Risk Analysis: An International Journal

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Table of Contents for Risk Analysis. List of articles from both the latest and EarlyView issues.
Updated: 37 min 48 sec ago

A Decision‐Centered Method to Evaluate Natural Hazards Decision Aids by Interdisciplinary Research Teams

14 January 2019 - 1:11pm
Abstract

There is a growing number of decision aids made available to the general public by those working on hazard and disaster management. When based on high‐quality scientific studies across disciplines and designed to provide a high level of usability and trust, decision aids become more likely to improve the quality of hazard risk management and response decisions. Interdisciplinary teams have a vital role to play in this process, ensuring the scientific validity and effectiveness of a decision aid across the physical science, social science, and engineering dimensions of hazard awareness, option identification, and the decisions made by individuals and communities. Often, these aids are not evaluated before being widely distributed, which could improve their impact, due to a lack of dedicated resources and guidance on how to systematically do so. In this Perspective, we present a decision‐centered method for evaluating the impact of hazard decision aids on decisionmaker preferences and choice during the design and development phase, drawing from the social and behavioral sciences and a value of information framework to inform the content, complexity, format, and overall evaluation of the decision aid. The first step involves quantifying the added value of the information contained in the decision aid. The second involves identifying the extent to which the decision aid is usable. Our method can be applied to a variety of hazards and disasters, and will allow interdisciplinary teams to more effectively evaluate the extent to which an aid can inform and improve decision making.

Integrated Risk Assessment and Management Methods Are Necessary for Effective Implementation of Natural Hazards Policy

14 January 2019 - 11:07am
Abstract

A transdisciplinary, integrated risk assessment and risk management process is particularly beneficial to the development of policies addressing risk from natural hazards. Strategies based on isolated risk assessment and management processes, guided by traditional “predict, then act” methods for decision making, may induce major regret if future conditions diverge from predictions. Analytic methods designed to identify robust solutions—those that perform satisfactorily over a broader range of future conditions—are more suitable for management of natural hazards risks, for at least three major reasons discussed within. Such approaches benefit from co‐production of knowledge to collaboratively produce adaptive, robust policies through an iterative process of dialogue between analysts, decisionmakers, and other stakeholders: exploring tradeoffs, searching for futures in which current plans are likely to fail, and developing adaptive management strategies responsive to evolving future conditions. The process leads to more effective adoption of risk management policies by ensuring greater feasibility of solutions, exploring a wide range of plausible future conditions, generating buy‐in, and giving a voice to actors with a diversity of perspectives. The second half of the article presents Louisiana's coastal master planning process as an exemplary model of participatory planning and integrated risk assessment and management. Louisiana planners have adopted a decision framework that incorporates insights from modern methods for decision making under deep uncertainty to effectively address the deep uncertainties and complexities characteristic of a variety of natural hazards and long‐range planning problems.

Integrated Risk Assessment and Management Methods Are Necessary for Effective Implementation of Natural Hazards Policy

14 January 2019 - 11:07am
Abstract

A transdisciplinary, integrated risk assessment and risk management process is particularly beneficial to the development of policies addressing risk from natural hazards. Strategies based on isolated risk assessment and management processes, guided by traditional “predict, then act” methods for decision making, may induce major regret if future conditions diverge from predictions. Analytic methods designed to identify robust solutions—those that perform satisfactorily over a broader range of future conditions—are more suitable for management of natural hazards risks, for at least three major reasons discussed within. Such approaches benefit from co‐production of knowledge to collaboratively produce adaptive, robust policies through an iterative process of dialogue between analysts, decisionmakers, and other stakeholders: exploring tradeoffs, searching for futures in which current plans are likely to fail, and developing adaptive management strategies responsive to evolving future conditions. The process leads to more effective adoption of risk management policies by ensuring greater feasibility of solutions, exploring a wide range of plausible future conditions, generating buy‐in, and giving a voice to actors with a diversity of perspectives. The second half of the article presents Louisiana's coastal master planning process as an exemplary model of participatory planning and integrated risk assessment and management. Louisiana planners have adopted a decision framework that incorporates insights from modern methods for decision making under deep uncertainty to effectively address the deep uncertainties and complexities characteristic of a variety of natural hazards and long‐range planning problems.

Exploring the Conceptual Foundation of Continuity Management in the Context of Societal Safety

9 January 2019 - 8:33pm
Abstract

Public and private actors with critical roles for ensuring societal safety need to work proactively to reduce risks and vulnerabilities. Traditionally, risk management activities have often been performed in order to ensure continuous functioning of key societal services. Recently, however, business continuity management (BCM), and its analytical subcomponent business impact assessment (BIA), has been introduced and used more extensively by both the private and public sector in order to increase the robustness and resilience of critical infrastructures and societal functions and services. BCM was originally developed in the business sector but has received a broader use during the last decade. Yet, BCM/BIA has gained limited attention in the scientific literature—especially when it comes to clarifying and developing its conceptual basis. First, this article examines and discusses the conceptual foundation of BCM concepts, including practical challenges of applying the concepts. Based on recent conceptual developments from the field of risk management, a developed conceptualization is suggested. Second, the article discusses challenges that arise when applying BCM in the societal safety area and provides some recommendations aiming to improve the clarity and quality of applications. Third, the article provides suggestions of how to integrate the overlapping approaches of BIA and risk assessment in order to improve efficiency and effectiveness of proactive, analytic processes. We hope that the article can stimulate a critical discussion about the key concepts of BCM, their wider use in societal safety, and their connection to other concepts and activities such as risk assessment.

Exploring the Conceptual Foundation of Continuity Management in the Context of Societal Safety

9 January 2019 - 8:33pm
Abstract

Public and private actors with critical roles for ensuring societal safety need to work proactively to reduce risks and vulnerabilities. Traditionally, risk management activities have often been performed in order to ensure continuous functioning of key societal services. Recently, however, business continuity management (BCM), and its analytical subcomponent business impact assessment (BIA), has been introduced and used more extensively by both the private and public sector in order to increase the robustness and resilience of critical infrastructures and societal functions and services. BCM was originally developed in the business sector but has received a broader use during the last decade. Yet, BCM/BIA has gained limited attention in the scientific literature—especially when it comes to clarifying and developing its conceptual basis. First, this article examines and discusses the conceptual foundation of BCM concepts, including practical challenges of applying the concepts. Based on recent conceptual developments from the field of risk management, a developed conceptualization is suggested. Second, the article discusses challenges that arise when applying BCM in the societal safety area and provides some recommendations aiming to improve the clarity and quality of applications. Third, the article provides suggestions of how to integrate the overlapping approaches of BIA and risk assessment in order to improve efficiency and effectiveness of proactive, analytic processes. We hope that the article can stimulate a critical discussion about the key concepts of BCM, their wider use in societal safety, and their connection to other concepts and activities such as risk assessment.

Potential of Citizen Science for Enhancing Infrastructure Monitoring Data and Decision‐Support Models for Local Communities

4 January 2019 - 8:00pm
Abstract

Citizen science is a process by which volunteer members of the public, who commonly lack advanced training in science, engage in scientific activities (e.g., data collection) that might otherwise be beyond the reach of professional researchers or practitioners. The purpose of this article is to discuss how citizen‐science projects coordinated by interdisciplinary teams of engineers and social scientists can potentially enhance infrastructure monitoring data and decision‐support models for local communities. The article provides an interdisciplinary definition of infrastructure data quality that extends beyond accuracy to include currency, timeliness, completeness, and equitability. We argue that with this expanded definition of data quality, citizen science can be a viable method for enhancing the quality of infrastructure monitoring data, and ultimately the credibility of risk analysis and decision‐support models that use these data. The article concludes with a set of questions to aid in producing high‐quality infrastructure monitoring data by volunteer citizen scientists.

Potential of Citizen Science for Enhancing Infrastructure Monitoring Data and Decision‐Support Models for Local Communities

4 January 2019 - 8:00pm
Abstract

Citizen science is a process by which volunteer members of the public, who commonly lack advanced training in science, engage in scientific activities (e.g., data collection) that might otherwise be beyond the reach of professional researchers or practitioners. The purpose of this article is to discuss how citizen‐science projects coordinated by interdisciplinary teams of engineers and social scientists can potentially enhance infrastructure monitoring data and decision‐support models for local communities. The article provides an interdisciplinary definition of infrastructure data quality that extends beyond accuracy to include currency, timeliness, completeness, and equitability. We argue that with this expanded definition of data quality, citizen science can be a viable method for enhancing the quality of infrastructure monitoring data, and ultimately the credibility of risk analysis and decision‐support models that use these data. The article concludes with a set of questions to aid in producing high‐quality infrastructure monitoring data by volunteer citizen scientists.

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