Who Would Be Willing to Accept Disaster Debris in Their Backyard? Investigating the Determinants of Public Attitudes in Post‐Fukushima Japan

In the wake of the 2011 Great East Japan Earthquake and tsunami, the Ministry of Environment in Japan asked municipalities nationwide to accept and treat disaster waste. This call for cross‐jurisdictional waste treatment provoked considerable public controversy. To explore how the national and municipal governments can seek more public acceptance in the wake of future disasters, this study implemented a nationwide survey and addressed the question of what factors influence the public's willingness to support their municipalities’ plans to host disaster waste. Three strands of the literature—on risk perception, public dissent, and prosocial behavior—offer valuable insights into hypothesis building, although none has addressed the above question. Estimates from an ordered logistic regression (N = 1,063) reveal that the conditions of a nuclear accident and living with a small child in the household would lower the level of support for accepting disaster waste, although this does not mean that people would give their support in the absence of a nuclear accident. The results also suggest that the national and municipal governments should communicate more with the public about the risks, benefits, and costs associated with hosting disaster debris, and make efforts to improve public trust in the national government.     

Risk Science Contributions: Three Illustrating Examples

This article aims to demonstrate that risk science is important for society, industry and all of us. Rather few people today, including scientists and managers, are familiar with what this science is about—its foundation and main features—and how it is used to gain knowledge and improve communication and decision making in real-life situations. The article seeks to meet this challenge, by presenting three examples, showing how risk science works to gain new generic, fundamental knowledge on risk concepts, principles, and methods, as well as supporting the practical tackling of actual risk problems.     

Using the CAUSE Model to Understand Public Communication about Water Risks: Perspectives from Texas Groundwater District Officials on Drought and Availability

Public communication about drought and water availability risks poses challenges to a potentially disinterested public. Water management professionals, though, have a responsibility to work with the public to engage in communication about water and environmental risks. Because limited research in water management examines organizational communication practices and perceptions, insights into research and practice can be gained through investigation of current applications of these risk communication efforts. Guided by the CAUSE model, which explains common goals in communicating risk information to the public (e.g., creating Confidence, generating Awareness, enhancing Understanding, gaining Satisfaction, and motivating Enactment), semistructured interviews of professionals (N = 25) employed by Texas groundwater conservation districts were conducted. The interviews examined how CAUSE model considerations factor in to communication about drought and water availability risks. These data suggest that many work to build constituents’ confidence in their districts. Although audiences and constituents living in drought‐prone areas were reported as being engaged with water availability risks and solutions, many district officials noted constituents’ lack of perceived risk and engagement. Some managers also indicated that public understanding was a secondary concern of their primary responsibilities and that the public often seemed apathetic about technical details related to water conservation risks. Overall, results suggest complicated dynamics between officials and the public regarding information access and motivation. The article also outlines extensions of the CAUSE model and implications for improving public communication about drought and water availability risks.     

Organizational Memory: From Expectations Memory to Procedural Memory

Organizational memory is not just the stock of knowledge about how to do things, but also of expectations of organizational members vis‐à‐vis each other and the organization as a whole. The central argument of this paper is that this second type of organizational memory –organizational expectations memory– is a necessary precondition for successfully creating and maintaining organizational procedural memory, which is at the basis of organizational performance. If members of organizations have fewer expectations of being rewarded beyond what is stipulated in formal contracts, these individuals are less likely to risk investing in collective tacit and firm‐specific knowledge resources and more likely to focus on building individual and mobile knowledge resources that have value outside the boundaries of the organization. A case study of latent organizations in the Dutch film industry is presented to support the central argument and suggests further avenues of research, in particular concerning the effects of labour mobility on organizational expectations memory.     

Evaluating and improving risk formulas for allocating limited budgets to expensive risk-reduction opportunities

Simple risk formulas, such as risk = probability × impact, or risk = exposure × probability × consequence, or risk = threat × vulnerability × consequence, are built into many commercial risk management software products deployed in public and private organizations. These formulas, which we call risk indices, together with risk matrices, “heat maps,” and other displays based on them, are widely used in applications such as enterprise risk management (ERM), terrorism risk analysis, and occupational safety. But, how well do they serve to guide allocation of limited risk management resources? This article evaluates and compares different risk indices under simplifying conditions favorable to their use (statistically independent, uniformly distributed values of their components; and noninteracting risk‐reduction opportunities). Compared to an optimal (nonindex) approach, simple indices produce inferior resource allocations that for a given cost may reduce risk by as little as 60% of what the optimal decisions would provide, at least in our simple simulations. This article suggests a better risk reduction per unit cost index that achieves 98–100% of the maximum possible risk reduction on these problems for all budget levels except the smallest, which allow very few risks to be addressed. Substantial gains in risk reduction achieved for resources spent can be obtained on our test problems by using this improved index instead of simpler ones that focus only on relative sizes of risk (or of components of risk) in informing risk management priorities and allocating limited risk management resources. This work suggests the need for risk management tools to explicitly consider costs in prioritization activities, particularly in situations where budget restrictions make careful allocation of resources essential for achieving close‐to‐maximum risk‐reduction benefits.     

Consumer Responses to Integrated Risk‐Benefit Information Associated with the Consumption of Food

The risk analysis of the health impact of foods is increasingly focused on integrated risk‐benefit assessment, which will also need to be communicated to consumers. It therefore becomes important to understand how consumers respond to integrated risk‐benefit information. Quality‐adjusted‐life‐years (QALYs) is one measure that can be used to assess the balance between risks and benefits associated with a particular food. The effectiveness of QALYs for communicating both positive and negative health effects associated with food consumption to consumers was examined, using a 3 × 2 experiment varying information about health changes in terms of QALYs associated with the consumption of fish (n = 325). The effect of this information on consumer perceptions of the usefulness of QALYs for describing health effects, on risk and benefit perceptions, attitudes, and intentions to consume fish was examined. Results demonstrated that consumers perceived QALYs as useful for communicating health effects associated with food consumption. QALYs communicated as a net effect were preferred for food products associated with negative net effects on health, while separate communication of both risks and benefits may be preferred for food products associated with positive or zero net health effects. Information about health changes in terms of QALYs facilitated informed decision making by consumers, as indicated by the impact on risk and benefit perceptions as intended by the information. The impact of this information on actual food consumption choices merits further investigation.     

Secondary Risk Theory: Validation of a Novel Model of Protection Motivation

Protection motivation theory states individuals conduct threat and coping appraisals when deciding how to respond to perceived risks. However, that model does not adequately explain today's risk culture, where engaging in recommended behaviors may create a separate set of real or perceived secondary risks. We argue for and then demonstrate the need for a new model accounting for a secondary threat appraisal, which we call secondary risk theory. In an online experiment, 1,246 participants indicated their intention to take a vaccine after reading about the likelihood and severity of side effects. We manipulated likelihood and severity in a 2 × 2 between‐subjects design and examined how well secondary risk theory predicts vaccination intention compared to protection motivation theory. Protection motivation theory performed better when the likelihood and severity of side effects were both low (R² = 0.30) versus high (R² = 0.15). In contrast, secondary risk theory performed similarly when the likelihood and severity of side effects were both low (R² = 0.42) or high (R² = 0.45). But the latter figure is a large improvement over protection motivation theory, suggesting the usefulness of secondary risk theory when individuals perceive a high secondary threat.     

A ‘No Blame’ Approach to Organizational Learning

In high‐reliability organizations (HROs) even minor errors can seriously hinder the very existence of the firm and the safety of employees and customers. Field studies have shown that HROs encourage the reporting of errors and near misses, exploiting these incidents to improve their operative processes. In this paper, we describe this practice as a ‘no blame’ approach to error management, and link it to learning theory, showing how no blame practices can enhance organizational learning. By taking a cognitive perspective of organizations, we draw on existing contributions and on a set of empirical case studies to discuss the characteristics of no blame practices, and their applicability in traditional, non‐HROs. Our findings show that, in exploiting information from error‐reporting, no blame practices are beneficial in environments where learning and reliability issues are particularly relevant. Empirical evidence suggests that a no blame approach can be extremely constructive for organizations that want to enhance their learning processes. We conclude that a no blame approach is a valuable way to achieve an organization that has flexibility and variability. However, no blame practices imply a set of organizational issues and costs that pose significant challenges to firms operating in non‐high‐reliability settings. The findings from our study contribute to the literature on HROs and organizational learning.     

Risk Analysis for U.S. Offshore Wind Farms: The Need for an Integrated Approach

Wind power is becoming an increasingly important part of the global energy portfolio, and there is growing interest in developing offshore wind farms in the United States to better utilize this resource. Wind farms have certain environmental benefits, notably near‐zero emissions of greenhouse gases, particulates, and other contaminants of concern. However, there are significant challenges ahead in achieving large‐scale integration of wind power in the United States, particularly offshore wind. Environmental impacts from wind farms are a concern, and these are subject to a number of on‐going studies focused on risks to the environment. However, once a wind farm is built, the farm itself will face a number of risks from a variety of hazards, and managing these risks is critical to the ultimate achievement of long‐term reductions in pollutant emissions from clean energy sources such as wind. No integrated framework currently exists for assessing risks to offshore wind farms in the United States, which poses a challenge for wind farm risk management. In this “Perspective”, we provide an overview of the risks faced by an offshore wind farm, argue that an integrated framework is needed, and give a preliminary starting point for such a framework to illustrate what it might look like. This is not a final framework; substantial work remains. Our intention here is to highlight the research need in this area in the hope of spurring additional research about the risks to wind farms to complement the substantial amount of on‐going research on the risks from wind farms.     

Risk Assessment Can Be a Game‐Changing Information Technology—But Too Often It Isn't

The printing press was a game‐changing information technology. Risk assessment could be also. At present, risk assessments are commonly used as one‐time decision aids: they provide justification for a particular decision, and afterwards usually sit on a shelf. However, when viewed as information technologies, their potential uses are much broader. Risk assessments: (1) are repositories of structured information and a medium for communication; (2) embody evaluative structures for setting priorities; (3) can preserve information over time and permit asynchronous communication, thus encouraging learning and adaptation; and (4) explicitly address uncertain futures. Moreover, because of their “what‐if” capabilities, risk assessments can serve as a platform for constructive discussion among parties that hold different values. The evolution of risk assessment in the nuclear industry shows how such attributes have been used to lower core‐melt risks substantially through improved templates for maintenance and more effective coordination with regulators (although risk assessment has been less commonly used in improving emergency‐response capabilities). The end result of this evolution in the nuclear industry has been the development of “living” risk assessments that are updated more or less in real time to answer even routine operational questions. Similar but untapped opportunities abound for the use of living risk assessments to reduce risks in small operational decisions as well as large policy decisions in other areas of hazard management. They can also help improve understanding of and communication about risks, and future risk assessment and management. Realization of these opportunities will require significant changes in incentives and active promotion by the risk analytic community.     

Context‐Specific,Scenario‐Based Risk Scales

Reacting to an emergency requires quick decisions under stressful and dynamic conditions. To react effectively, responders need to know the right actions to take given the risks posed by the emergency. While existing research on risk scales focuses primarily on decision making in static environments with known risks, these scales may be inappropriate for conditions where the decision maker's time and mental resources are limited and may be infeasible if the actual risk probabilities are unknown. In this article, we propose a method to develop context‐specific, scenario‐based risk scales designed for emergency response training. Emergency scenarios are used as scale points, reducing our dependence on known probabilities; these are drawn from the targeted emergency context, reducing the mental resources required to interpret the scale. The scale is developed by asking trainers/trainees to rank order a range of risk scenarios and then aggregating these orderings using a Kemeny ranking. We propose measures to assess this aggregated scale's internal consistency, reliability, and validity, and we discuss how to use the scale effectively. We demonstrate our process by developing a risk scale for subsurface coal mine emergencies and test the reliability of the scale by repeating the process, with some methodological variations, several months later.     

6 Three Perspectives on Team Learning

Abstract

The emergence of a research literature on team learning has been driven by at least two factors. First, longstanding interest in what makes organizational work teams effective leads naturally to questions about how members of newly formed teams learn to work together and how existing teams improve or adapt. Second, some have argued that teams play a crucial role in organizational learning. These interests have produced a growing and heterogeneous literature. Empirical studies of learning by small groups or teams present a variety of terms, concepts, and methods. This heterogeneity is both generative and occasionally confusing. We identify three distinct areas of research that provide insight into how teams learn to stimulate cross-area discussion and future research. We find that scholars have made progress in understanding how teams in general learn, and propose that future work should develop more precise and context-specific theories to help guide research and practice in disparate task and industry domains.     

Perception of Risk and the Attribution of Responsibility for Accidents

Accidents, one often hears, “happen”; we accept, and even expect, that they will be part of daily life. But in situations in which injury or death result, judgments of responsibility become critical. How might our perceptions of risk influence the ways in which we allocate responsibility for an accident? Drawing from attribution and risk perception theory, this study investigates how perceived controllability and desirability of risk, in addition to perceived danger and recreational risk‐taking, relate to attributions of responsibility for the cause of unintentional injury in a unique setting: U.S. national parks. Three parks, Mount Rainier, Olympic, and Delaware Water Gap, provide the setting for this survey‐based study, which considers how park visitors (N = 447) attribute responsibility for the cause of a hypothetical visitor accident. Results suggest that respondents tended to make more internal (i.e., related to characteristics of the victim), rather than external (i.e., related to characteristics of the park, or park management) attributions. As respondents viewed park‐related risk as controllable, they were more likely to attribute the cause of the accident to the victim. Moreover, among other significant variables, having experienced a similar accident predicted lower internal causal attribution. Opportunities for future research linking risk perception and attribution variables, as well as practical implications for the management of public outdoor settings, are presented.     

A Decision Support Tool to Compare Waterborne and Foodborne Infection and/or Illness Risks Associated with Climate Change

Climate change may impact waterborne and foodborne infectious disease, but to what extent is uncertain. Estimating climate‐change‐associated relative infection risks from exposure to viruses, bacteria, or parasites in water or food is critical for guiding adaptation measures. We present a computational tool for strategic decision making that describes the behavior of pathogens using location‐specific input data under current and projected climate conditions. Pathogen‐pathway combinations are available for exposure to norovirus, Campylobacter, Cryptosporidium, and noncholera Vibrio species via drinking water, bathing water, oysters, or chicken fillets. Infection risk outcomes generated by the tool under current climate conditions correspond with those published in the literature. The tool demonstrates that increasing temperatures lead to increasing risks for infection with Campylobacter from consuming raw/undercooked chicken fillet and for Vibrio from water exposure. Increasing frequencies of drought generally lead to an elevated infection risk of exposure to persistent pathogens such as norovirus and Cryptosporidium, but decreasing risk of exposure to rapidly inactivating pathogens, like Campylobacter. The opposite is the case with increasing annual precipitation; an upsurge of heavy rainfall events leads to more peaks in infection risks in all cases. The interdisciplinary tool presented here can be used to guide climate change adaptation strategies focused on infectious diseases.     

Institutionalized Ignorance as a Precondition for Rational Risk Expertise

The present case study seeks to explain the conditions for experts’ rational risk perception by analyzing the institutional contexts that constitute a field of food safety expertise in Denmark. The study highlights the role of risk reporting and how contextual factors affect risk reporting from the lowest organizational level, where concrete risks occur, to the highest organizational level, where the body of professional risk expertise is situated. The article emphasizes the role of knowledge, responsibility, loyalty, and trust as risk‐attenuation factors and concludes by suggesting that the preconditions for the expert's rationality may rather be a lack of risk‐specific knowledge due to poor risk reporting than a superior level of risk knowledge.     

Geographic Distributions of Extreme Weather Risk Perceptions in the United States

Weather and climate disasters pose an increasing risk to life and property in the United States. Managing this risk requires objective information about the nature of the threat and subjective information about how people perceive it. Meteorologists and climatologists have a relatively firm grasp of the historical objective risk. For example, we know which parts of the United States are most likely to experience drought, heat waves, flooding, snow or ice storms, tornadoes, and hurricanes. We know less about the geographic distribution of the perceived risks of meteorological events and trends. Do subjective perceptions align with exposure to weather risks? This question is difficult to answer because analysts have yet to develop a comprehensive and spatially consistent methodology for measuring risk perceptions across geographic areas in the United States. In this project, we propose a methodology that uses multilevel regression and poststratification to estimate extreme weather and climate risk perceptions by geographic area (i.e., region, state, forecast area, and county). Then we apply the methodology using data from three national surveys (n = 9,542). This enables us to measure, map, and compare perceptions of risk from multiple weather hazards in geographic areas across the country.     

Improving Flood Risk Communication by Focusing on Prevention‐Focused Motivation

This article proposes an approach to flood risk communication that gives particular emphasis to the distinction between prevention and promotion motivation. According to E. Tory Higgins, the promotion system and the prevention system are assumed to coexist in every person, but one or the other may be temporarily or chronically more accessible. These insights have far‐reaching implications for our understanding of people's reasoning about risks. Flood risk communication framed in terms of prevention involves the notions of chance and harm, woven into a story about particular events that necessitate decisions to be more careful about safety issues and protect one's family and oneself from danger. The article describes how the insights worked out in practice, using a flood risk communication experiment among a sample from the general population in a highly populated river delta of the Netherlands. It had a posttest‐only control group design (n = 2,302). The results showed that risk communication had a large effect on the participants’ responses and that this effect was higher among chronic prevention‐focused people than among others. Any information that increased the fit between a prevention‐framed message and a person's chronic prevention motivation produced stronger situationally induced, prevention‐focused responses. This may significantly improve communication about risks. In contrast, the notion of water city projects, featuring waterside living, had more appeal to promotion‐focused people.     

Does Size Matter? A Study of Risk Perceptions of Global Population Growth

The global human population now exceeds 7 billion and is projected to reach 10 billion around 2060. While population growth has been associated with certain benefits (e.g., economies of scale, technological advancements), theoretical models, probabilistic projections, and empirical evidence also indicate that this growth could increase the likelihood of many adverse events (e.g., climate change, resource shortages) and the impact of these events, as more people are exposed to the outcomes. While concerns about these issues are well‐documented in the academic literature, there is little evidence concerning the public's perceptions of the risks associated with global population growth (GPG) and how these perceptions are likely to influence related decisions. To address these issues, we conducted a U.K.‐based study that examined respondents’ risk perceptions of GPG, their willingness to embrace mitigation/precautionary behaviors, and reasons for variations in these two factors. We found that GPG is perceived as a moderate‐to‐high risk, with concerns about the increased likelihood of resource shortages, ecological damage, and violent conflict being foremost. Respondents believed that the worst effects of GPG would arrive around 2050 and would be experienced by the world's poorest people. Respondents who perceived greater levels of risk from GPG were generally those who indicated a greater willingness to embrace mitigation behaviors (e.g., reduce resource consumption) and preventative actions (e.g., support political action to limit growth). We discuss how our findings might be utilized to better manage the potential challenges associated with GPG and we suggest several directions for further research.     

Overcoming Learning Aversion in Evaluating and Managing Uncertain Risks

Decision biases can distort cost‐benefit evaluations of uncertain risks, leading to risk management policy decisions with predictably high retrospective regret. We argue that well‐documented decision biases encourage learning aversion, or predictably suboptimal learning and premature decision making in the face of high uncertainty about the costs, risks, and benefits of proposed changes. Biases such as narrow framing, overconfidence, confirmation bias, optimism bias, ambiguity aversion, and hyperbolic discounting of the immediate costs and delayed benefits of learning, contribute to deficient individual and group learning, avoidance of information seeking, underestimation of the value of further information, and hence needlessly inaccurate risk‐cost‐benefit estimates and suboptimal risk management decisions. In practice, such biases can create predictable regret in selection of potential risk‐reducing regulations. Low‐regret learning strategies based on computational reinforcement learning models can potentially overcome some of these suboptimal decision processes by replacing aversion to uncertain probabilities with actions calculated to balance exploration (deliberate experimentation and uncertainty reduction) and exploitation (taking actions to maximize the sum of expected immediate reward, expected discounted future reward, and value of information). We discuss the proposed framework for understanding and overcoming learning aversion and for implementing low‐regret learning strategies using regulation of air pollutants with uncertain health effects as an example.     

Systems‐Based Guiding Principles for Risk Modeling,Planning, Assessment,Management, and Communication

This article is grounded on the premise that the complex process of risk assessment, management, and communication, when applied to systems of systems, should be guided by universal systems‐based principles. It is written from the perspective of systems engineering with the hope and expectation that the principles introduced here will be supplemented and complemented by principles from the perspectives of other disciplines. Indeed, there is no claim that the following 10 guiding principles constitute a complete set; rather, the intent is to initiate a discussion on this important subject that will incrementally lead us to a more complete set of guiding principles. The 10 principles are as follows: First Principle: Holism is the common denominator that bridges risk analysis and systems engineering. Second Principle: The process of risk modeling, assessment, management, and communication must be systemic and integrated. Third Principle: Models and state variables are central to quantitative risk analysis. Fourth Principle: Multiple models are required to represent the essence of the multiple perspectives of complex systems of systems. Fifth Principle: Meta‐modeling and subsystems integration must be derived from the intrinsic states of the system of systems. Sixth Principle: Multiple conflicting and competing objectives are inherent in risk management. Seventh Principle: Risk analysis must account for epistemic and aleatory uncertainties. Eighth Principle: Risk analysis must account for risks of low probability with extreme consequences. Ninth Principle: The time frame is central to quantitative risk analysis. Tenth Principle: Risk analysis must be holistic, adaptive, incremental, and sustainable, and it must be supported with appropriate data collection, metrics with which to measure efficacious progress, and criteria on the basis of which to act. The relevance and efficacy of each guiding principle is demonstrated by applying it to the U.S. Federal Aviation Administration complex Next Generation (NextGen) system of systems.