policy-making process. We identified those issues that received greater than average coverage in the media. However, we found that in the majority of cases governmental initiatives or decisions preceded the media coverage – that is, instead of the media agenda pulling the policy agenda, the general logic is the opposite: the media are talking about the policy initiatives of the government. The ambition of the paper is twofold. First, our findings reinforce those claims in the literature that point to the many institutional and political factors affecting the media-politics nexus. This suggests that policy-making might be very different in new(er) democracies. Second, our research analyses the policy-making side of Viktor Orbán’s governance. Changes in the polity, democratic backlash and illiberal tendencies are usually the focus concerning the political changes in Hungary since 2010, but no attention has been devoted to how this type of governance is reflected in policy-making. Our paper seeks to make a contribution also in this respect.