Changes in the Factors Influencing Public Acceptance of Nuclear Power Generation in Japan Since the 2011 Fukushima Daiichi Nuclear Disaster

Public support for nuclear power generation has decreased in Japan since the Fukushima Daiichi nuclear accident in March 2011. This study examines how the factors influencing public acceptance of nuclear power changed after this event. The influence factors examined are perceived benefit, perceived risk, trust in the managing bodies, and pro‐environmental orientation (i.e., new ecological paradigm). This study is based on cross‐sectional data collected from two online nationwide surveys: one conducted in November 2009, before the nuclear accident, and the other in October 2011, after the accident. This study's target respondents were residents of Aomori, Miyagi, and Fukushima prefectures in the Tohoku region of Japan, as these areas were the epicenters of the Great East Japan Earthquake and the locations of nuclear power stations. After the accident, trust in the managing bodies was found to have a stronger influence on perceived risk, and pro‐environmental orientation was found to have a stronger influence on trust in the managing bodies; however, perceived benefit had a weaker positive influence on public acceptance. We also discuss the theoretical and practical implications of these findings.     

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.     

Integrating Behavioral Science with Human Factors to Address Process Safety

ABSTRACT

Applying the science of human factors to eliminate error across all aspects of process design, management, operation, and maintenance has been a focus in the process safety area for many years. Human error has been attributed as a major cause of many high profile catastrophic accidents around the world. These accidents have resulted in national and international attention, which has led to a focus on improving organizational capabilities, systems, and in many cases, governmental regulations around human factors. This article provides a review of the field of human factors highlighting various topics in the literature, and introduces governmental regulatory bodies currently engaging organizations in a scientific approach to human factors. Finally, the need for integrating behavioral science methodologies with human factors is addressed. This is done with specific focus on how Organizational Behavior Management methodologies can work in concert with human factors to optimize process safety.     

In Search of Perfect Foresight? Policy Bias,Management of Unknowns,and What Has Changed in Science Policy Since the Tohoku Disaster

The failure to foresee the catastrophic earthquakes, tsunamis, and nuclear accident of 2011 has been perceived by many in Japan as a fundamental shortcoming of modern disaster risk science. Hampered by a variety of cognitive and institutional biases, the conventional disaster risk management planning based on the “known risks” led to the cascading failures of the interlinked disaster risk management (DRM) apparatus. This realization led to a major rethinking in the use of science for policy and the incorporations of lessons learned in the country's new DRM policy. This study reviews publicly available documents on expert committee discussions and scientific articles to identify what continuities and changes have been made in the use of scientific knowledge in Japanese risk management. In general, the prior influence of cognitive bias (e.g., overreliance on documented hazard risks) has been largely recognized, and increased attention is now being paid to the incorporation of less documented but known risks. This has led to upward adjustments in estimated damages from future risks and recognition of the need for further strengthening of DRM policy. At the same time, there remains significant continuity in the way scientific knowledge is perceived to provide sufficient and justifiable grounds for the development and implementation of DRM policy. The emphasis on “evidence‐based policy” in earthquake and tsunami risk reduction measures continues, despite the critical reflections of a group of scientists who advocate for a major rethinking of the country's science‐policy institution respecting the limitations of the current state science.     

Examining Public Trust in Risk‐Managing Organizations After a Major Disaster

This research investigates the public's trust in risk‐managing organizations after suffering serious damage from a major disaster. It is natural for public trust to decrease in organizations responsible for mitigating the damage. However, what about trust in organizations that address hazards not directly related to the disaster? Based on the results of surveys conducted by a national institute, the Japanese government concluded, in a White Paper on Science and Technology, that the public's trust in scientists declined overall after the 2011 Tohoku Earthquake. Because scientists play a key role in risk assessment and risk management in most areas, one could predict that trust in risk‐managing organizations overall would decrease after a major disaster. The methodology of that survey, however, had limitations that prevented such conclusions. For this research, two surveys were conducted to measure the public's trust in risk‐managing organizations regarding various hazards, before and after the Tohoku Earthquake (n = 1,192 in 2008 and n = 1,138 in 2012). The results showed that trust decreased in risk‐managing organizations that deal with earthquakes and nuclear accidents, whereas trust levels related to many other hazards, especially in areas not touched by the Tohoku Earthquake, remained steady or even increased. These results reject the assertion that distrust rippled through all risk‐managing organizations. The implications of this research are discussed, with the observation that this result is not necessarily gratifying for risk managers because high trust sometimes reduces public preparedness for disasters.     

Who by Accident? The Social Morphology of Car Accidents

Prior studies in the sociology of accidents have shown that different social groups have different rates of accident involvement. This study extends those studies by implementing Bourdieu's relational perspective of social space to systematically explore the homology between drivers’ social characteristics and their involvement in specific types of motor vehicle accident. Using a large database that merges official Israeli road‐accident records with socioeconomic data from two censuses, this research maps the social order of road accidents through multiple correspondence analysis. Extending prior studies, the results show that different social groups indeed tend to be involved in motor vehicle accidents of different types and severity. For example, we find that drivers from low socioeconomic backgrounds are overinvolved in severe accidents with fatal outcomes. The new findings reported here shed light on the social regularity of road accidents and expose new facets in the social organization of death.     

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.     

Bridging Practice and Theory: A Design Science Approach

Despite ambitious efforts in various fields of research over multiple decades, the goal of making academic research relevant to the practitioner remains elusive: theoretical and academic research interests do not seem to coincide with the interests of managerial practice. This challenge is more fundamental than knowledge transfer, it is one of diverging knowledge interests and means of knowledge production. In this article, we look at this fundamental challenge through the lens of design science, which is an approach aimed primarily at discovery and problem solving as opposed to accumulation of theoretical knowledge. We explore in particular the ways in which problem‐solving research and theory‐oriented academic research can complement one another. In operations management (OM) research, recognizing and building on this complementarity is especially crucial, because problem‐solving–oriented research produces the very artifacts (e.g., technologies) that empirical OM research subsequently evaluates in an attempt to build explanatory theory. It is indeed the practitioner—not the academic scientist—who engages in basic research in OM. This idiosyncrasy prompts the question: how can we enhance the cross‐fertilization between academic research and research practice to make novel theoretical insights and practical relevance complementary? This article proposes a design science approach to bridge practice to theory rather than theory to practice.     

Knowledge Management for the Entrepreneurial Venture

We synthesize research from operations management, entrepreneurship, organizational science, and strategy to investigate the performance‐enhancing benefits of knowledge management activities throughout the entrepreneurial process of a high‐tech venture from idea conception to commercialization. We adopt a dynamic learning perspective of entrepreneurship to understand how knowledge management activities change throughout four phases of the venture's life cycle. We introduce a framework that identifies a set of knowledge‐based capabilities that enhance the entrepreneurial venture's success. In the context of the first phase, we discuss knowledge as a key driver of entrepreneurial alertness and creativity, both of which impact the quality and quantity of opportunities and innovations discovered. Second, we describe how knowledge enables the entrepreneur to make decisions under uncertainty such as determining which opportunity to pursue. For Phase 3 of the life cycle, we explore the challenges of managing knowledge during the development of the product or technology including the trade‐off between exploration and exploitation. In the final phase, we explore how knowledge impacts the market entry decision, survival, and the value captured at commercialization. We conclude the article with suggestions for future research.     

How a Nuclear Power Plant Accident Influences Acceptance of Nuclear Power: Results of a Longitudinal Study Before and After the Fukushima Disaster

Major nuclear accidents, such as the recent accident in Fukushima, Japan, have been shown to decrease the public's acceptance of nuclear power. However, little is known about how a serious accident affects people's acceptance of nuclear power and the determinants of acceptance. We conducted a longitudinal study (N= 790) in Switzerland: one survey was done five months before and one directly after the accident in Fukushima. We assessed acceptance, perceived risks, perceived benefits, and trust related to nuclear power stations. In our model, we assumed that both benefit and risk perceptions determine acceptance of nuclear power. We further hypothesized that trust influences benefit and risk perceptions and that trust before a disaster relates to trust after a disaster. Results showed that the acceptance and perceptions of nuclear power as well as its trust were more negative after the accident. In our model, perceived benefits and risks determined the acceptance of nuclear power stations both before and after Fukushima. Trust had strong effects on perceived benefits and risks, at both times. People's trust before Fukushima strongly influenced their trust after the accident. In addition, perceived benefits before Fukushima correlated with perceived benefits after the accident. Thus, the nuclear accident did not seem to have changed the relations between the determinants of acceptance. Even after a severe accident, the public may still consider the benefits as relevant, and trust remains important for determining their risk and benefit perceptions. A discussion of the benefits of nuclear power seems most likely to affect the public's acceptance of nuclear power, even after a nuclear accident.     

Resilience of Cyber Systems with Over‐ and Underregulation

Recent cyber attacks provide evidence of increased threats to our critical systems and infrastructure. A common reaction to a new threat is to harden the system by adding new rules and regulations. As federal and state governments request new procedures to follow, each of their organizations implements their own cyber defense strategies. This unintentionally increases time and effort that employees spend on training and policy implementation and decreases the time and latitude to perform critical job functions, thus raising overall levels of stress. People's performance under stress, coupled with an overabundance of information, results in even more vulnerabilities for adversaries to exploit. In this article, we embed a simple regulatory model that accounts for cybersecurity human factors and an organization's regulatory environment in a model of a corporate cyber network under attack. The resulting model demonstrates the effect of under‐ and overregulation on an organization's resilience with respect to insider threats. Currently, there is a tendency to use ad‐hoc approaches to account for human factors rather than to incorporate them into cyber resilience modeling. It is clear that using a systematic approach utilizing behavioral science, which already exists in cyber resilience assessment, would provide a more holistic view for decisionmakers.     

On “Black Swans” and “Perfect Storms”: Risk Analysis and Management When Statistics Are Not Enough

Two images, “black swans” and “perfect storms,” have struck the public's imagination and are used—at times indiscriminately—to describe the unthinkable or the extremely unlikely. These metaphors have been used as excuses to wait for an accident to happen before taking risk management measures, both in industry and government. These two images represent two distinct types of uncertainties (epistemic and aleatory). Existing statistics are often insufficient to support risk management because the sample may be too small and the system may have changed. Rationality as defined by the von Neumann axioms leads to a combination of both types of uncertainties into a single probability measure—Bayesian probability—and accounts only for risk aversion. Yet, the decisionmaker may also want to be ambiguity averse. This article presents an engineering risk analysis perspective on the problem, using all available information in support of proactive risk management decisions and considering both types of uncertainty. These measures involve monitoring of signals, precursors, and near‐misses, as well as reinforcement of the system and a thoughtful response strategy. It also involves careful examination of organizational factors such as the incentive system, which shape human performance and affect the risk of errors. In all cases, including rare events, risk quantification does not allow “prediction” of accidents and catastrophes. Instead, it is meant to support effective risk management rather than simply reacting to the latest events and headlines.     

A Look at State‐Level Risk Assessment in the United States: Making Decisions in the Absence of Federal Risk Values

State environmental agencies in the United States are charged with making risk management decisions that protect public health and the environment while managing limited technical, financial, and human resources. Meanwhile, the federal risk assessment community that provides risk assessment guidance to state agencies is challenged by the rapid growth of the global chemical inventory. When chemical toxicity profiles are unavailable on the U.S. Environmental Protection Agency's Integrated Risk Information System or other federal resources, each state agency must act independently to identify and select appropriate chemical risk values for application in human health risk assessment. This practice can lead to broad interstate variation in the toxicity values selected for any one chemical. Within this context, this article describes the decision‐making process and resources used by the federal government and individual U.S. states. The risk management of trichloroethylene (TCE) in the United States is presented as a case study to demonstrate the need for a collaborative approach among U.S. states toward identification and selection of chemical risk values while awaiting federal risk values to be set. The regulatory experience with TCE is contrasted with collaborative risk science models, such as the European Union's efforts in risk assessment harmonization. Finally, we introduce State Environmental Agency Risk Collaboration for Harmonization, a free online interactive tool designed to help to create a collaborative network among state agencies to provide a vehicle for efficiently sharing information and resources, and for the advancement of harmonization in risk values used among U.S. states when federal guidance is unavailable.     

Major Accidents (Gray Swans) Likelihood Modeling Using Accident Precursors and Approximate Reasoning

Compared to the remarkable progress in risk analysis of normal accidents, the risk analysis of major accidents has not been so well‐established, partly due to the complexity of such accidents and partly due to low probabilities involved. The issue of low probabilities normally arises from the scarcity of major accidents’ relevant data since such accidents are few and far between. In this work, knowing that major accidents are frequently preceded by accident precursors, a novel precursor‐based methodology has been developed for likelihood modeling of major accidents in critical infrastructures based on a unique combination of accident precursor data, information theory, and approximate reasoning. For this purpose, we have introduced an innovative application of information analysis to identify the most informative near accident of a major accident. The observed data of the near accident were then used to establish predictive scenarios to foresee the occurrence of the major accident. We verified the methodology using offshore blowouts in the Gulf of Mexico, and then demonstrated its application to dam breaches in the United Sates.     

Kurt Lewin's Field Theory: A Review and Re‐evaluation

Field theory was central to Kurt Lewin's work yet, after his death, interest in it declined significantly until the 1990s when a variant, force field analysis, became widely used. This paper examines the origins, purpose and continuing relevance of field theory. It especially looks at the influences of gestalt psychology, topology and Ernst Cassirer's philosophy of science on its development. It argues that Lewin's attempt to replace conventional topology with his own Lewinian mathematics‐based topology in pursuit of scientific rigour resulted in the undermining of its relevance. The paper also compares force field analysis with Lewin's original conception of field theory and shows that it has significant weaknesses in terms of rigour. It concludes that a return to Lewin's original conception of field theory, based on gestalt psychology and conventional topology, can provide academics and practitioners with a valuable and much‐needed approach to managing change.     

Human Factors Analysis for Maritime Accidents Based on a Dynamic Fuzzy Bayesian Network

Human factors are widely regarded to be highly contributing factors to maritime accident prevention system failures. The conventional methods for human factor assessment, especially quantitative techniques, such as fault trees and bow-ties, are static and cannot deal with models with uncertainty, which limits their application to human factors risk analysis. To alleviate these drawbacks, in the present study, a new human factor analysis framework called multidimensional analysis model of accident causes (MAMAC) is introduced. MAMAC combines the human factors analysis and classification system and business process management. In addition, intuitionistic fuzzy set theory and Bayesian Network are integrated into MAMAC to form a comprehensive dynamic human factors analysis model characterized by flexibility and uncertainty handling. The proposed model is tested on maritime accident scenarios from a sand carrier accident database in China to investigate the human factors involved, and the top 10 most highly contributing primary events associated with the human factors leading to sand carrier accidents are identified. According to the results of this study, direct human factors, classified as unsafe acts, are not a focus for maritime investigators and scholars. Meanwhile, unsafe preconditions and unsafe supervision are listed as the top two considerations for human factors analysis, especially for supervision failures of shipping companies and ship owners. Moreover, potential safety countermeasures for the most highly contributing human factors are proposed in this article. Finally, an application of the proposed model verifies its advantages in calculating the failure probability of accidents induced by human factors.     

Working around the Barriers to Creating and Sharing Knowledge in Capital Goods Projects: the Client's Perspective*

The article considers knowledge management issues from the client's perspective. In the example presented, a sludge treatment centre procured by Northumbrian Water Ltd (NWL), the task faced by the client was to manage knowledge in a context where the core technology being procured was new and resulted in the need for new knowledge to be created and shared both pre‐ and post‐delivery. In exploring these issues, the article reveals the problems of (and some solutions to) managing knowledge across the project life‐cycle and between different groups, where the motivation for generating and sharing knowledge was not the same for all participants.     

Operations Risk Management: Overview of Paul Kleindorfer's Contributions

This paper reviews Paul Kleindorfer's contributions to Operations Management (OM), with a special focus on his research on risk management. An annotated bibliography of selected other contributions reviews the breadth of topics that have occupied Kleindorfer's research attention over his now 45 + years of research. These include optimal control theory, scheduling theory, decision sciences, investment planning and peak load pricing, plus a number of important applications in network industries and insurance. In the area of operations risk management, we review recent work that Kleindorfer and his colleagues in the Wharton Risk Center have undertaken on environmental management and operations, focusing on process safety and environmental risks in the chemical industry. This work is directly related to Kleindorfer's work in the broader area of “sustainable operations”, which he, Kal Singhal and Luk Van Wassenhove recently surveyed as part of the new initiative at POMS to encompass sustainable management practices within the POMS community. Continuing in the area of supply chain risks, the paper reviews Kleindorfer's contributions to the development of an integrated framework for contracting and risk hedging for supply management. The emphasis on alignment of pricing, performance and risk management in this framework is presaged in the work undertaken by Kleindorfer and his co‐authors in the 1980s on after‐sales support services for high‐technology products. This work on supply chain risk, and its successors, is reviewed here in light of its growing importance in managing the unbundled and global supply chains characteristic of the new economy.     

Valuation of childhood risk reduction: the importance of age, risk preferences, and perspective.

This article explores two problems analysts face in determining how to estimate values for children's health and safety risk reductions. The first addresses the question: Do willingness‐to‐pay estimates for health risk changes differ across children and adults and, if so, how? To answer this question, the article first examines the potential effects of age and risk preferences on willingness to pay. A summary of the literature reporting empirical evidence of differences between willingness to pay for adult health and safety risk reductions and willingness to pay for health and safety risk reductions in children is also provided. The second dimension of the problem is a more fundamental issue: Whose perspective is relevant when valuing children's health effects—society's, children's, adults‐as‐children, or parents'? Each perspective is considered, followed ultimately by the conclusion that adopting a parental perspective through an intrahousehold allocation model seems closest to meeting the needs of the estimation problem at hand. A policy example in which the choice of perspective affects the outcome of a regulatory benefit‐cost analysis rounds out the article and emphasizes the importance of perspective.     

“What—Me Worry?”1“Why So Serious?”:2 A Personal View on the Fukushima Nuclear Reactor Accidents

Infrequently, it seems that a significant accident precursor or, worse, an actual accident, involving a commercial nuclear power reactor occurs to remind us of the need to reexamine the safety of this important electrical power technology from a risk perspective. Twenty‐five years since the major core damage accident at Chernobyl in the Ukraine, the Fukushima reactor complex in Japan experienced multiple core damages as a result of an earthquake‐induced tsunami beyond either the earthquake or tsunami design basis for the site. Although the tsunami itself killed tens of thousands of people and left the area devastated and virtually uninhabitable, much concern still arose from the potential radioactive releases from the damaged reactors, even though there was little population left in the area to be affected. As a lifelong probabilistic safety analyst in nuclear engineering, even I must admit to a recurrence of the doubt regarding nuclear power safety after Fukushima that I had experienced after Three Mile Island and Chernobyl. This article is my attempt to “recover” my personal perspective on acceptable risk by examining both the domestic and worldwide history of commercial nuclear power plant accidents and attempting to quantify the risk in terms of the frequency of core damage that one might glean from a review of operational history.