System of Systems Engineering and Risk Management of Extreme Events: Concepts and Case Study

The domain of risk analysis is expanded to consider strategic interactions among multiple participants in the management of extreme risk in a system of systems. These risks are fraught with complexity, ambiguity, and uncertainty, which pose challenges in how participants perceive, understand, and manage risk of extreme events. In the case of extreme events affecting a system of systems, cause‐and‐effect relationships among initiating events and losses may be difficult to ascertain due to interactions of multiple systems and participants (complexity). Moreover, selection of threats, hazards, and consequences on which to focus may be unclear or contentious to participants within multiple interacting systems (ambiguity). Finally, all types of risk, by definition, involve potential losses due to uncertain events (uncertainty). Therefore, risk analysis of extreme events affecting a system of systems should address complex, ambiguous, and uncertain aspects of extreme risk. To accomplish this, a system of systems engineering methodology for risk analysis is proposed as a general approach to address extreme risk in a system of systems. Our contribution is an integrative and adaptive systems methodology to analyze risk such that strategic interactions among multiple participants are considered. A practical application of the system of systems engineering methodology is demonstrated in part by a case study of a maritime infrastructure system of systems interface, namely, the Straits of Malacca and Singapore.     

国际工程造价管理体制的比较研究

工程造价管理体制改革—直是近两年来国家经济体制改革的一个重要组成部分。随着我国建筑市场体制改革的深入,对于这一课题的研究已经成为当务之急。本文运用比较管理研究的方法深入分析和对照了中国香港、英联邦国家、美国、日本和我国的工程造价管理体制,分别从工程造价总的管理体制、政府性工程项目管理体制和具体的工程造价管理方式方法阐述了各自的利弊和我们在工程造价管理体制改革中应该借鉴的地方。     

Integrating Risk and Resilience Approaches to Catastrophe Management in Engineering Systems

Recent natural and man‐made catastrophes, such as the Fukushima nuclear power plant, flooding caused by Hurricane Katrina, the Deepwater Horizon oil spill, the Haiti earthquake, and the mortgage derivatives crisis, have renewed interest in the concept of resilience, especially as it relates to complex systems vulnerable to multiple or cascading failures. Although the meaning of resilience is contested in different contexts, in general resilience is understood to mean the capacity to adapt to changing conditions without catastrophic loss of form or function. In the context of engineering systems, this has sometimes been interpreted as the probability that system conditions might exceed an irrevocable tipping point. However, we argue that this approach improperly conflates resilience and risk perspectives by expressing resilience exclusively in risk terms. In contrast, we describe resilience as an emergent property of what an engineering system does, rather than a static property the system has. Therefore, resilience cannot be measured at the systems scale solely from examination of component parts. Instead, resilience is better understood as the outcome of a recursive process that includes: sensing, anticipation, learning, and adaptation. In this approach, resilience analysis can be understood as differentiable from, but complementary to, risk analysis, with important implications for the adaptive management of complex, coupled engineering systems. Management of the 2011 flooding in the Mississippi River Basin is discussed as an example of the successes and challenges of resilience‐based management of complex natural systems that have been extensively altered by engineered structures.     

EDB: A Case Study in Communicating Risk

This is a report on the Environmental Protection Agency's (EPA's) efforts to communicate with the public about the risks of ethylene dibromide (EDB), what the agency said it was doing about these risks and what information the public actually received through television and newspapers. Although special in many ways, the EDB case illustrates the problems that regulatory agencies have when they must take regulatory action and assure the public that the risks in question are being dealt with adequately. It also illustrates issues that the press faces. Above all, it illustrates the barriers to communication presented by the different perspectives of regulatory agencies and individuals and the types of information they each are most interested in.     

Warning Systems in Risk Management

A method is presented here that allows probabilistic evaluation and optimization of warning systems, and comparison of their performance and cost-effectiveness with those of other means of risk management. The model includes an assessment of the signals, and of human response, given the memory that people have kept of the quality of previous alerts. The trade-off between the rate of false alerts and the length of the lead time is studied to account for the long-term effects of "crying wolf" and the effectiveness of emergency actions. An explicit formulation of the system's benefits, including inputs from a signal model, a response model, and a consequence model, is given to allow optimization of the warning threshold and of the system's sensitivity.     

Cryptosporidiosis Susceptibility and Risk: A Case Study

Regional estimates of cryptosporidiosis risks from drinking water exposure were developed and validated, accounting for AIDS status and age. We constructed a model with probability distributions and point estimates representing Cryptosporidium in tap water, tap water consumed per day (exposure characterization); dose response, illness given infection, prolonged illness given illness; and three conditional probabilities describing the likelihood of case detection by active surveillance (health effects characterization). The model predictions were combined with population data to derive expected case numbers and incidence rates per 100,000 population, by age and AIDS status, borough specific and for New York City overall in 2000 (risk characterization). They were compared with same-year surveillance data to evaluate predictive ability, assumed to represent true incidence of waterborne cryptosporidiosis. The predicted mean risks, similar to previously published estimates for this region, overpredicted observed incidence-most extensively when accounting for AIDS status. The results suggest that overprediction may be due to conservative parameters applied to both non-AIDS and AIDS populations, and that biological differences for children need to be incorporated. Interpretations are limited by the unknown accuracy of available surveillance data, in addition to variability and uncertainty of model predictions. The model appears sensitive to geographical differences in AIDS prevalence. The use of surveillance data for validation and model parameters pertinent to susceptibility are discussed.     

A Value Measure for Public‐Sector Enterprise Risk Management: A TSA Case Study

This article presents a public value measure that can be used to aid executives in the public sector to better assess policy decisions and maximize value to the American people. Using Transportation Security Administration (TSA) programs as an example, we first identify the basic components of public value. We then propose a public value account to quantify the outcomes of various risk scenarios, and we determine the certain equivalent of several important TSA programs. We illustrate how this proposed measure can quantify the effects of two main challenges that government organizations face when conducting enterprise risk management: (1) short‐term versus long‐term incentives and (2) avoiding potential negative consequences even if they occur with low probability. Finally, we illustrate how this measure enables the use of various tools from decision analysis to be applied in government settings, such as stochastic dominance arguments and certain equivalent calculations. Regarding the TSA case study, our analysis demonstrates the value of continued expansion of the TSA trusted traveler initiative and increasing the background vetting for passengers who are afforded expedited security screening.     

Stringency of Workplace Air Contaminant Exposure Limits: A Case Study of OSHA Risk Management

Political context may play a large role in influencing the efficiency of environmental and health regulations. This case study uses data from a 1989 update of the Occupational Safety and Health Administration (OSHA) Permissible Exposure Limits (PELs) program to determine the relative effects of legislative mandates, costly acquisition of information by the agency, and pressure applied by special interest groups upon exposure standards. The empirical analysis suggests that federal agencies successfully thwart legislative attempts to limit agency discretion, and that agencies exercise bounded rationality by placing greater emphasis on more easily obtained information. The 1989 PELs were less significantly related to more costly information, contained safety factors for chemicals presenting relatively more ambiguous risks, and the proposed standard stringencies showed evidence of being influenced by vying industry and labor interests.     

组织环境对工程项目成本管理影响研究——基于中铁二局的案例分析

工程项目成本管理是施工企业生存发展的关键所在。本文从组织环境这一宽泛的视角,探讨组织内外部环境中对工程项目成本管理产生影响的重要因素。以中铁二局为研究对象,通过实地访谈研究识别企业组织环境对工程项目成本管理的影响因素。本文应用扎根理论,通过对访谈数据逐级编码分析,构建了基于组织结构、控制体系和社会关系等三大支持系统的"3S"理论,从而揭示组织环境对工程项目成本管理的作用机制和对企业成本管理的意义。     

The Use of Stochastic Simulation in Knowledge-Based Systems

Knowledge-based systems support the decision-making process with the help of domain specific knowledge bases. The knowledge bases almost always have uncertainty associated with them. A variety of approaches have been proposed in the artificial intelligence (AI) literature for the construction of and reasoning with uncertain knowledge bases. Building on this stream of research, we focus on how stochastic simulation can be used to construct and reason with knowledge bases that have uncertainties. An advantage of the simulation methodology is that it may not have to make many of the assumptions made by other approaches. It also allows the designer of the knowledge-based system to control the methodology based on accuracy and time requirements. The simulation approach to knowledge base construction is a modified version of the concept induction procedure used in AI. However, it incorporates, as does simulation modeling, statistical tests to identify the best rule that describes the relationship among the variables. We show that when simulation is used to reason with uncertain knowledge bases, under certain conditions, the number of simulation trials needed to achieve a given level of accuracy is independent of the characteristics, such as the size, of the knowledge base. Empirical results obtained from an experiment confirm our theoretical results and provide evidence that simulation methodology is practical for real life knowledge-based systems.     

Cyber Risk Management for Critical Infrastructure: A Risk Analysis Model and Three Case Studies

Managing cyber security in an organization involves allocating the protection budget across a spectrum of possible options. This requires assessing the benefits and the costs of these options. The risk analyses presented here are statistical when relevant data are available, and system‐based for high‐consequence events that have not happened yet. This article presents, first, a general probabilistic risk analysis framework for cyber security in an organization to be specified. It then describes three examples of forward‐looking analyses motivated by recent cyber attacks. The first one is the statistical analysis of an actual database, extended at the upper end of the loss distribution by a Bayesian analysis of possible, high‐consequence attack scenarios that may happen in the future. The second is a systems analysis of cyber risks for a smart, connected electric grid, showing that there is an optimal level of connectivity. The third is an analysis of sequential decisions to upgrade the software of an existing cyber security system or to adopt a new one to stay ahead of adversaries trying to find their way in. The results are distributions of losses to cyber attacks, with and without some considered countermeasures in support of risk management decisions based both on past data and anticipated incidents.     

A Comparative Analysis of Korean and American Management Education: A Knowledge-Based Odyssey

The evolution of post-industrial society is resulting in a `knowledgeeconomy. The changes involve `knowledge workers' in contrast to `manualworkers' of the past industrial economy. The quantity and quality of knowledgeworkers will determine success in national borderless competition. Althoughthe United State's recent prosperity and near perfect employment rate areexemplary, the technology leading to this success has been developed andshared by traditional industrial powers, i.e., Japan and France, and mid-techpowers such as South Korea.This paper examines methods by which South Korea incorporates Americanapplications of the knowledge economy into its system. The interdisciplinaryapproach includes sociological, linguistic, educational, and ethical elements.Suggested methods include double loop sharing, knowledge management withelectronic support systems, professional journals, and professionalinternational conferences. This paper offers a brief history and synopsis ofcurrent developments in knowledge-based systems, and suggests South Korean andAmerican applications. Recommendations also include the emphasis on Englishas the primary language to improve Korean communication among government,industry, and academic entities.     

工程项目支付进度优化：一个案例研究

本文以一个具有代表性的实际工程项目--JZDWBD-V为对象,对支付进度安排问题进行研究.作者首先介绍该工程项目的实际背景;随后从承包商、业主及双方联合等角度构建该项目支付进度安排的优化模型,并求解获得不同角度下的满意支付进度安排;通过将理论结果与现实情况的对比分析,找出该工程项目在实际管理中存在的差距,为支付进度的管理、项目工期和费用的控制提供定量化决策支持.     

Forest Fire Risk Management and Public Participation in Changing Socioenvironmental Conditions: A Case Study in a Mediterranean Region

Under current conditions of accelerated socioenvironmental change in the Mediterranean forested landscapes, fire is one of the most critical and difficult risks to tackle within the region. This article summarizes the lessons learned from a project based on the participatory integration of qualitative local stakeholders' knowledge with expert GIS fire simulations carried out in the County of El Bages, Catalonia, Spain. First, in this article, a theoretical model--the forest fire circle--is presented in order to explain the reasons for the rise in the damage and frequency of forest fires in this Mediterranean area. Second, it describes the methodology developed and the stages followed during the project. Results show that: (1) the advocacy of old forest reactive management paradigm assumptions and practices based on uncontrolled forest succession can put vast wooded areas of the Mediterranean basin at critical risk; and (2) forest fire management approaches that ignore the crucial role of long-term prevention and local capacity building strategies have failed. In the final section, the content and the specific dimensions of the old reactive paradigm that has characterized forest fire risk management in Catalonia are discussed and contrasted with the possibly emerging preventative paradigm.     

Risk Management for Leontief-Based Interdependent Systems

When stricken by a terrorist attack, a war, or a natural disaster, an economic unit or a critical infrastructure may suffer significant loss of productivity. More importantly, due to interdependency or interconnectedness, this initial loss may propagate into other systems and eventually lead to much greater derivative loss. This belongs to what is known as a cascading effect. It is demonstrated in this article that the cascading effect and the derivative loss can be significantly reduced by effective risk management. This is accomplished by deliberately distributing the initial inoperability to other systems so that the total loss (or inoperability) is minimized. The optimal distribution strategy is found by a linear programming technique. The same risk management can also be applied to situations where objectives need to be prioritized. A case study featuring 12 economic sectors illustrates the theory. The result suggests that using the same amount of resources, minimizing risk (inoperability) of infrastructures will generally give rise to highest payoff, whereas overlooking it may result in greatest total loss. The framework developed in this work uses a steady-state approach that applies primarily to managing situations where the attack is catastrophic resulting in very long recovery time.     

Applicability of a Neuroprobabilistic Integral Risk Index for the Environmental Management of Polluted Areas: A Case Study

Recently, we developed a GIS-Integrated Integral Risk Index (IRI) to assess human health risks in areas with presence of environmental pollutants. Contaminants were previously ranked by applying a self-organizing map (SOM) to their characteristics of persistence, bioaccumulation, and toxicity in order to obtain the Hazard Index (HI). In the present study, the original IRI was substantially improved by allowing the entrance of probabilistic data. A neuroprobabilistic HI was developed by combining SOM and Monte Carlo analysis. In general terms, the deterministic and probabilistic HIs followed a similar pattern: polychlorinated biphenyls (PCBs) and light polycyclic aromatic hydrocarbons (PAHs) were the pollutants showing the highest and lowest values of HI, respectively. However, the bioaccumulation value of heavy metals notably increased after considering a probability density function to explain the bioaccumulation factor. To check its applicability, a case study was investigated. The probabilistic integral risk was calculated in the chemical/petrochemical industrial area of Tarragona (Catalonia, Spain), where an environmental program has been carried out since 2002. The risk change between 2002 and 2005 was evaluated on the basis of probabilistic data of the levels of various pollutants in soils. The results indicated that the risk of the chemicals under study did not follow a homogeneous tendency. However, the current levels of pollution do not mean a relevant source of health risks for the local population. Moreover, the neuroprobabilistic HI seems to be an adequate tool to be taken into account in risk assessment processes.