A dynamic Bayesian network-based emergency decision-making framework highlighting emergency propagations: Illustrated using the Fukushima nuclear accidents and the Covid-19 pandemic

When facing public emergencies, human societies need to make decisions rapidly in order to mitigate the problems. However, this process can be difficult due to complexity of the emergency scenarios and lack of systematic methods for analyzing them. In the work reported here, we develop a framework based upon dynamic Bayesian networks in order to simulate emergency scenarios and support corresponding decisions. In this framework, we highlight the importance of emergency propagation, which is a critical factor often ignored by decisionmakers. We illustrate that failure of considering emergency propagation can lead to suboptimal mitigation strategies. By incorporating this critical factor, our framework enables decisionmakers to identify optimal response strategies minimizing emergency impacts. Scenarios developed from two public emergencies: the 2011 Fukushima nuclear power plant accidents and the Covid-19 pandemic, are utilized to illustrate the framework in this paper. Capabilities of the framework in supporting decision making in both events illustrate its generality and adaptability when dealing with complex real-world situations. Our analysis results reveal many similarities between these two seemingly distinct events. This indicates that seemingly unrelated emergencies can share many common features beyond their idiosyncratic characteristics. Valuable mitigation insights can be obtained by analyzing a broad range of past emergencies systematically.     

Physical–cyber–human framework-based resilience evaluation toward urban power system: Case study from China

Because the increased frequency, intensity, and duration of extreme weather events have significantly challenged power systems, there has been an increased interest in resilient power systems. This article establishes a multicriteria resilience evaluation framework for urban power systems from a physical–cyber–human system perspective, in which the two principal elements responsible for power system function degradation are described, the three major domains comprising urban power systems are explained, four core capacities that positively contribute to power system resilience are proposed, and 15 (11 objective and four subjective) power system resilience evaluation indicators are identified. Fuzzy hesitant judgment and a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) aggregation method are employed to minimize the expert divergence and maximize the group consensus. A validation method is designed and a comparison with commonly applied performance-based and attributes-based evaluation methods is conducted. The applicability of the evaluation framework is verified using data from four Chinese municipalities: Shanghai, Beijing, Chongqing, and Tianjin. It was found that Shanghai's resilience was the best, and Chongqing's physical resistance disadvantages would result in the greatest difficulties in coping with extreme event disturbances. Physical, cyber, and human domain resilience enhancement strategies are given for different cities separately. This study provides a practical tool to evaluate, compare, and enhance power system resilience for governments and public utilities.     

A framework for supporting health capability-based planning: Identifying and structuring health capabilities

The COVID-19 pandemic has highlighted that health security systems must be redesigned, in a way that they are better prepared and ready to cope with multiple and diverse health threats, from predictable and well-known epidemics to unexpected and challenging pandemics. A powerful way of accomplishing this goal is to focus the planning on health capabilities. This focus may enhance the ability to respond to and recover from health threats and emergencies, while helping to identify the level of resources required to maintain and build up those capabilities that are critical in ensuring the preparedness of health security systems. However, current attempts for defining and organizing health capabilities have some important limitations. First, such attempts were not designed to consider diverse scenarios and multiple health threats. Second, they provide a limited representation of capabilities and lack a systemic perspective. Third, they struggle to identify capability and resource gaps. In this article, we thus propose a new framework for identifying and structuring health capabilities and support health capability planning. The suggested framework has three main potential benefits. First, the framework may help policymakers in planning under high levels of uncertainty, by considering multiple realistic and stressful scenarios. Second, it can provide risk analysts with a more comprehensive representation of health capabilities and their complex relationships. Third, it can support planners in identifying resource and capability gaps. We illustrate the use of the framework in practice considering an outbreak scenario caused by three different health threats (COVID-19, Ebola, and Influenza viruses).     

The complementary effects of rationality and intuition on strategic decision quality

Rationality and intuition are important dimensions of the strategic decision process. Prior studies have viewed these as distinct dimensions, providing limited insights for our understanding of strategic decision processes. Drawing on the dual process theory and research on process capability, this study examines the interplay between rationality and intuition based on a sample of 103 strategic decisions made by service firms in Greece. The results suggest that combining rationality and intuition at the same time leads to successful strategic decisions. Also, the moderating role of environmental dynamism was investigated. We found that in dynamic settings, decision-making teams which combine rationality and intuition outperform teams which use rationality or intuition separately. The implications of these findings for theory and practice are important and are analysed in the paper.     

Managing value appropriation in buyer–supplier relationships: The role of commercial decision resources

The resource-based view explains firms’ value appropriation in buyer–supplier relationships by pointing to sustained differences in economic efficiency across firms. Firms with more efficient resources create more value than competitors, which in turn provides a “protective cushion” against competition. However, just as firms may differ in the economic efficiency of their resources and in the value they create, they may also differ in their information processing and how successful they are at value appropriation. Building on the literature on decision-making under uncertainty in psychology, I argue that firms may increase their value appropriation in exchange relationships by investing in commercial decision resources that allow for more effective information processing in commercial decisions. Examples of commercial decision resources include IT-based systems for product costing and tracking customers/competitors, the design of commercial organization, control systems, and commercial experience and skill.     

决策应用软件开发平台Smart Decision研制——国家杰出青年科学基金项目回溯

国家自然科学基金委员会国家杰出青年科学基金项目“网络环境下群体智能决策支持系统生成器研究与开发”是2002年1月立项,于2005年12月完成的。通过对项目研究理论思想和创新性的分析,全面介绍了项目研究工作的特色、研究内容和进展,特别介绍了项目的创新性研究成果,并对项目的学术价值、成果应用及学术交流进行了阐述。     

Moral Utility Theory: Understanding the motivation to behave (un)ethically

Moral Utility Theory provides an integrative framework for understanding the motivational basis of ethical decision making by modeling it as a process of subjective expected utility (SEU) maximization. The SEUs of ethical and unethical behavioral options are proposed to be assessed intuitively during goal pursuit, with unethical conduct emerging when the expected benefits of moral transgressions outweigh the expected costs. A key insight of the model is that any factors that increase the value of a goal—including incentives, framings, and mindsets—can motivate misbehavior by increasing the SEU of unethical conduct. Although Moral Utility Theory emphasizes the automatic and habitual nature of most SEU appraisals, it also describes a mechanism for initiating the deliberative moral reasoning process: the experience of moral uncertainty. Moral uncertainty is proposed to occur when the SEUs of ethical and unethical behaviors are similar in magnitude, thereby activating the behavioral inhibition system and motivating the allocation of attentional resources toward the decision process. This framework bridges the gap between affective and cognitive perspectives on ethical decision making by identifying automatic evaluations as a central driver of moral decisions while also specifying when and how moral reasoning processes are initiated. By combining dual-process models of morality with well-validated principles from the science of motivation, Moral Utility Theory provides theoretical parsimony and formal modeling potential to the study of ethical decision making. The framework also suggests practical strategies—from employee selection and training to goal setting and compensation systems—for encouraging ethical behavior in organizations.     

产出随机及贸易信用下农产品供应链农户决策与政府补偿价值

针对由单一公司和受资金约束单一农户组成的农产品供应链中融资难问题,考虑政府补偿公司预付货款损失及农产品产出随机性,分别构建了贸易信用下农户有、无破产风险的供应链博弈模型,并对比分析农户最优决策,最后探讨了政府补偿对社会福利及供应链的价值创造。研究表明,灾害年投入产出率越小,农户有破产风险的供应链决策模式对农户越有利;政府补偿策略不仅可化解公司预付货款损失风险和创造更多社会福利,还能激励农户制定更合理生产投入量,并提升供应链效率,且在一定条件下还可达到集中决策下最优期望利润水平,为供应链创造更多价值。     

基于SOAR模型的网民群体负面情感建模研究

面向网络舆情演变过程中政府应急响应需求,本文基于SOAR （State,Operator and Result）模型,将网民作为智能体Agent,将网络舆情中网民群体行为转变过程看作相应舆情问题空间中状态随时间的连续转换过程,设计突发事件中网民群体负面情感SOAR Agent模型,包括网民Agent的工作记忆、长期记忆、决策过程、学习机制,构建网民群体行为转换规则库和相应算法。在此基础上,设计仿真实验,结合典型网络舆情事件案例,对政府不同应急措施下微博用户群体行为演变过程进行建模。实证结果表明,基于网民群体负面情感的建模,可以分析和预测在不同网络舆情阶段、不同政府应急响应措施下网民群体的行为决策规律。     

规避农副产品原材料产出不确定风险的商业保险策略

为了保证产品质量、降低生产成本,许多农副产品制造商选择自己种植原材料以满足农副产品的加工生产。然而,农作物的产出易受不利事件（如各种自然灾害）的影响而具有不确定性。这种不确定性可能导致最终产品产出不足,严重时甚至引发财务危机。为了应对潜在风险,农副产品制造商可向金融机构购买商业保险。本文建立了单周期农副产品制造商的计划产量决策模型,通过研究制造商购买商业保险的边界条件及最优商业保险策略,分析商业保险策略在制造商规避原材料产出不确定风险时所具有的价值。研究结果表明：（1）只有保费的安全因子低于外部融资的单位惩罚成本时,制造商才会购买商业保险;（2）最优商业保险策略与计划产量无关;（3）最终产品单位净收益越低,商业保险的价值反而越高。