风险方法的局限性

IF 1.7 3区 工程技术 Q3 ENGINEERING, CIVIL Civil Engineering and Environmental Systems Pub Date : 2019-01-02 DOI:10.1080/10286608.2019.1615474
D. Elms
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引用次数: 4

摘要

风险评估方法功能强大,用途广泛,但也存在局限性和微妙的陷阱。本文探讨了风险的本质。主要困难有三个。首先,信息的质量和完整性存在问题。缺乏精确的信息意味着必须估计可能性和后果,因此信息容易受到偏见的影响:有些是探索的。其次,风险模型存在严重的完整性问题,其中的遗漏可能导致严重的后果。有时被称为“黑天鹅”的意外事件比比皆是。第三,非常小的概率和重大后果的结合可能导致不可靠和可疑的结果。应用领域考虑结构工程,项目管理和风险管理一般。在某些情况下,弹性方法比风险方法更可取。
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Limitations of risk approaches
ABSTRACT Risk methods are powerful and versatile, but they have limitations and subtle traps. The paper explores the nature of risk. There are three main difficulties. First, there is a problem with quality and completeness of information. Lack of precise information means that likelihood and consequences have to be estimated, so the information is vulnerable to biases: some are explored. Secondly, there is a serious problem of completeness in risk models, where omissions can lead to serious consequences. Unexpected events, sometimes called ‘black swans’, abound. Thirdly, the conjunction of very small probabilities and major consequences can lead to unreliable and dubious results. Applications areas considered are structural engineering, project management and risk management generally. There are situations where a resilience approach is preferable to risk.
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来源期刊
Civil Engineering and Environmental Systems
Civil Engineering and Environmental Systems 工程技术-工程:土木
CiteScore
3.30
自引率
16.70%
发文量
10
审稿时长
>12 weeks
期刊介绍: Civil Engineering and Environmental Systems is devoted to the advancement of systems thinking and systems techniques throughout systems engineering, environmental engineering decision-making, and engineering management. We do this by publishing the practical applications and developments of "hard" and "soft" systems techniques and thinking. Submissions that allow for better analysis of civil engineering and environmental systems might look at: -Civil Engineering optimization -Risk assessment in engineering -Civil engineering decision analysis -System identification in engineering -Civil engineering numerical simulation -Uncertainty modelling in engineering -Qualitative modelling of complex engineering systems
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