Implementation of Equity in Resource Allocation for Regional Earthquake Risk Mitigation Using Two‐Stage Stochastic Programming

This article presents a new methodology to implement the concept of equity in regional earthquake risk mitigation programs using an optimization framework. It presents a framework that could be used by decisionmakers (government and authorities) to structure budget allocation strategy toward different seismic risk mitigation measures, i.e., structural retrofitting for different building structural types in different locations and planning horizons. A two‐stage stochastic model is developed here to seek optimal mitigation measures based on minimizing mitigation expenditures, reconstruction expenditures, and especially large losses in highly seismically active countries. To consider fairness in the distribution of financial resources among different groups of people, the equity concept is incorporated using constraints in model formulation. These constraints limit inequity to the user‐defined level to achieve the equity‐efficiency tradeoff in the decision‐making process. To present practical application of the proposed model, it is applied to a pilot area in Tehran, the capital city of Iran. Building stocks, structural vulnerability functions, and regional seismic hazard characteristics are incorporated to compile a probabilistic seismic risk model for the pilot area. Results illustrate the variation of mitigation expenditures by location and structural type for buildings. These expenditures are sensitive to the amount of available budget and equity consideration for the constant risk aversion. Most significantly, equity is more easily achieved if the budget is unlimited. Conversely, increasing equity where the budget is limited decreases the efficiency. The risk‐return tradeoff, equity‐reconstruction expenditures tradeoff, and variation of per‐capita expected earthquake loss in different income classes are also presented.     

Trend effects on perceived avalanche hazard

Hazard-level forecasts constitute an important risk mitigation tool to reduce loss of economic values and human life. Avalanche forecasts represent an example of this. As for many other domains, avalanche risk is communicated using a color-coded, categorical risk scale aimed at informing the public about past, current, and future risk. We report the results from three experiments in which we tested if an irrelevant past trend in forecasted avalanche danger affects perceptions of current and future avalanche risk. Our sample consisted of individuals from three different populations targeted by national avalanche warning services. All three experiments showed that the perception of avalanche risk is influenced by the trend, but that the effect is opposite for perceptions of current and expectations of future avalanche risk. While future avalanche risk is extrapolated in the same direction as the change from the previous day, we found that perceived current risk appears to be based on an average of past and current risk. These effects diminish when we provide participants with a scale indicating the exact level of avalanche danger. For most of our measurement instruments, however, the effects remain significant. These results imply that targeted populations may consider historic information more than was intended by the sender. As such, our results have implications for both avalanche warning services and risk communication in general.     

Using GIS in Risk Analysis: A Case Study of Hazardous Waste Transport

This paper provides an illustration of how a geographic information system (GIS) can be used in risk analysis. It focuses on liquid hazardous waste transport and utilizes records archived by the London Waste Regulatory Authority. This data source provides information on the origin and destination of each waste stream, but not the route followed during transport. A GIS was therefore employed to predict the paths used, taking into account different routing criteria and characteristics of the available road network. Details were also assembled on population distribution and ground-water vulnerability, thus providing a basis for evaluating the potential consequences of a waste spillage during transport. Four routing scenarios were implemented to identify sections of road which consistently saw heavy traffic. These simulations also highlighted that some interventions could lead to risk tradeoffs rather than hazard mitigation. Many parts of the research would not have been possible without a GIS, and the study demonstrates the considerable potential of such software in environmental risk assessment and management.     

Adaptive Flood Risk Management Under Climate Change Uncertainty Using Real Options and Optimization

It is well recognized that adaptive and flexible flood risk strategies are required to account for future uncertainties. Development of such strategies is, however, a challenge. Climate change alone is a significant complication, but, in addition, complexities exist trying to identify the most appropriate set of mitigation measures, or interventions. There are a range of economic and environmental performance measures that require consideration, and the spatial and temporal aspects of evaluating the performance of these is complex. All these elements pose severe difficulties to decisionmakers. This article describes a decision support methodology that has the capability to assess the most appropriate set of interventions to make in a flood system and the opportune time to make these interventions, given the future uncertainties. The flood risk strategies have been explicitly designed to allow for flexible adaptive measures by capturing the concepts of real options and multiobjective optimization to evaluate potential flood risk management opportunities. A state‐of‐the‐art flood risk analysis tool is employed to evaluate the risk associated to each strategy over future points in time and a multiobjective genetic algorithm is utilized to search for the optimal adaptive strategies. The modeling system has been applied to a reach on the Thames Estuary (London, England), and initial results show the inclusion of flexibility is advantageous, while the outputs provide decisionmakers with supplementary knowledge that previously has not been considered.     

Efficacy Foundations for Risk Communication: How People Think About Reducing the Risks of Climate Change

Believing action to reduce the risks of climate change is both possible (self‐efficacy) and effective (response efficacy) is essential to motivate and sustain risk mitigation efforts, according to current risk communication theory. Although the public recognizes the dangers of climate change, and is deluged with lists of possible mitigative actions, little is known about public efficacy beliefs in the context of climate change. Prior efficacy studies rely on conflicting constructs and measures of efficacy, and links between efficacy and risk management actions are muddled. As a result, much remains to learn about how laypersons think about the ease and effectiveness of potential mitigative actions. To bring clarity and inform risk communication and management efforts, we investigate how people think about efficacy in the context of climate change risk management by analyzing unprompted and prompted beliefs from two national surveys (N = 405, N = 1,820). In general, respondents distinguish little between effective and ineffective climate strategies. While many respondents appreciate that reducing fossil fuel use is an effective risk mitigation strategy, overall assessments reflect persistent misconceptions about climate change causes, and uncertainties about the effectiveness of risk mitigation strategies. Our findings suggest targeting climate change risk communication and management strategies to (1) address gaps in people's existing mental models of climate action, (2) leverage existing public understanding of both potentially effective mitigation strategies and the collective action dilemma at the heart of climate change action, and (3) take into account ideologically driven reactions to behavior change and government action framed as climate action.     

Using Structured Decision Making to Help Implement a Precautionary Approach to Endangered Species Management

Endangered species protection is a significant risk management concern throughout North America. An extensive conceptual literature emphasizes the role to be played by precautionary approaches. Risk managers, typically working in concert with concerned stakeholders, frequently cite the concept as key to their efforts to prevent extinctions. Little has been done, however, to evaluate the multidimensional impacts of precautionary frameworks or to assist in the examination of competing precautionary risk management options as part of an applied risk management decision framework. In this article we describe how decision-aiding techniques can assist in the creation and analysis of alternative precautionary strategies, using the example of a multistakeholder committee charged with protection of endangered Cultus Lake salmon on the Canadian west coast. Although managers were required to adopt a precautionary approach, little attention had been given to how quantitative analyses could be used to help define the concept or to how a precautionary approach might be implemented in the face of difficult economic, social, and biological tradeoffs. We briefly review key steps in a structured decision-making (SDM) process and discuss how this approach was implemented to help bound the management problem, define objectives and performance measures, develop management alternatives, and evaluate their consequences. We highlight the role of strategy tables, employed to help participants identify, alternative management options. We close by noting areas of agreement and disagreement among participants and discuss the implications of decision-focused processes for other precautionary resource management efforts.     

Dealing with high-risk environments: Institutional-based tools to reduce political risk costs

The international business (IB) literature on political risk mitigation has assigned explanatory preeminence to the organizational capabilities of multinational corporations (MNCs). The literature has assumed that political risk is avoidable for MNCs with specific political capabilities. We argue that political risk is inevitable. We posit that even if MNCs have political capabilities, host countries' political risk and its associated costs will not simply disappear. Extending the literature on political risk mitigation, we highlight the role of institutional-based tools in curbing political risk costs. Specifically, we posit that MNCs can reduce political risk costs through (i) international investment agreements, (ii) investment contracts with host governments, (iii) political risk insurance, and (iv) guarantees with binding enforcement mechanisms in unison with relying on political capabilities, thereby dampening the negative effect of uncontrollable host country political risk. We leverage the political-institutional approach to political risk and draw on relevant literature from law and IB to develop a framework to describe the conditions under which MNCs may use these institutional-based tools.     

A Review of Risk Perceptions and Other Factors that Influence Flood Mitigation Behavior

In flood risk management, a shift can be observed toward more integrated approaches that increasingly address the role of private households in implementing flood damage mitigation measures. This has resulted in a growing number of studies into the supposed positive relationship between individual flood risk perceptions and mitigation behavior. Our literature review shows, however, that, actually, this relationship is hardly observed in empirical studies. Two arguments are provided as an explanation. First, on the basis of protection motivation theory, a theoretical framework is discussed suggesting that individuals’ high‐risk perceptions need to be accompanied by coping appraisal to result in a protective response. Second, it is pointed out that possible feedback from already‐adopted mitigation measures on risk perceptions has hardly been considered by current studies. In addition, we also provide a review of factors that drive precautionary behavior other than risk perceptions. It is found that factors such as coping appraisal are consistently related to mitigation behavior. We conclude, therefore, that the current focus on risk perceptions as a means to explain and promote private flood mitigation behavior is not supported on either theoretical or empirical grounds.     

A Hybrid Methodology for Modeling Risk of Adverse Events in Complex Health‐Care Settings

In spite of increased attention to quality and efforts to provide safe medical care, adverse events (AEs) are still frequent in clinical practice. Reports from various sources indicate that a substantial number of hospitalized patients suffer treatment‐caused injuries while in the hospital. While risk cannot be entirely eliminated from health‐care activities, an important goal is to develop effective and durable mitigation strategies to render the system “safer.” In order to do this, though, we must develop models that comprehensively and realistically characterize the risk. In the health‐care domain, this can be extremely challenging due to the wide variability in the way that health‐care processes and interventions are executed and also due to the dynamic nature of risk in this particular domain. In this study, we have developed a generic methodology for evaluating dynamic changes in AE risk in acute care hospitals as a function of organizational and nonorganizational factors, using a combination of modeling formalisms. First, a system dynamics (SD) framework is used to demonstrate how organizational‐level and policy‐level contributions to risk evolve over time, and how policies and decisions may affect the general system‐level contribution to AE risk. It also captures the feedback of organizational factors and decisions over time and the nonlinearities in these feedback effects. SD is a popular approach to understanding the behavior of complex social and economic systems. It is a simulation‐based, differential equation modeling tool that is widely used in situations where the formal model is complex and an analytical solution is very difficult to obtain. Second, a Bayesian belief network (BBN) framework is used to represent patient‐level factors and also physician‐level decisions and factors in the management of an individual patient, which contribute to the risk of hospital‐acquired AE. BBNs are networks of probabilities that can capture probabilistic relations between variables and contain historical information about their relationship, and are powerful tools for modeling causes and effects in many domains. The model is intended to support hospital decisions with regard to staffing, length of stay, and investments in safety, which evolve dynamically over time. The methodology has been applied in modeling the two types of common AEs: pressure ulcers and vascular‐catheter‐associated infection, and the models have been validated with eight years of clinical data and use of expert opinion.     

Coupling the Biophysical and Social Dimensions of Wildfire Risk to Improve Wildfire Mitigation Planning

We describe recent advances in biophysical and social aspects of risk and their potential combined contribution to improve mitigation planning on fire‐prone landscapes. The methods and tools provide an improved method for defining the spatial extent of wildfire risk to communities compared to current planning processes. They also propose an expanded role for social science to improve understanding of community‐wide risk perceptions and to predict property owners’ capacities and willingness to mitigate risk by treating hazardous fuels and reducing the susceptibility of dwellings. In particular, we identify spatial scale mismatches in wildfire mitigation planning and their potential adverse impact on risk mitigation goals. Studies in other fire‐prone regions suggest that these scale mismatches are widespread and contribute to continued wildfire dwelling losses. We discuss how risk perceptions and behavior contribute to scale mismatches and how they can be minimized through integrated analyses of landscape wildfire transmission and social factors that describe the potential for collaboration among landowners and land management agencies. These concepts are then used to outline an integrated socioecological planning framework to identify optimal strategies for local community risk mitigation and improve landscape‐scale prioritization of fuel management investments by government entities.     

Strategy implementation: Taking stock and moving forward

Strategy implementation (SI) is a significant managerial, and organizational challenge as many practitioners struggle to make strategies actionable and to achieve intended results. Moreover, there is no unified body of research on SI. This is problematic for academics aiming to contribute to a research-based body of knowledge on implementation. To remedy this problem, we draw on the strategy-as-practice perspective and conceptualize SI as a particular type of ‘strategy work’, manifest in the activities, actors, and tools through which strategy is executed. This conceptual framework allows us to synthesize the fragmented literature into five implementation practices: structure and process matching, resource matching, monitoring, framing, and negotiating. We show how these implementation activities operate at different levels and involve different actors and tools. With its emphasis on what managers (and other people) do within specific structural, temporal, and material arrangements, the strategy-as-practice perspective offers exciting opportunities for future implementation research.     

Disentangling combinations and contingencies of generic strategies: A set-theoretic configurational approach

Porter's framework of generic strategies conceptualizes key elements of firms' strategic positions in their industry. Research on these generic strategies has been challenged by the complexity of capturing relations between generic strategies (i.e., cost leadership, differentiation, and focus) and their interdependencies with other strategic commitments for performance outcomes. We address these challenges by utilizing fuzzy set Qualitative Comparative Analysis (fsQCA) to explore the causal complexity underlying the links between generic strategies and firm performance. Specifically, we study combinations of firms' generic strategies and other strategy attributes as paths to high or low performance in the U.S. and Canadian airline industry. We find six equifinal configurations that are consistently linked to high performance and nine configurations that are consistently linked to the absence of high performance. Our findings shed light on the contingencies underlying performance consequences of generic strategies. Consequently they redirect theoretical debates on the links between generic strategies and firm performance as well as on the superiority of pure versus hybrid generic strategies towards relations of set-theoretic of necessity and sufficiency. Specifically, we show that having a generic strategy advantage is not sufficient for high performance but that it is a vital ingredient in recipes for success. Similarly, our findings suggest that a generic strategy disadvantage is not sufficient for low performance, but is a key ingredient in all paths to poor performance. We conclude with a discussion of our study's contributions to the literature, suggestions for future research, and implications for managerial practice.     

Organizational Improvisation: A Consolidating Review and Framework

Organizational improvisation is increasingly recognized as a relevant area of management research. However, the cumulativeness of research on improvisation in organizations remains low. This paper organizes existing contributions on organizational improvisation within a new consolidating framework combining degrees (minor, bounded and structural) and levels (individual, interpersonal and organizational) of improvisation. The proposed degree/level framework allows for reviewing the existing literature on organizational improvisation in the management disciplines of strategy, organizational behaviour, organizational theory, innovation and marketing in a systematic manner. It also exposes potential areas for future research across management disciplines, research areas, organizational settings and industries, and beyond existing metaphors, most notably of jazz and improvisational theatre.     

Post-Katrina Hazard Mitigation on the Gulf Coast

The article reviews the major hazard mitigation measures considered for the Gulf Coast following hurricanes between 2005 and 2008, especially Hurricanes Katrina and Ike. Basic similarities among and between the hazard events are noted, along with a wide variety of efforts to eliminate or reduce risks from natural hazards in establishing mitigation as the major protector of affected areas. Intergovernmental collaboration, insurance reform, and public risk perception are included. Both the processes used and substantive policy options are examined. This includes attempts at system-wide solutions in dealing with the mullti-state region for recovery from devastation and providing greater resiliency toward further hazard events. Such themes as a comprehensive system approach and the use of risk informed decision making, communication of risk to the public, and the use of professional and technical expertise, are being used on the Gulf Coast. Risk informed decision making uses techniques and methods from risk analysis, scenario planning, and multi-criteria decision analysis. Stakeholders are incorporated into the development of alternatives conveyed to the public. Policy alternative include coastal restoration measures such as barrier island and shoreline restoration, structural engineering such as floodwalls and levees, and nonstructural options such as buyouts, relocation, and effective zoning and building codes. The most comprehensive approaches follow a multiple lines of defense strategy to combine the various types of risk reduction measures.     

Cost‐Benefit Analysis for Optimization of Risk Protection Under Budget Constraints

Cost‐benefit analysis (CBA) is commonly applied as a tool for deciding on risk protection. With CBA, one can identify risk mitigation strategies that lead to an optimal tradeoff between the costs of the mitigation measures and the achieved risk reduction. In practical applications of CBA, the strategies are typically evaluated through efficiency indicators such as the benefit‐cost ratio (BCR) and the marginal cost (MC) criterion. In many of these applications, the BCR is not consistently defined, which, as we demonstrate in this article, can lead to the identification of suboptimal solutions. This is of particular relevance when the overall budget for risk reduction measures is limited and an optimal allocation of resources among different subsystems is necessary. We show that this problem can be formulated as a hierarchical decision problem, where the general rules and decisions on the available budget are made at a central level (e.g., central government agency, top management), whereas the decisions on the specific measures are made at the subsystem level (e.g., local communities, company division). It is shown that the MC criterion provides optimal solutions in such hierarchical optimization. Since most practical applications only include a discrete set of possible risk protection measures, the MC criterion is extended to this situation. The findings are illustrated through a hypothetical numerical example. This study was prepared as part of our work on the optimal management of natural hazard risks, but its conclusions also apply to other fields of risk management.     

An Integrated Framework for Environmental Multi‐Impact Spatial Risk Analysis

Quantitative risk analysis is being extensively employed to support policymakers and provides a strong conceptual framework for evaluating decision alternatives under uncertainty. Many problems involving environmental risks are, however, of a spatial nature, i.e., containing spatial impacts, spatial vulnerabilities, and spatial risk‐mitigation alternatives. Recent developments in multicriteria spatial analysis have enabled the assessment and aggregation of multiple impacts, supporting policymakers in spatial evaluation problems. However, recent attempts to conduct spatial multicriteria risk analysis have generally been weakly conceptualized, without adequate roots in quantitative risk analysis. Moreover, assessments of spatial risk often neglect the multidimensional nature of spatial impacts (e.g., social, economic, human) that are typically occurring in such decision problems. The aim of this article is therefore to suggest a conceptual quantitative framework for environmental multicriteria spatial risk analysis based on expected multi‐attribute utility theory. The framework proposes: (i) the formal assessment of multiple spatial impacts; (ii) the aggregation of these multiple spatial impacts; (iii) the assessment of spatial vulnerabilities and probabilities of occurrence of adverse events; (iv) the computation of spatial risks; (v) the assessment of spatial risk mitigation alternatives; and (vi) the design and comparison of spatial risk mitigation alternatives (e.g., reductions of vulnerabilities and/or impacts). We illustrate the use of the framework in practice with a case study based on a flood‐prone area in northern Italy.     

Understanding Household Preferences for Hurricane Risk Mitigation Information: Evidence from Survey Responses

Risk information is critical to adopting mitigation measures, and seeking risk information is influenced by a variety of factors. An essential component of the recently adopted My Safe Florida Home (MSFH) program by the State of Florida is to provide homeowners with pertinent risk information to facilitate hurricane risk mitigation activities. We develop an analytical framework to understand household preferences for hurricane risk mitigation information through allowing an intensive home inspection. An empirical analysis is used to identify major drivers of household preferences to receive personalized information regarding recommended hurricane risk mitigation measures. A variety of empirical specifications show that households with home insurance, prior experience with damages, and with a higher sense of vulnerability to be affected by hurricanes are more likely to allow inspection to seek information. However, households with more members living in the home and households who live in manufactured/mobile homes are less likely to allow inspection. While findings imply MSFH program's ability to link incentives offered by private and public agencies in promoting mitigation, households that face a disproportionately higher level of risk can get priority to make the program more effective.     

An Agent‐Based Model for Pathogen Persistence and Cross‐Contamination Dynamics in a Food Facility

We used an agent‐based modeling (ABM) framework and developed a mathematical model to explain the complex dynamics of microbial persistence and spread within a food facility and to aid risk managers in identifying effective mitigation options. The model explicitly considered personal hygiene practices by food handlers as well as their activities and simulated a spatially explicit dynamic system representing complex interaction patterns among food handlers, facility environment, and foods. To demonstrate the utility of the model in a decision‐making context, we created a hypothetical case study and used it to compare different risk mitigation strategies for reducing contamination and spread of Listeria monocytogenes in a food facility. Model results indicated that areas with no direct contact with foods (e.g., loading dock and restroom) can serve as contamination niches and recontaminate areas that have direct contact with food products. Furthermore, food handlers’ behaviors, including, for example, hygiene and sanitation practices, can impact the persistence of microbial contamination in the facility environment and the spread of contamination to prepared foods. Using this case study, we also demonstrated benefits of an ABM framework for addressing food safety in a complex system in which emergent system‐level responses are predicted using a bottom‐up approach that observes individual agents (e.g., food handlers) and their behaviors. Our model can be applied to a wide variety of pathogens, food commodities, and activity patterns to evaluate efficacy of food‐safety management practices and quantify contamination reductions associated with proposed mitigation strategies in food facilities.     

Interventions for musculoskeletal disorders in computer-intense office work: a framework for evaluation

Workplace interventions for work-related musculoskeletal disorders (WMSDs) are usually multifaceted. These interventions tend to deal with multiple work organizational and physical risk factors and have components occurring at different organizational levels. The organizations are often changing, with shifting initiatives and priorities. Evaluation of such interventions poses challenges in documentation of implementation, reduction in exposures, and assessment of improved health outcomes. We describe a means-outcomes framework for evaluating field interventions that includes strategies, activities, objectives and metrics for outcomes using quantitative and qualitative methods. We demonstrate application of the framework to our work with a large newspaper, which builds on existing laboratory, aetiological and best practice evidence to improve musculoskeletal health. The newspaper had adopted several organizational strategies aimed at improving financial performance, including restructuring into teams, a major set of moves/renovations and introduction of new software. Concomitant WMSD-related organizational strategies include an ergonomics policy, human resources activities, promotion of team work, changes in environment and equipment specifications and development of information systems. We have found the framework useful for focusing the purpose of data collection and ensuring coverage of important components. At the same time, it provides sufficient flexibility to respond to the changing process of implementation.     

Communicating supply chain risks and mitigation strategies: a comprehensive framework

Concerning the increasing emphasis on risk management in this uncertain global environment, there is an urgent demand for practical decision support tools that support supply chain risk communication and management. This research proposes an integrated framework that takes explicit account of multiple types of risk in aiding decision-making, and compares and ranks alternative risk mitigation strategies individually and collectively in indicator basis using fuzzy set theory and multiple criteria decision analysis methods. Through an illustrative case, the research demonstrates that the proposed framework provides a holistic view of supply chain risks and enables firms to foresee, spot and respond to the exposed risks in an effective and efficient manner.