Using scenarios to develop strategies

Scenarios were not used for strategic decision-making until some time after their introduction. Structured approaches which fully use scenarios for strategy development have only emerged in the last few years. This paper describes such an approach as practised in Shell Nederland and focuses on the business environment with reference to the norms and values. A second paper dealing with the values in more details will appear in the next issue.     

经济政策不确定性与股票风险特征

构建了包含经济政策不确定性的随机贴现模型,通过参数校准、静态比较等方法,探讨了不同政策不确定性下股票风险的动态特征.在此基础上,通过实证模拟分析政策不确定性影响股票风险的传导机制,并通过组合分析法检验政策不确定性在股票风险形成中的作用,以此验证该理论模型在中国的适用性.最后,运用面板数据回归模型对政策不确定性与股票风险的关系进行量化分析.结果表明:1)政策不确定性能够通过企业现金流、贴现因子和相关系数等途径提高股票风险,该效应在控制传统风险因子、企业异质性因素和外部环境因素后依然显著;2)具有非国有性质、较低盈利能力和低资产增长率的企业股票更易受政策不确定性的影响;3)在经济萧条和改革幅度较大的阶段,政策不确定性对股票风险的溢出效应显著增强.     

需求不确定下的补偿策略理论模型

在需求不确定的前提条件下就供应商对销售商的补偿策略进行了深入研究,建立了包 含风险偏好的补偿策略理论模型. 在该理论模型的基础上,运用数值分析的手段分析了风险偏 好对供应链中参与者决策行为的影响,为供应链决策者制定合理的决策提供了科学依据. 最 后,结合我国国情,重点讨论如何在我国正确实施补偿策略.     

从神经经济学和神经营销学到神经管理学

神经科学是20世纪最重要的科学之一,随着脑成像和脑电测量技术的日益成熟,近年来在心理学、社会学、经济学、管理学等领域的应用与交叉融合取得了重要的发展.本文介绍了21世纪出现在经济与管理领域中的两个重要的、与神经科学交叉发展的学科:神经经济学和神经营销学.从它们的发展以及最新的研究成果来看,两者虽然同采用神经科学方法,都是研究个体行为的脑活动,却受各自学科研究方法的影响,表现出较大的差异.进而,本文分析了神经科学引入管理科学的可行途径,提出了神经管理学的概念及其主要的可能发展的方面,提出神经科学对管理科学的交叉,其将引起管理科学的革命性的发展,开创新的广阔的研究领域.     

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.     

现货供应不确定下的优化采购策略研究

在现货市场和传统契约市场共存时,研究了现货供应的不确定性和销售商的风险规避态度对于销售商的采购策略的影响。首先,在现货供应充足和供应不确定两种情况下分析了实现供应链协调的最优订购量和退货价格,以及销售商的风险规避态度对于订购量的影响.然后,通过数值计算进行了分析和验证.结果表明,现货供应充足时的订购量总是低于现货供应不确定时的订购量;但现货供应充足时供应链的期望利润高于现货供应不确定的情况.现货市场存在下,风险厌恶因子对订购量的影响趋势与单纯契约市场下正好相反.     

Cases of real-life policies related to risk: How can they enhance risk analysis and risk science?

Policies on risk constitute a core topic of risk analysis and risk science, and it is common at risk conferences to present real-life cases of such policies, for example related to the handling of climate change and pandemics. Although these are of broad interest, showing how important issues in society are dealt with, it can be questioned to what extent and how these cases contribute to enhancing risk analysis and risk science. The present paper addresses this concern. It is argued that, in order to learn from the cases, they need in general to be more thoroughly followed up with discussions of concepts, principles, approaches, and methods for assessing, characterizing, communicating and handling risk. Describing a governmental policy on, for example, the handling of COVID-19 is a point of departure for interesting discussions concerning its justification and performance, in particular in relation to risk and the most updated knowledge from the risk analysis field. Such discussions are, however, often lacking. The paper points to some key obstacles and challenges for the learning process, including the difficulty of distinguishing between policies, policy analysis, and politics.     

可持续发展管理:从指标体系到政策

本文提出可持续发展指标与政策的构成基础,强调对可持续发展管理来说,政策比指标更为需要。     

Artifactual Uncertainty in Risk Analysis

The field of comparative risk analysis of electrical energy alternatives has traditionally been plagued by highly uncertain estimates of risk rates, and consequently by conflicting judgements of relative risk. To the extent that this uncertainty arises from traditional sources–imperfect observations or actual variance in the data–it can be brought within a Bayesian statistical framework which allows policy conclusions to be formulted and tested at different levels of confidence. It is shown that there are important methodological or "artifactual" sources of uncertainty, however, that cannot be treated by statistical means; these require conceptual advances for their resolution. By identifying these sources of uncertainty in simple thought experiments and examples, it is shown in what ways the concept of attributable risk, which is the policy-maker's chief concern, must be sharpened and refined to have unambiguous meaning. The conventional "multilinear" formula for calculating risk indices is challenged as a measure of attributable risk, and directions for further research to improve the methodological foundations of comparative risk analysis are identified.     

Equity in Social Risk: Some Empirical Observations

In societal risk analysis the equity of the distribution of risks is often an important consideration owing to the special nature of health risks. We empirically validate some assumptions about equity that have been discussed in the decision analytic literature. Our results show that the way fatalities are distributed throughout a society is considered along with the number of fatalities in evaluating alternative policies involving mortality risks. The concepts of ex ante equity and ex post equity are both shown to be important in judgments of fairness. We next present a decision model based on multiattribute preference theory incorporating the number of fatalities, as well as ex ante equity and ex post equity. When ex ante equity and ex post equity are positively weighted in this fair-risk model , options with more equal risk distributions are ranked higher. Next we empirically show that the distribution of benefits has an impact on judgments of fairness. The fair-risk model does not include information on the benefits distribution, so it would apply when benefits are distributed equally or when the decision maker wishes to not include benefits in the model. We briefly discuss how the notion of proportional equity can incorporate benefits into judgments of the fairness of risk distributions. We then include benefits in a more general model in which fair risk-benefit combinations are those that are exchange equitable. A key implication of this envy-free risk–benefit model is that an unequal distribution of risks may be preferred if it is accompanied by a compensatory differential in benefits consistent with peoples' preference tradeoffs between received benefits and assumed risks. Finally, we discuss how perceived deservedness may influence judgments about equity. We conclude with a discussion of the implications of research on alternative notions of equity for policy makers dealing with social risks.     

On doing better science: From thrill of discovery to policy implications

In this position paper, I argue that the main purpose of research is to discover and report on phenomena in a truthful manner. Once uncovered, these phenomena can have important implications for society. The utility of research depends on whether it makes a contribution because it is original or can add to cumulative research efforts, is rigorously and reliably done, and is able to inform basic or applied research and later policy. However, five serious “diseases” stifle the production of useful research. These diseases include: significosis, an inordinate focus on statistically significant results; neophilia, an excessive appreciation for novelty; theorrhea, a mania for new theory; arigorium, a deficiency of rigor in theoretical and empirical work; and finally, disjunctivitis, a proclivity to produce large quantities of redundant, trivial, and incoherent works. I surmise that these diseases have caused immense harm to science and have cast doubt on the role of science in society. I discuss what publication gatekeepers should do to eradicate these diseases, to stimulate the undertaking of more useful and impactful research, and to provide the needed incentives to better align the interests of researchers with those of the greater good. Finally, I highlight where technical improvements are needed to enhance research quality, and call on deeper reflection, transparency, and honesty in how we do research.     

How Much Uncertainty is Too Much and How Do We Know? A Case Example of the Assessment of Ozone Monitor Network Options

Limited time and resources usually characterize environmental decision making at policy organizations such as the U.S. Environmental Protection Agency. In these climates, addressing uncertainty, usually considered a flaw in scientific analyses, is often avoided. However, ignoring uncertainties can result in unpleasant policy surprises. Furthermore, it is important for decisionmakers to know how defensible a chosen policy option is over other options when the uncertainties of the data are considered. The purpose of this article is to suggest an approach that is unique from other approaches in that it considers uncertainty in two specific ways-the uncertainty of stakeholder values within a particular decision context and data uncertainty in the light of the decision-contextual data-values relationship. It is the premise of this article that the interaction between data and stakeholder values is critical to how the decision options are viewed and determines the effect of data uncertainty on the relative acceptability of the decision options, making the understanding of this interaction important to decisionmakers and other stakeholders. This approach utilizes the recently developed decision analysis framework and process, multi-criteria integrated resource assessment (MIRA). This article will specifically address how MIRA can be used to help decisionmakers better understand the importance of uncertainty on the specific (i.e., decision contextual) environmental policy options that they are deliberating.     

Dynamic Blowout Risk Analysis Using Loss Functions

Most risk analysis approaches are static; failing to capture evolving conditions. Blowout, the most feared accident during a drilling operation, is a complex and dynamic event. The traditional risk analysis methods are useful in the early design stage of drilling operation while falling short during evolving operational decision making. A new dynamic risk analysis approach is presented to capture evolving situations through dynamic probability and consequence models. The dynamic consequence models, the focus of this study, are developed in terms of loss functions. These models are subsequently integrated with the probability to estimate operational risk, providing a real‐time risk analysis. The real‐time evolving situation is considered dependent on the changing bottom‐hole pressure as drilling progresses. The application of the methodology and models are demonstrated with a case study of an offshore drilling operation evolving to a blowout.     

Domino Effect Analysis Using Bayesian Networks

A new methodology is introduced based on Bayesian network both to model domino effect propagation patterns and to estimate the domino effect probability at different levels. The flexible structure and the unique modeling techniques offered by Bayesian network make it possible to analyze domino effects through a probabilistic framework, considering synergistic effects, noisy probabilities, and common cause failures. Further, the uncertainties and the complex interactions among the domino effect components are captured using Bayesian network. The probabilities of events are updated in the light of new information, and the most probable path of the domino effect is determined on the basis of the new data gathered. This study shows how probability updating helps to update the domino effect model either qualitatively or quantitatively. The methodology is applied to a hypothetical example and also to an earlier‐studied case study. These examples accentuate the effectiveness of Bayesian network in modeling domino effects in processing facility.     

Promoting Seismic Retrofit Implementation Through “Nudge”: Using Warranty as a Driver

This article proposes a new type of warranty policy that applies the “nudge” concept developed by Thaler and Sunstein to encourage homeowners in Japan to implement seismic retrofitting. Homeowner adaptation to natural disasters through loss reduction measures is known to be inadequate. To encourage proactive risk management, the “nudge” approach capitalizes on how choice architecture can influence human decision‐making tendencies. For example, people tend to place more value on a warranty for consumer goods than on actuarial value. This article proposes a “warranty for seismic retrofitting” as a “nudge” policy that gives homeowners the incentive to adopt loss reduction measures. Under such a contract, the government guarantees all repair costs in the event of earthquake damage to the house if the homeowner implements seismic retrofitting. To estimate the degree to which a warranty will increase the perceived value of seismic retrofitting, we use field survey data from 1,200 homeowners. Our results show that a warranty increases the perceived value of seismic retrofitting by an average of 33%, and an approximate cost‐benefit analysis indicates that such a warranty can be more economically efficient than an ex ante subsidy. Furthermore, we address the failure of the standard expected utility model to explain homeowners’ decisions based on warranty evaluation, and explore the significant influence of ambiguity aversion on the efficacy of seismic retrofitting and nonanalytical factors such as feelings or trust.     

Elusive Critical Elements of Transformative Risk Assessment Practice and Interpretation: Is Alternatives Analysis the Next Step?

This article argues that “game‐changing” approaches to risk analysis must focus on “democratizing” risk analysis in the same way that information technologies have democratized access to, and production of, knowledge. This argument is motivated by the author's reading of Goble and Bier's analysis, “Risk Assessment Can Be a Game‐Changing Information Technology—But Too Often It Isn't” (Risk Analysis, 2013; 33: 1942–1951), in which living risk assessments are shown to be “game changing” in probabilistic risk analysis. In this author's opinion, Goble and Bier's article focuses on living risk assessment's potential for transforming risk analysis from the perspective of risk professionals—yet, the game‐changing nature of information technologies has typically achieved a much broader reach. Specifically, information technologies change who has access to, and who can produce, information. From this perspective, the author argues that risk assessment is not a game‐changing technology in the same way as the printing press or the Internet because transformative information technologies reduce the cost of production of, and access to, privileged knowledge bases. The author argues that risk analysis does not reduce these costs. The author applies Goble and Bier's metaphor to the chemical risk analysis context, and in doing so proposes key features that transformative risk analysis technology should possess. The author also discusses the challenges and opportunities facing risk analysis in this context. These key features include: clarity in information structure and problem representation, economical information dissemination, increased transparency to nonspecialists, democratized manufacture and transmission of knowledge, and democratic ownership, control, and interpretation of knowledge. The chemical safety decision‐making context illustrates the impact of changing the way information is produced and accessed in the risk context. Ultimately, the author concludes that although new chemical safety regulations do transform access to risk information, they do not transform the costs of producing this information—rather, they change the bearer of these costs. The need for further risk assessment transformation continues to motivate new practical and theoretical developments in risk analysis and management.     

Using Probabilistic Terrorism Risk Modeling for Regulatory Benefit-Cost Analysis: Application to the Western Hemisphere Travel Initiative in the Land Environment

This article presents a framework for using probabilistic terrorism risk modeling in regulatory analysis. We demonstrate the framework with an example application involving a regulation under consideration, the Western Hemisphere Travel Initiative for the Land Environment, (WHTI‐L). First, we estimate annualized loss from terrorist attacks with the Risk Management Solutions (RMS) Probabilistic Terrorism Model. We then estimate the critical risk reduction, which is the risk‐reducing effectiveness of WHTI‐L needed for its benefit, in terms of reduced terrorism loss in the United States, to exceed its cost. Our analysis indicates that the critical risk reduction depends strongly not only on uncertainties in the terrorism risk level, but also on uncertainty in the cost of regulation and how casualties are monetized. For a terrorism risk level based on the RMS standard risk estimate, the baseline regulatory cost estimate for WHTI‐L, and a range of casualty cost estimates based on the willingness‐to‐pay approach, our estimate for the expected annualized loss from terrorism ranges from $2.7 billion to $5.2 billion. For this range in annualized loss, the critical risk reduction for WHTI‐L ranges from 7% to 13%. Basing results on a lower risk level that results in halving the annualized terrorism loss would double the critical risk reduction (14–26%), and basing the results on a higher risk level that results in a doubling of the annualized terrorism loss would cut the critical risk reduction in half (3.5–6.6%). Ideally, decisions about terrorism security regulations and policies would be informed by true benefit‐cost analyses in which the estimated benefits are compared to costs. Such analyses for terrorism security efforts face substantial impediments stemming from the great uncertainty in the terrorist threat and the very low recurrence interval for large attacks. Several approaches can be used to estimate how a terrorism security program or regulation reduces the distribution of risks it is intended to manage. But, continued research to develop additional tools and data is necessary to support application of these approaches. These include refinement of models and simulations, engagement of subject matter experts, implementation of program evaluation, and estimating the costs of casualties from terrorism events.