On the Meaning and Use of the Risk Appetite Concept

The risk appetite concept has been given considerable attention recently in enterprise risk management contexts. A number of definitions exist, most with a link to risk acceptability, but also values and goals. The usefulness of the concept is, however, disputed; some authors argue that we can in fact do better without it. In this article, we provide a thorough discussion of what the risk appetite concept is actually trying to express and how it best can be used in the relevant decision making. The main purposes of the article are (i) to argue that the risk appetite concept, suitably interpreted, has a role to play in risk management, (ii) to show that the risk appetite concept is well supported by some types of risk perspectives and not by others, and (iii) to show how the risk appetite concept is linked to other related concepts, such as risk seeking and risk acceptability. The risk perspectives studied range from expected value and probability based definitions of risk to views on risk, that are founded on uncertainties.     

In Search of ‘Managerial Work’: Past,Present and Future of an Analytical Category

Based on a comprehensive review of literature, the paper examines how ‘managerial work’ as a fluid analytical category has been approached methodologically, theoretically and empirically for more than 60 years. In particular, it highlights the existence of competing scholarly understandings regarding its nature, performance, meaning and politics. The authors suggest that subsequent empirical investigations have too often worked, methodologically and theoretically, to slot in, and thus effectively reduce, the term to a particular pre‐existing box, rather than exploring open‐endedly the what and how, but also the why of ‘managerial work’ as a distinct mode of situated ordering. Having represented the concept's past and present by identifying four distinct research approaches reflected in representative publications, the authors suggest that more attention should be devoted to a mode of analytical departure that promises to address directly the suggested shortcomings in the literature. Specifically, it is argued that much could be gained if contemporary notions of practice were brought into the study of managerial work. To this end, the authors outline the contours of a practice‐based approach as a sensitizing framework for understanding managerial work by highlighting the situated, relational, sociomaterial, meaning‐making and consequence‐oriented analytical foci the approach suggests, and suggesting a number of conjoint research questions, as well as acknowledging subsequent limitations.     

Exploring the Conceptual Foundation of Continuity Management in the Context of Societal Safety

Public and private actors with critical roles for ensuring societal safety need to work proactively to reduce risks and vulnerabilities. Traditionally, risk management activities have often been performed in order to ensure continuous functioning of key societal services. Recently, however, business continuity management (BCM), and its analytical subcomponent business impact assessment (BIA), has been introduced and used more extensively by both the private and public sector in order to increase the robustness and resilience of critical infrastructures and societal functions and services. BCM was originally developed in the business sector but has received a broader use during the last decade. Yet, BCM/BIA has gained limited attention in the scientific literature—especially when it comes to clarifying and developing its conceptual basis. First, this article examines and discusses the conceptual foundation of BCM concepts, including practical challenges of applying the concepts. Based on recent conceptual developments from the field of risk management, a developed conceptualization is suggested. Second, the article discusses challenges that arise when applying BCM in the societal safety area and provides some recommendations aiming to improve the clarity and quality of applications. Third, the article provides suggestions of how to integrate the overlapping approaches of BIA and risk assessment in order to improve efficiency and effectiveness of proactive, analytic processes. We hope that the article can stimulate a critical discussion about the key concepts of BCM, their wider use in societal safety, and their connection to other concepts and activities such as risk assessment.     

A risk science perspective on liability/guilt and uncertainty judgements in courts

This article aims to provide new insights about risk and uncertainty in law contexts, by incorporating ideas and principles of contemporary risk science. The main focus is on one particular aspect of the law: its operation in courts where a defendant has been charged with a violation of civil or criminal law. Judgements about risk and uncertainty—typically using the probability concept—and how these relate to the evidence play a central role in such situations. The decision on whether the defendant is liable/guilty or not may strongly depend on how these concepts are understood and communicated. Considerable work has been conducted to provide theoretical and practical foundations for the risk and uncertainty characterizations in these contexts. Yet, it can be argued that a proper foundation for linking the evidence and the uncertainty (probability) judgements is lacking, the result being poor communication in courts about risk and uncertainties. The present article seeks to clarify what the problems are and provide guidance on how to rectify them.     

Facts and Values in Risk Analysis for Environmental Toxicants

The U.S. Office of Science and Technology Policy describes toxic substance regulation as composed of two stages. Stage I (facts) uses empirical data and scientific judgment to characterize human exposure and risk. Stage II (values) uses social and political judgment to decide regulatory action based on significance of the risk, benefits of the agent, and costs of its control. This paper argues that such a view represents an unrealistic and unattainable goal. We present examples showing how values enter virtually every part of risk analysis, and we review work on the vagaries in human judgment concerning both facts and values. These issues indicate that U.S. regulatory policy needs reconsideration.     

Optimal Expediting Policies for a Serial Inventory System with Stochastic Lead Time

In recent supply chains, often operating multiple delivery modes such as standard freight shipping and air is an effective way of addressing both delivery lead time uncertainties and service rates. We propose a model on how to optimally operate multiple delivery modes. We consider a serial supply chain and an expediting option from intermediate installations to the downstream of the chain. The goods move stochastically among the installations and the system faces a stochastic demand. We identify systems that yield simple optimal policies, in which both regular ordering and expediting follow a variant of the base stock policy. Expediting allows the system to be leaner due to the reduced regular order amount. In addition, we provide managerial insights linking expediting, base stock levels, and expediting costs based on analytical and numerical results.     

New technology and developments in management organization

New technology can provide the means to institute considerable changes in management organization, both through its application to operations and through its direct use in managerial work. These changes are expected to lead to smaller more cohesive management structures on the basis of the advantages offered by new technology for control and integration. However, a number of organizational design choices are involved with the introduction of new technology. These may present uncertainties, and it is not expected that the changes discussed will be appropriate to all kinds of organization. In Britain, there are also particular institutional and cultural barriers to the full realization of new technology's managerial potential.     

On the Need for Rethinking Current Practice that Highlights Goal Achievement Risk in an Enterprise Context

This article addresses the issue of how performance and risk management can complement each other in order to enhance the management of an enterprise. Often, we see that risk management focuses on goal achievements and not the enterprise risk related to its activities in the value chain. The statement “no goal, no risk” is a common misconception. The main aim of the article is to present a normative model for describing the links between performance and risk, and to use this model to give recommendations on how to best structure and plan the management of an enterprise in situations involving risk and uncertainties. The model, which has several novel features, is based on the interaction between different types of risk management (enterprise risk management, task risk management, and personal risk management) and a structure where the enterprise risk management overrules both the task and personal risk management. To illustrate the model we use the metaphor of a ship, where the ship is loaded with cash‐generating activities and has a direction over time determined by the overall strategic objectives. Compared to the current enterprise risk management practice, the model and related analysis are founded on a new perspective on risk, highlighting knowledge and uncertainties beyond probabilities.     

注册会计师审计风险计量模型的研究

注册会计师(CPA)在进行每一个审计项目时,都要进行专业判断,都要承担一定的责任和风险。因此,整个审计活动都可以看作是一个审计风险的管理过程。对审计风险实施有效管理的前提是风险的计量,它决定着审计工作的成败。通过构造审计风险计量模型,为审计风险要素的计量提供方法和依据,缩小主观判断与实际水平之间的差异,更有效的保证审计质量和提高审计效率。     

Employers' Reactions to the Productivity Drive: the Search for Labour Consensus*

Abstract. European employers' different policies of personnel management and of industrial relations depend to some extent on the technological and organisational choices they make, but cultural - and especially institutional - factors play an even greater role, in a period in which previous models for action clearly appear inadequate and in which, as a consequence, uncertainty grows. This article illustrates a conceptual and analytical framework which helps understand the scope and the meaning of the recent managerial search for a greater labour consensus noted by many observers. Then it shows how this framework can be used, by applying it to the analysis of the Italian case. Finally, it tries to transform some of the propositions discussed into questions and hypotheses which should guide comparative research.     

Using Uncertainty Analysis to Improve Consistency in Regulatory Assessments of Criteria Pollutant Standards

Regulatory impact analyses (RIAs), required for new major federal regulations, are often criticized for not incorporating epistemic uncertainties into their quantitative estimates of benefits and costs. “Integrated uncertainty analysis,” which relies on subjective judgments about epistemic uncertainty to quantitatively combine epistemic and statistical uncertainties, is often prescribed. This article identifies an additional source for subjective judgment regarding a key epistemic uncertainty in RIAs for National Ambient Air Quality Standards (NAAQS)—the regulator's degree of confidence in continuation of the relationship between pollutant concentration and health effects at varying concentration levels. An illustrative example is provided based on the 2013 decision on the NAAQS for fine particulate matter (PM_2.5). It shows how the regulator's justification for setting that NAAQS was structured around the regulator's subjective confidence in the continuation of health risks at different concentration levels, and it illustrates how such expressions of uncertainty might be directly incorporated into the risk reduction calculations used in the rule's RIA. The resulting confidence-weighted quantitative risk estimates are found to be substantially different from those in the RIA for that rule. This approach for accounting for an important source of subjective uncertainty also offers the advantage of establishing consistency between the scientific assumptions underlying RIA risk and benefit estimates and the science-based judgments developed when deciding on the relevant standards for important air pollutants such as PM_2.5.     

A Comparative Analysis of PRA and Intelligent Adversary Methods for Counterterrorism Risk Management

In counterterrorism risk management decisions, the analyst can choose to represent terrorist decisions as defender uncertainties or as attacker decisions. We perform a comparative analysis of probabilistic risk analysis (PRA) methods including event trees, influence diagrams, Bayesian networks, decision trees, game theory, and combined methods on the same illustrative examples (container screening for radiological materials) to get insights into the significant differences in assumptions and results. A key tenent of PRA and decision analysis is the use of subjective probability to assess the likelihood of possible outcomes. For each technique, we compare the assumptions, probability assessment requirements, risk levels, and potential insights for risk managers. We find that assessing the distribution of potential attacker decisions is a complex judgment task, particularly considering the adaptation of the attacker to defender decisions. Intelligent adversary risk analysis and adversarial risk analysis are extensions of decision analysis and sequential game theory that help to decompose such judgments. These techniques explicitly show the adaptation of the attacker and the resulting shift in risk based on defender decisions.     

In search of a soul of relevance for European management research

The argument is made that contemporary management research is driven by misplaced scientific ideals that keep research at a distance from managerial practice. Misplaced scientific ideals are institutionally reinforced, and therefore hard to change. To provide a viable alternative a different ‘soul of relevance’ needs to be constructed, which addresses the localized, embedded, fluid and contingent nature of managerial work. Four tenets are suggested that may tentatively form the basis of such work, which are as follows: practice as constitutive of organization, time as ontology, becoming as essence, and heterogeneity of factors. Narrative patterns that combine these tenets may help constitute a soul of relevance that further energizes European management research.     

Modeling Extreme Risks in Ecology

Extreme risks in ecology are typified by circumstances in which data are sporadic or unavailable, understanding is poor, and decisions are urgently needed. Expert judgments are pervasive and disagreements among experts are commonplace. We outline approaches to evaluating extreme risks in ecology that rely on stochastic simulation, with a particular focus on methods to evaluate the likelihood of extinction and quasi‐extinction of threatened species, and the likelihood of establishment and spread of invasive pests. We evaluate the importance of assumptions in these assessments and the potential of some new approaches to account for these uncertainties, including hierarchical estimation procedures and generalized extreme value distributions. We conclude by examining the treatment of consequences in extreme risk analysis in ecology and how expert judgment may better be harnessed to evaluate extreme risks.     

What Can Decision Analysis Do for Invasive Species Management?

Decisions about management of invasive species are difficult for all the reasons typically addressed by multiattribute decision analysis: uncertain outcomes, multiple and conflicting objectives, and many interested parties with differing views on both facts and values. This article illustrates how the tools of multiattribute analysis can improve management of invasive species, with an emphasis on making explicit the social values and preferences that must inform invasive species management. Risk assessment protocols developed previously for invasive species management typically suffer from two interacting flaws: (1) separating risk assessment from risk management, thus disrupting essential connections between the social values at stake in invasive species decisions and the scientific knowledge necessary to predict the likely impacts of management actions, and (2) relying on expert judgment about risk framed in qualitative and value-laden terms, inadvertently mixing the expert's judgment about what is likely to happen with personal preferences. Using the values structuring and probability-modeling elements of formal decision analysis can remedy these difficulties and make invasive species management responsive to both good science and public values. The management of feral pigs in Hawaiian ecosystems illustrates the need for such an integrated approach.     

Sizing Up a Superstorm: Exploring the Role of Recalled Experience and Attribution of Responsibility in Judgments of Future Hurricane Risk

Research suggests that hurricane‐related risk perception is a critical predictor of behavioral response, such as evacuation. Less is known, however, about the precursors of these subjective risk judgments, especially when time has elapsed from a focal event. Drawing broadly from the risk communication, social psychology, and natural hazards literature, and specifically from concepts adapted from the risk information seeking and processing model and the protective action decision model, we examine how individuals’ distant recollections, including attribution of responsibility for the effects of a storm, attitude toward relevant information, and past hurricane experience, relate to risk judgment for a future, similar event. The present study reports on a survey involving U.S. residents in Connecticut, New Jersey, and New York (n = 619) impacted by Hurricane Sandy. While some results confirm past findings, such as that hurricane experience increases risk judgment, others suggest additional complexity, such as how various types of experience (e.g., having evacuated vs. having experienced losses) may heighten or attenuate individual‐level judgments of responsibility. We suggest avenues for future research, as well as implications for federal agencies involved in severe weather/natural hazard forecasting and communication with public audiences.     

Accommodating Uncertainty in Comparative Risk

Comparative risk projects can provide broad policy guidance but they rarely have adequate scientific foundations to support precise risk rankings. Many extant projects report rankings anyway, with limited attention to uncertainty. Stochastic uncertainty, structural uncertainty, and ignorance are types of incertitude that afflict risk comparisons. The recently completed New Jersey Comparative Risk Project was innovative in trying to acknowledge and accommodate some historically ignored uncertainties in a substantive manner. This article examines the methods used and lessons learned from the New Jersey project. Monte Carlo techniques were used to characterize stochastic uncertainty, and sensitivity analysis helped to manage structural uncertainty. A deliberative process and a sorting technique helped manage ignorance. Key findings are that stochastic rankings can be calculated but they reveal such an alarming degree of imprecision that the rankings are no longer useful, whereas sorting techniques are helpful in spite of uncertainty. A deliberative process is helpful to counter analytical overreaching.     

The Effect of Demand–Supply Mismatches on Firm Risk

A supply chain management (SCM) system comprises many subsystems, including forecasting, order management, supplier management, procurement, production planning and control, warehousing and distribution, and product development. Demand–supply mismatches (DSMs) could indicate that some or all of these subsystems are not working as expected, creating uncertainties about the overall capabilities and effectiveness of the SCM system, which can increase firm risk. This article documents the effect of DSMs on firm risk as measured by equity volatility. Our sample consists of three different types of DSMs announced by publicly traded firms: production disruptions, excess inventory, and product introduction delays. We find that all three types of DSMs result in equity volatility increases. Over a 2‐year period around the announcement date, we observe mean abnormal equity volatility increases of 5.62% for production disruptions, 11.19% for excess inventory, and 6.28% for product introduction delays. Volatility increases associated with excess inventory are significantly higher than the increases associated with production disruptions and product introduction delays. Across all three types of DSMs, volatility changes are positively correlated with changes in information asymmetry. The results provide some support that volatility changes are also correlated with changes in financial and operating leverage.