政府干预下突发事件舆情传播规律与控制决策

通过对突发事件背景下的舆情传播进行多案例研究,界定了群众类型和政府干预作用,并分析了各类群众间的状态转移关系.然后,通过借鉴SEIR传染病模型的构造思路,结合舆情传播的实际特点,建立了政府干预下的舆情传播控制系统,进而运用平均场方法给出了系统的微分方程组模型.进一步,通过研究模型的平衡点和稳定性,得到了政府所应选择的管控方向,并以2011年东日本大地震事件中的舆情传播为例进行了验证.最后,基于该案例,通过设计多个情景,考查了政府的不同应急决策关注点对群众行为的影响,给出了应急方案的制定策略.     

Experimental Evidence Against the Paradigm of Mortality Risk Aversion

This article deals with the question of how societal impacts of fatal accidents can be integrated into the management of natural or man‐made hazards. Today, many governmental agencies give additional weight to the number of potential fatalities in their risk assessments to reflect society's aversion to large accidents. Although mortality risk aversion has been proposed in numerous risk management guidelines, there has been no evidence that lay people want public decisionmakers to overweight infrequent accidents of large societal consequences against more frequent ones of smaller societal consequences. Furthermore, it is not known whether public decisionmakers actually do such overweighting when they decide upon the mitigation of natural or technical hazards. In this article, we report on two experimental tasks that required participants to evaluate negative prospects involving 1–100 potential fatalities. Our results show that neither lay people nor hazard experts exhibit risk‐averse behavior in decisions on mortality risks.     

突发公共事件应急信息系统框架与功能

突发公共事件信息具有海量、分散、多样和复杂等特性。现代化管理信息系统的信息采集、存储、分析和管理功能可以提高突发公共事件的处理效率和决策水平。本文探讨了国内外基于数据挖掘和智能知识的突发公共事件信息管理研究情况及如何建立一个系统的公共事件信息管理框架,为突发公共事件的变化趋势进行预测和事件信息收集、处理、知识获取、事件评估、决策和应急管理工作提供科学依据和支持。     

考虑多种诱导信息下公众满意度的舆情危机响应决策方法

针对当前研究较少考虑到多种诱导信息情境下舆情危机响应决策问题的现状,首先在介绍研究理论和方法的基础上,对该决策问题进行了描述;然后,通过分析诱导信息的属性结构及其量化方式,运用前景理论从属性层面,提出了舆情危机特定情景和响应方案下公众对多种诱导信息发展态势满意度的计算方法;进一步地,考虑到方案对危机情景演变的影响,运用累积前景理论从公众满意度干预视角,提出了方案筛选的风险决策方法。最后,以一类重大传染病疫情场景中舆情危机响应决策问题为例,介绍该方法的潜在应用和说明其有效性。     

基于公众偏好大数据分析的大群体应急决策质量动态演化研究

针对突发事件大群体应急决策质量及其影响因素的问题，探讨了公众参与视角下突发事件演化的全生命周期，以及各阶段下公众风险感知对应急决策质量的影响，并以“8·12天津港爆炸”为背景案例进行分析。首先，阐述了公众偏好大数据的获取及处理方式，并以此对“8·12天津港爆炸”案例的公众偏好大数据进行预处理和可视化；其次，通过TF-IDF算法提取并量化公众风险感知，建立大群体应急决策质量打分函数，衡量不同阶段的应急决策质量；最后，基于“8·12天津港爆炸”案例的微博数据进行大群体应急决策质量的动态演化分析，得出研究结论和启示。实证表明，所提的模型与方法具有较新颖的研究视角，能够为大数据背景下的应急响应和政府决策提供理论支持和方法辅助。     

Point‐of‐Dispensing Location and Capacity Optimization via a Decision Support System

Dispensing of mass prophylaxis can be critical to public health during emergency situations and involves complex decisions that must be made in a short period of time. This study presents a model and solution approach for optimizing point‐of‐dispensing (POD) location and capacity decisions. This approach is part of a decision support system designed to help officials prepare for and respond to public health emergencies. The model selects PODs from a candidate set and suggests how to staff each POD so that average travel and waiting times are minimized. A genetic algorithm (GA) quickly solves the problem based on travel and queuing approximations (QAs) and it has the ability to relax soft constraints when the dispensing goals cannot be met. We show that the proposed approach returns solutions comparable with other systems and it is able to evaluate alternative courses of action when the resources are not sufficient to meet the performance targets.     

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).     

突发事件中舆情传播机制与演化博弈分析

针对当前研究较少从属性层次来研究突发事件中的舆情传播问题,本文运用突发事件的结构化描述方法从属性层次分析了舆情的产生和传播的动力学机制,进而分别建立了传播主体的决策行为和博弈关系的结构化描述框架。然后,考虑传播主体的认知差异,运用演化博弈论方法分别对社会公众之间及社会公众与政府部门之间的博弈关系进行了研究。最后,运用实际案例对理论研究的有效性进行了验证,并运用数值仿真考查了该案例中博弈主体的认知差异对博弈均衡的影响。     

Dealing with the White Death: Avalanche Risk Management for Traffic Routes

This article discusses mitigation strategies to protect traffic routes from snow avalanches. Up to now, mitigation of snow avalanches on many roads and railways in the Alps has relied on avalanche sheds, which require large initial investments resulting in high opportunity costs. Therefore, avalanche risk managers have increasingly adopted organizational mitigation measures such as warning systems and closure policies instead. The effectiveness of these measures is, however, greatly dependent on human decisions. In this article, we present a method for optimizing avalanche mitigation for traffic routes in terms of both their risk reduction impact and their net benefit to society. First, we introduce a generic framework for assessing avalanche risk and for quantifying the impact of mitigation. This allows for sound cost-benefit comparisons between alternative mitigation strategies. Second, we illustrate the framework with a case study from Switzerland. Our findings suggest that site-specific characteristics of avalanche paths, as well as the economic importance of a traffic route, are decisive for the choice of optimal mitigation strategies. On routes endangered by few avalanche paths with frequent avalanche occurrences, structural measures are most efficient, whereas reliance on organizational mitigation is often the most appropriate strategy on routes endangered by many paths with infrequent or fuzzy avalanche risk. Finally, keeping a traffic route open may be very important for tourism or the transport industry. Hence, local economic value may promote the use of a hybrid strategy that combines organizational and structural measures to optimize the resource allocation of avalanche risk mitigation.     

An Optimization‐Based Framework for the Identification of Vulnerabilities in Electric Power Grids Exposed to Natural Hazards

This article proposes a novel mathematical optimization framework for the identification of the vulnerabilities of electric power infrastructure systems (which is a paramount example of critical infrastructure) due to natural hazards. In this framework, the potential impacts of a specific natural hazard on an infrastructure are first evaluated in terms of failure and recovery probabilities of system components. Then, these are fed into a bi‐level attacker–defender interdiction model to determine the critical components whose failures lead to the largest system functionality loss. The proposed framework bridges the gap between the difficulties of accurately predicting the hazard information in classical probability‐based analyses and the over conservatism of the pure attacker–defender interdiction models. Mathematically, the proposed model configures a bi‐level max‐min mixed integer linear programming (MILP) that is challenging to solve. For its solution, the problem is casted into an equivalent one‐level MILP that can be solved by efficient global solvers. The approach is applied to a case study concerning the vulnerability identification of the georeferenced RTS24 test system under simulated wind storms. The numerical results demonstrate the effectiveness of the proposed framework for identifying critical locations under multiple hazard events and, thus, for providing a useful tool to help decisionmakers in making more‐informed prehazard preparation decisions.     

Bi-objective multi-resource scheduling problem for emergency relief operations

Abstract

Resource scheduling for emergency relief operations is complex as it has many constraints. However, an effective allocation and sequencing of resources are crucial for the minimization of the completion times in emergency relief operations. Despite the importance of such decisions, only a few mathematical models of emergency relief operations have been studied. This article presents a bi-objective mixed integer programming (MIP) that helps to minimize both the total weighted time of completion of the demand points and the makespan of the total emergency relief operation. A two-phase method is developed to solve the bi-objective MIP problem. Additionally, a case study of hospital network in the Melbourne metropolitan area is used to evaluate the model. The results indicate that the model can successfully support the decisions required in the optimal resource scheduling of emergency relief operations.     

A Simulation of Partial Information Use in Decision Making: Implications for DSS Design

Information matrices are often the output produced by a decision support system. These matrices are a common method for expressing a decision situation under different decision-making scenarios. The decisions involved in designing a decision support system to generate the information matrix are important and involve several cost and benefit components. A designer needs guidance in making effective design decisions in this context. Such guidance can be provided by considering the relationships among specific design decisions, costs, and benefits. The general objective of this study is to provide a comprehensive framework for this purpose. This study is the first to develop and present a comprehensive cost-benefit framework for evaluating design decisions for a variety of scenarios. The specific objective of this research is to provide guidance regarding the number of available information dimensions to incorporate in a computer-based decision aid. Simulation experiments are conducted with a completely specified model based on the cost-benefit framework (including needed assumptions) to evaluate how many information dimensions to include for a specific information matrix size to achieve a balance between information use costs and decision quality. Based upon extensive simulation analyses for a hypothetical decision maker, the practical guideline found for designers is to include only the top half of the relevant information dimensions in any specific decision support system. Over a large number of repeating choice decisions, the savings in cognitive effort and information gathering costs clearly offset relatively minor losses in decision quality.     

Understanding the Economic Costs and Benefits of Catastrophes and Their Aftermath: A Review and Suggestions for the U.S. Federal Government

The number and magnitude of devastating natural and human events make it imperative that we actively and systematically estimate the costs and benefits of policy decisions in affected localities, regions, states, and nations. Such strategic risk management preparedness efforts should forecast well into the future and include scenarios with and without enhanced engineered structures; with reduced vulnerability through land-use planning and design; with the impact of resiliency and mitigation; with evacuation and relocation; and with the costs and benefits of recovery and restoration. We describe different kinds of regional economic models that can be used in these preparedness planning efforts, explore critical data needs, and advocate a shared federal-state-local strategic planning effort to accomplish the objective.     

基于应对等级的突发事件网络舆情热度分析

突发事件应对等级是应急管理部门采取应对措施的基础,而网络舆情热度是突发事件态势发展的一个重要因素。以应对等级为切入点,构建网络舆情热度评价指标体系,从不同应对等级和事件类型的角度选取8个典型案例,运用GooSeeker等工具进行案例数据挖掘,获得各突发事件的舆情热度值,进一步通过构建突发事件应对等级和舆情热度分析图,发现其存在"一致"和"不一致"的对应关系。研究结果表明：一方面,把突发事件应对等级引入网络舆情热度量表,使舆情热度的评价与政府发布的应对等级建立联系,评价指标更加完善。另一方面,获得不同对应关系下应对等级对舆情热度的指标贡献,对突发事件网络舆情应对提出了更有针对性和科学性的建议。     

Agent‐Based Modeling to Simulate Contamination Events and Evaluate Threat Management Strategies in Water Distribution Systems

In the event of contamination of a water distribution system, decisions must be made to mitigate the impact of the contamination and to protect public health. Making threat management decisions while a contaminant spreads through the network is a dynamic and interactive process. Response actions taken by the utility managers and water consumption choices made by the consumers will affect the hydraulics, and thus the spread of the contaminant plume, in the network. A modeling framework that allows the simulation of a contamination event under the effects of actions taken by utility managers and consumers will be a useful tool for the analysis of alternative threat mitigation and management strategies. This article presents a multiagent modeling framework that combines agent‐based, mechanistic, and dynamic methods. Agents select actions based on a set of rules that represent an individual's autonomy, goal‐based desires, and reaction to the environment and the actions of other agents. Consumer behaviors including ingestion, mobility, reduction of water demands, and word‐of‐mouth communication are simulated. Management strategies are evaluated, including opening hydrants to flush the contaminant and broadcasts. As actions taken by consumer agents and utility operators affect demands and flows in the system, the mechanistic model is updated. Management strategies are evaluated based on the exposure of the population to the contaminant. The framework is designed to consider the typical issues involved in water distribution threat management and provides valuable analysis of threat containment strategies for water distribution system contamination events.     

重大传染病疫情演化情境下应急物资配置决策建模分析:以新冠肺炎疫情为例

基于对新冠肺炎疫情时空分布的分析,从时段、关键事件、传播动力学、空间分布、感染规模、信息特征、医疗资源等7个维度构建了重大传染病疫情演化的5种情境,提出了各种情境下需要解决的5个关键应急物资配置决策问题。综合考虑应急物资配置的空间、信息、物资、供应、需求和网络等特性,分析了每一个决策问题进行建模优化的关键因素。基于这些关键因素构建了一个多周期贝叶斯序贯决策模型,给出了求解步骤和解析解,并结合武汉疫情进行了算例分析,验证了模型的有效性。在重大传染病疫情演化情境下,综合考虑这些关键因素,应用贝叶斯决策分析进行应急物资配置决策建模有利于建立更加符合实际的决策模型,减少决策损失。     

突发危机事件网络舆情治理的多情景演化博弈分析

互联网时代，网络媒体已经成为谣言传播的重要载体，严重威胁到我国的网络空间安全和社会和谐稳定，因此加强和创新对网络媒体的监管，妥善治理突发危机事件网络舆情是各级政府面临的重大挑战。针对突发危机事件网络舆情治理的研究，本文运用演化博弈理论构建了网络媒体与地方政府双方演化博弈模型，在引入中央政府惩罚机制基础上，对比分析了网络媒体与地方政府双方行为策略选择的演化稳定均衡，同时采取多案例进行实证研究，并通过数值仿真分析对模型进行多情景推演模拟。研究结果表明：突发危机事件网络舆情传播热度与网络媒体和地方政府双方的策略选择有着直接关系；若地方政府承受突发危机事件网络舆情恶性演化造成的经济损失与信誉损失持续增大，双方演化系统都会出现周期性波动现象；引入中央政府惩罚机制后，其惩罚力度若高于网络媒体消极应对网络舆情所受到的惩罚和地方政府的监管投入成本时，最终系统会演化至良性状态，研究结论为政府部门在面对突发危机事件网络舆情治理方面提供了新思路。     

A conceptual framework for understanding the outsourcing decision

Outsourcing is an increasingly important initiative being pursued by corporations in North America and Europe in pursuit of improved efficiency. This paper provides a conceptual framework to assist managers in identifying and implementing outsourcing decisions. In particular, the framework suggests a way for managers to identify the pre- and post-contractual risks associated with outsourcing decisions along with strategies that can be implemented in the pre-contractual stage in order to mitigate those risks. Empirical findings from the ‘transactions cost' literature are referenced to illustrate elements of our conceptual framework.     

Implementation of Equity in Resource Allocation for Regional Earthquake Risk Mitigation Using Two‐Stage Stochastic Programming

This article presents a new methodology to implement the concept of equity in regional earthquake risk mitigation programs using an optimization framework. It presents a framework that could be used by decisionmakers (government and authorities) to structure budget allocation strategy toward different seismic risk mitigation measures, i.e., structural retrofitting for different building structural types in different locations and planning horizons. A two‐stage stochastic model is developed here to seek optimal mitigation measures based on minimizing mitigation expenditures, reconstruction expenditures, and especially large losses in highly seismically active countries. To consider fairness in the distribution of financial resources among different groups of people, the equity concept is incorporated using constraints in model formulation. These constraints limit inequity to the user‐defined level to achieve the equity‐efficiency tradeoff in the decision‐making process. To present practical application of the proposed model, it is applied to a pilot area in Tehran, the capital city of Iran. Building stocks, structural vulnerability functions, and regional seismic hazard characteristics are incorporated to compile a probabilistic seismic risk model for the pilot area. Results illustrate the variation of mitigation expenditures by location and structural type for buildings. These expenditures are sensitive to the amount of available budget and equity consideration for the constant risk aversion. Most significantly, equity is more easily achieved if the budget is unlimited. Conversely, increasing equity where the budget is limited decreases the efficiency. The risk‐return tradeoff, equity‐reconstruction expenditures tradeoff, and variation of per‐capita expected earthquake loss in different income classes are also presented.     

Public Support For Earthquake Risk Mitigation In Portland,Oregon

During the 1980s, seismic research suggested that Oregon and the City of Portland had a higher risk of a major earthquake than had previously been assumed. In 1993, the State of Oregon adopted a new version of the Oregon Structural Specialty Code, which changed the designation of western Oregon from seismic zone 2b to seismic zone 3. The City of Portland established a program and a Task Force on Seismic Strengthening of Buildings to recommend actions that would encourage upgrading of city buildings. A survey of adult city residents was conducted in April, 1996 to determine public attitudes and opinions about earthquake risks, management and mitigation of earthquake hazards, priorities for protection by strengthening buildings, evaluations of strategies for informing the public about earthquake risks, and support for specific options the city might take to protect citizens against earthquake events. Social and demographic information on individuals and households was also collected. Respondents provided ratings for a wide range of social and environmental risks, provided information on priorities for strengthening key buildings and infrastructure facilities, and answered hypothetical questions about voting for bond measures to pay for city earthquake-mitigation programs. Respondents recognized significant risk from earthquakes and supported programs to protect people, especially vulnerable residents such as children and the sick. There was strong support for protecting emergency response capabilities. There was much less support for using public funds to reduce the risks associated with privately owned buildings. There were also some strong pockets of resistance to publicly funded mitigation programs in response to the hypothetical bond measures.