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Key research themes
1. How can risk be decomposed and aggregated to enhance multi-level risk assessment and management?
This theme investigates methods for decomposing complex risks into components and aggregating these components across multiple organizational or process levels. It focuses on creating comprehensive risk indicators that account for hierarchical and lateral relationships among risks, with implications for optimized risk management decisions and the design of corrective or preventive actions.
Key finding: The paper proposes a novel methodology for multipurpose aggregation of risk components and indicators that flexibly handles arbitrarily many components and aggregation levels beyond the traditional one- or two-level... Read more
Key finding: This work introduces marginal risk decompositions where the total risk measure for an aggregated portfolio is expressed as the sum of marginal impacts of individual components. It establishes conditions under which such... Read more
Key finding: The authors provide a detailed distinction between horizontal and vertical (hierarchical) aggregation of risks in organizations, demonstrating how aggregation methods must accommodate these differing structures to correctly... Read more
Key finding: This paper applies Lean methodology to risk management by proposing a hierarchical decomposition of risks into final risks (outcome-based) and indicated risks (process-related deviations). By structuring process increments as... Read more
Key finding: The study discusses parameter estimation methods for probabilistic risk propagation models, particularly in critical infrastructure contexts where sparse data complicates direct parametrization. It demonstrates how risk... Read more
2. What theoretical frameworks enable the decomposition and conditional representation of risk in probabilistic and multidimensional settings?
This theme explores advanced mathematical and theoretical foundations for representing, decomposing, and conditioning risk measures beyond classical contexts. It emphasizes frameworks allowing risk evaluations under variable and conditional probability measures, multidimensional risk aversion, and the formal decomposition of risk into marginal and conditional components, thereby enabling nuanced analyses and optimization in complex stochastic environments.
Key finding: The authors introduce 'risk forms'—bivariate functionals acting on measurable functions and probability measures—and establish a generalized Kusuoka representation applicable across variable probability measures. They prove a... Read more
Key finding: This paper develops a decomposition of risk premia for multidimensional risks by isolating two components: one related to the shape of indifference maps under certainty (ordinal substitution effects) and another reflecting... Read more
Key finding: The paper characterizes when a risk measure admits a marginal additive decomposition, relating to directional derivatives under assumptions such as homogeneous portfolio growth. It outlines classes of risk measures (scalable... Read more
Key finding: This work evaluates consistency of various risk measures with respect to first and second order stochastic dominance (fosd and sosd). It finds that most downside risk measures (e.g., Value-at-Risk, lower partial moments)... Read more
3. How do conceptualizations of risk influence risk assessment, governance, and communication in systemic and complex contexts?
This theme covers foundational analyses of the nature and definitions of risk, emphasizing how differing interpretations impact risk governance frameworks, perception, and communication strategies. It includes the categorization of risks, the relationship between uncertainty, ambiguity, systemic risk, and vulnerability, as well as their implications for managing complex, uncertain, and ambiguous risk problems, especially in societal and organizational settings.
Key finding: The article clarifies distinctions between risk types and risk problems, especially emphasizing the roles of complexity, uncertainty, and ambiguity in risk governance. It proposes a refined risk-problem classification system... Read more
Key finding: This paper proposes a generalized theoretical definition of risk grounded in systems theory and probability, aiming to unify disparate domain-specific risk definitions. It highlights the necessity of explicit scenario... Read more
Key finding: This foreword advocates for acknowledging the pluralistic and context-dependent nature of risk, arguing that risk definitions vary by social context, stakeholder perspectives, and domain-specific epistemologies. It emphasizes... Read more
Key finding: The article reviews psychological, sociological, and cultural theories of risk perception, emphasizing the challenges posed by complexity, uncertainty, and ambiguity in modern technological risks. It discusses implications... Read more
Key finding: By performing an ontological analysis based on the Common Ontology of Value and Risk (COVER), this paper clarifies the concept of risk propagation, showing that it often conflates risk with belief updating or probability... Read more