Relative Risk Perception for Terrorism: Implications for Preparedness and Risk Communication

Terrorism presents a significant risk that is often approached at public policy, infrastructure, or emergency management level. Public perceptions of the likelihood of terrorist events, and how this may relate to individual preparedness, are not always extensively examined. The tendency to think that negative events are less likely to happen to oneself than to the average person is known as optimism bias. Optimism bias is relevant to perceptions of terrorism, because it is thought to be related to a reduction in precaution use. Using an online survey of 164 participants, this study aimed to determine whether Sydney residents thought they had a lower likelihood of experiencing terrorist events than other Australians. Significant optimism bias was observed for witnessing terrorist events, but not for personally experiencing terrorist events. In addition, Sydney residents tended to think that terrorist attacks were more likely to occur in Sydney than another major Australian city in the next five years. At the same time, household and workplace preparedness for terrorism was quite low, as was awareness of emergency strategies in the central business district. Perceptions of high likelihood of terrorism happening in one's own city, yet low preparedness present a challenge for risk communication and emergency management strategies. The diversity of possible terrorist targets, and the simple plans that can moderate the effects of a disaster may need to be emphasized in future anti‐terrorism initiatives.     

Chemical and biological terrorism: planning for the worst

Preparing for a chemical or biological terrorist event has recently become an intense area of focus for emergency health planners in every state and city in America. Many of these individuals believe that a chemical or biological terrorist event is likely in the near future and they raise concerns about the readiness of our nation's health system to rapidly identify and manage a disaster of this magnitude. In both types of events, physician leadership is essential to reduce death and disability and restore public order. Several policy issues need to be addressed in this complex issue. Physician executives play a key role in preparing the health system to respond to this type of disaster.     

Contemporary Terrorism: Risk Perception in the London Options Market

Previous studies have a demonstrated a linkage between terrorist attacks and the operation of financial markets. This article focuses on terrorist events carried out over the last five years and examines how they have been perceived among participants on the London financial market. Data from the London options market suggest a high degree of sensitivity to these events. We argue that this sensitivity reveals a vulnerability in the financial markets should the recent trends in terrorist activity continue.     

Fusion of Intelligence Information: A Bayesian Approach

The attack that occurred on September 11, 2001 was, in the end, the result of a failure to detect and prevent the terrorist operations that hit the United States. The U.S. government thus faces at this time the daunting tasks of first, drastically increasing its ability to obtain and interpret different types of signals of impending terrorist attacks with sufficient lead time and accuracy, and second, improving its ability to react effectively. One of the main challenges is the fusion of information, from different sources (U.S. or foreign), and of different types (electronic signals, human intelligence. etc.). Fusion thus involves two very distinct and separate issues: communications, i.e., ensuring that the different U.S. and foreign intelligence agencies communicate all relevant and accurate information in a timely fashion and, perhaps more difficult, merging the content of signals, some "sharp" and some "fuzzy," some dependent and some independent into useful information. The focus of this article is on the latter issue, and on the use of the results. In this article, I present a classic probabilistic Bayesian model sometimes used in engineering risk analysis, which can be helpful in the fusion of information because it allows computation of the posterior probability of an event given its prior probability (before the signal is observed) and the quality of the signal characterized by the probabilities of false positive and false negative. Experience suggests that the nature of these errors has been sometimes misunderstood; therefore, I discuss the validity of several possible definitions.     

Media Exposure to Terrorism and Perception of Immigrants as a Threat: The Role of Emotional Intelligence and Psychophysiological Self-Regulation

To better understand how media exposure to terrorism-related images can lead to perceiving immigrants as more threatening, in the present study we manipulated participants’ exposure to media coverage of terrorist attacks and investigated how this may influence people's perception of Arab immigrants. Considering the important role of regulatory abilities when facing stressful events like terrorist attacks, we measured individual differences in both trait emotional intelligence and resting heart rate variability (HRV). Results showed that participants perceived Arab immigrants as more threatening in the media exposure condition than in the control condition. Importantly, there were moderating effects of both trait emotional intelligence and HRV. People with lower trait emotional intelligence or lower HRV at rest felt more threatened in the media exposure condition compared to the control condition, whereas this effect was not observed among participants with higher trait emotional intelligence or higher resting HRV. The present study highlights some of the complexities related to how media exposure to terrorism-related images influences people's reactions to, and evaluations of, an outgroup that is related to the perpetrators of the attacks.     

Does exposure to a traumatic event make organizations resilient?

Why do some organizations bounce-back from traumatic events more quickly than others? While the research on organizations offers extensive insights on recovery from economic or technological shocks, there is limited understanding of how organizations recover from life-threatening events such as terrorist attacks. In this study, we build on the research on resilience and argue that organizational recovery from a traumatic event is informed by the perception of threat. Higher perception of threat increases inter-organizational collaboration and the care associated with the deployment of slack as well as to learning. We tested our arguments with a sample of US and non-US firms before and after the 9/11 terrorist attacks and found that, due to spatial proximity, US firms’ higher perception of threat led to a larger increase in the frequency of inter-organizational alliances than that of non-US firms. This preference was more frequently directed towards local partners and demonstrated a distinct emphasis on slack and learning. Contrary to conventional wisdom, our findings suggest that organizational resilience in the face of a traumatic event benefits not from immunity but from spatial proximity to the threat. Proximity increases the perception of threat, and with it, the impetus for adaptation.     

Cross‐Milieu Terrorist Collaboration: Using Game Theory to Assess the Risk of a Novel Threat

This article uses a game‐theoretic approach to analyze the risk of cross‐milieu terrorist collaboration—the possibility that, despite marked ideological differences, extremist groups from very different milieus might align to a degree where operational collaboration against Western societies becomes possible. Based upon theoretical insights drawn from a variety of literatures, a bargaining model is constructed that reflects the various benefits and costs for terrorists’ collaboration across ideological milieus. Analyzed in both sequential and simultaneous decision‐making contexts and through numerical simulations, the model confirms several theoretical arguments. The most important of these is that although likely to be quite rare, successful collaboration across terrorist milieus is indeed feasible in certain circumstances. The model also highlights several structural elements that might play a larger role than previously recognized in the collaboration decision, including that the prospect of nonmaterial gains (amplification of terror and reputational boost) plays at least as important a role in the decision to collaborate as potential increased capabilities does. Numerical simulation further suggests that prospects for successful collaboration over most scenarios (including operational) increase when a large, effective Islamist terrorist organization initiates collaboration with a smaller right‐wing group, as compared with the other scenarios considered. Although the small number of historical cases precludes robust statistical validation, the simulation results are supported by existing empirical evidence of collaboration between Islamists and right‐ or left‐wing extremists. The game‐theoretic approach, therefore, provides guidance regarding the circumstances under which such an unholy alliance of violent actors is likely to succeed.     

Improving Risk-Based Decision Making for Terrorism Applications

How can we best allocate limited defensive resources to reduce terrorism risks? Dillon et al.'s Antiterrorism Risk-Based Decision Aid (ARDA) system provides a useful point of departure for addressing this crucial question by exhibiting a real-world system that calculates risk reduction scores for different portfolios of risk-reducing countermeasures and using them to rank-order different possible risk mitigation alternatives for Navy facilities. This comment points out some potential limitations of any scoring system that does not take into account risk externalities, interdependencies among threats, uncertainties that are correlated across targets, and attacker responses to alternative allocations of defensive resources. In at least some simple situations, allocations based on risk reduction scores and comparisons can inadvertently increase risks by providing intelligent attackers with valuable information, or they can fail to reduce risks as effectively as nonscoring, optimization-based approaches. These limitations of present scoring methods present exciting technical challenges and opportunities for risk analysts to develop improved methods for protecting facilities and infrastructure against terrorist threats.     

Risk Analysis of Terrorist Attacks

A quantitative probabilistic/systems analysis model is described which is useful for allocating resources to safeguard valuable documents or materials in either a fixed-site facility or a moving convoy against an overt terrorist attack. The model is also useful for ranking the sensitive areas at a site according to their survivability of a given hypothesized terrorist attempt. To compare various defense strategies and security configurations, the probability of a successful terrorist activity is computed based on event tree models of the site/security configuration. This calculation incorporates a realistic engagement model (in the event a guard force engages the terrorists prior to completion of their objective) and information on barrier penetration times (for example, distribution of the time to defeat a chain link fence or vault door, traverse an open area, and so forth). Two security analyses are described to illustrate the methodology. One example considers a terrorist attack on a convoy transporting a missile from a storage to a launch facility. The second example involves an attack on a munitions storage facility.     

Adaptive Management: A Paradigm for Remediation of Public Facilities Following a Terrorist Attack

Terrorist actions are aimed at maximizing harm (health, psychological, economical, and political) through the combined physical impacts of the act and fear. Immediate and effective response to a terrorist act is critical to limit human and environmental harm, effectively restore facility function, and maintain public confidence. Though there have been terrorist attacks in public facilities that we have learned from, overall our experiences in restoration of public facilities following a terrorist attack are limited. Restoration of public facilities following a release of a hazardous material is inherently far more complex than in industrial settings and has many unique technical, economic, social, and political challenges. For example, there may be a great need to quickly restore the facility to full operation and allow public access even though it was not designed for easy or rapid restoration, and critical information is needed for quantitative risk assessment and effective restoration must be anticipated to be incomplete and uncertain. Whereas present planning documents have substantial linearity in their organization, the “adaptive management” paradigm provides a constructive parallel paradigm for restoration of public facilities that anticipates and plans for uncertainty, inefficiencies, and stakeholder participation. Adaptive management grew out of the need to manage and restore natural resources in highly complex and changing environments with limited knowledge about causal relationships and responses to restoration actions. Similarities between natural resource management and restoration of a public facility after a terrorist attack suggest that integration of adaptive management principles explicitly into restoration processes will result in substantially enhanced and flexible responses necessary to meet the uncertainties of potential terrorist attacks.     

Terrorist Population Dynamics Model

A system that includes a number of terrorist cells is considered. The cells can consist of one or more terrorists. The current number of terrorist cells is further denoted by N(t), where t is a current time counted from any appropriate origin. The objective is to find the evolution of the system in terms of N(t) and some interpretable parameters, such as the initial number of the terrorist cells N0=N(0), the cell disabling rate constant lambda (or the cell half-life t1/2), and the rate of formation of new cells P. The cost-effectiveness analysis, performed in the framework of the model, reveals that the effectiveness of disabling a terrorist cell is getting worse after 2-3 half-lives of a cell, which shows that if the anti-terrorist actions have not reached their goal during that time, the respective policy should be considered for revision, using the risk assessment consideration. Another important issue raised concerns balancing the efforts related to counterterrorism actions inside the system and the efforts protecting its borders. The respective data analysis is suggested and illustrated using simulated data.     

基于双层规划的反恐应急设施选址模型及算法

恐怖袭击常以人流密集地区的平民作为袭击目标，并存在突发性和随机性等特点，极易造成严重的袭击后果。通过反恐应急设施的合理布局可以缩短救援人员和物资的到达时间，从而减轻袭击后果。首先，对反恐应急设施选址问题进行描述，并将其构造为一类离散双层规划模型。其中，上层规划是关于政府选址的0-1规划问题，下层规划则是关于恐怖分子袭击目标选择的0-1规划问题。其次，结合模型和问题的特征设计算法，利用分支定界算法实现上层选址变量的隐枚举，同时通过下层问题的求解来确定上下界并判断是否满足分枝或剪枝的条件。最后，结合南疆地区的交通拓扑网络进行算例分析，结果证明有效的选址方案可以大大降低袭击损失。     

Benchmark Analysis for Quantifying Urban Vulnerability to Terrorist Incidents

We describe a quantitative methodology to characterize the vulnerability of U.S. urban centers to terrorist attack, using a place-based vulnerability index and a database of terrorist incidents and related human casualties. Via generalized linear statistical models, we study the relationships between vulnerability and terrorist events, and find that our place-based vulnerability metric significantly describes both terrorist incidence and occurrence of human casualties from terrorist events in these urban centers. We also introduce benchmark analytic technologies from applications in toxicological risk assessment to this social risk/vulnerability paradigm, and use these to distinguish levels of high and low urban vulnerability to terrorism. It is seen that the benchmark approach translates quite flexibly from its biological roots to this social scientific archetype.     

Improved adaptive group testing algorithms with applications to multiple access channels and dead sensor diagnosis

We study group-testing algorithms for resolving broadcast conflicts on a multiple access channel (MAC) and for identifying the dead sensors in a mobile ad hoc wireless network. In group-testing algorithms, we are asked to identify all the defective items in a set of items when we can test arbitrary subsets of items. In the standard group-testing problem, the result of a test is binary—the tested subset either contains defective items or not. In the more generalized versions we study in this paper, the result of each test is non-binary. For example, it may indicate whether the number of defective items contained in the tested subset is zero, one, or at least two. We give adaptive algorithms that are provably more efficient than previous group testing algorithms. We also show how our algorithms can be applied to solve conflict resolution on a MAC and dead sensor diagnosis. Dead sensor diagnosis poses an interesting challenge compared to MAC resolution, because dead sensors are not locally detectable, nor are they themselves active participants. A preliminary version of this paper was presented at SPAA 2006.     

Adversarial risk analysis for counterterrorism modeling

Recent large-scale terrorist attacks have raised interest in models for resource allocation against terrorist threats. The unifying theme in this area is the need to develop methods for the analysis of allocation decisions when risks stem from the intentional actions of intelligent adversaries. Most approaches to these problems have a game-theoretic flavor although there are also several interesting decision-analytic-based proposals. One of them is the recently introduced framework for adversarial risk analysis, which deals with decision-making problems that involve intelligent opponents and uncertain outcomes. We explore how adversarial risk analysis addresses some standard counterterrorism models: simultaneous defend-attack models, sequential defend-attack-defend models, and sequential defend-attack models with private information. For each model, we first assess critically what would be a typical game-theoretic approach and then provide the corresponding solution proposed by the adversarial risk analysis framework, emphasizing how to coherently assess a predictive probability model of the adversary's actions, in a context in which we aim at supporting decisions of a defender versus an attacker. This illustrates the application of adversarial risk analysis to basic counterterrorism models that may be used as basic building blocks for more complex risk analysis of counterterrorism problems.     

Behavioral Modeling of Adversaries with Multiple Objectives in Counterterrorism

Attacker/defender models have primarily assumed that each decisionmaker optimizes the cost of the damage inflicted and its economic repercussions from their own perspective. Two streams of recent research have sought to extend such models. One stream suggests that it is more realistic to consider attackers with multiple objectives, but this research has not included the adaption of the terrorist with multiple objectives to defender actions. The other stream builds off experimental studies that show that decisionmakers deviate from optimal rational behavior. In this article, we extend attacker/defender models to incorporate multiple objectives that a terrorist might consider in planning an attack. This includes the tradeoffs that a terrorist might consider and their adaption to defender actions. However, we must also consider experimental evidence of deviations from the rationality assumed in the commonly used expected utility model in determining such adaption. Thus, we model the attacker's behavior using multiattribute prospect theory to account for the attacker's multiple objectives and deviations from rationality. We evaluate our approach by considering an attacker with multiple objectives who wishes to smuggle radioactive material into the United States and a defender who has the option to implement a screening process to hinder the attacker. We discuss the problems with implementing such an approach, but argue that research in this area must continue to avoid misrepresenting terrorist behavior in determining optimal defensive actions.     

Simulation Modeling of Anthrax Spore Dispersion in a Bioterrorism Incident

Recent events have increased awareness of the risk posed by terrorist attacks. Bacillus anthracis has resurfaced in the 21st century as a deadly agent of bioterrorism because of its potential for causing massive civilian casualties. This analysis presents the results of a computer simulation of the dispersion of anthrax spores in a typical 50-story, high-rise building after an intentional release during a bioterrorist incident. The model simulates aerosol dispersion in the case of intensive, small-scale convection, which equalizes the concentration of anthrax spores over the building volume. The model can be used to predict the time interval required for spore dispersion throughout a building after a terrorist attack in a high-rise building. The analysis reveals that an aerosol release of even a relatively small volume of anthrax spores during a terrorist incident has the potential to quickly distribute concentrations that are infectious throughout the building.     

Management innovation: a dynamic analysis of the implementation phase over time

Abstract

We develop management innovation theory, providing insights into the role of time in the implementation phase. The management innovation literature has sought to empirically identify factors that facilitate or hinder management innovation implementation from a static perspective. To address the evolution of these factors’ resistance, a temporal perspective is appropriate, but an analysis of these factors’ evolution over time is lacking. We identify the inhibiting factors that influence the management innovation implementation phase over time and address ways in which they evolve.We conduct a comparative longitudinal and dynamic analysis based on two intermediate-sized enterprises and address the obstacles that emerge during the implementation phase of a specific management innovation: lean manufacturing. Our results highlight different categories of inhibiting factors: some inhibiting factors appear at the beginning of the implementation phase with high intensity and then fade over time; conversely, other inhibiting factors appear later and then increase in intensity.     

Vulnerability and Risk: Some Thoughts from a Political and Policy Perspective

Public policies to mitigate the impacts of extreme events such as hurricanes or terrorist attacks will differ depending on whether they focus on reducing risk or reducing vulnerability. Here we present and defend six assertions aimed at exploring the benefits of vulnerability-based policies. (1) Risk-based approaches to covering the costs of extreme events do not depend for their success on reduction of vulnerability. (2) Risk-based approaches to preparing for extreme events are focused on acquiring accurate probabilistic information about the events themselves. (3) Understanding and reducing vulnerability does not demand accurate predictions of the incidence of extreme events. (4) Extreme events are created by context. (5) It is politically difficult to justify vulnerability reduction on economic grounds. (6) Vulnerability reduction is a human rights issue; risk reduction is not.