Search results

The purpose of this study is to enhance the existing enterprise risk-management (ERM) theory by introducing both a resource-based view and a dynamic capability perspective. These strategic management concepts might resolve several theoretical shortcomings in the field of risk management. The concept of risk-management capabilities is proposed as an explanation of a firm’s risk resilience.

This paper is conceptual in nature. For illustrative purposes, the paper refers to practical examples.

First, the resource-based view provides a framework that helps to set priorities in risk management. Second, the dynamic capability perspective illustrates how firms can handle unforeseen events. Third, it is proposed that dynamic capabilities are needed to allow a constant reassessment of the impact of specific resources and, consequently, of ERM priorities. Fourth, a risk-management capability, as an integral part of a dynamic capability, allows firms to develop risk resilience in turbulent environments.

This paper develops an enhanced framework for ERM within specific boundary conditions. It shows how priorities at the strategic level are to be set, and how these priorities influence the operational level of risk management.

The framework provides clear guidelines on setting priorities in ERM and implementing a risk-management process within firms.

This study contributes to the theoretical literature on ERM by enhancing it through a new framework. The resource-based view and dynamic capability perspective benefit through insights from risk-management literature.

The purpose of this paper is to examine the Company Dynamic Response Map (CDRM) risk management model that uses the dynamic capabilities concept. The study examines risks associated with strategic decision-making in construction projects and evaluates proposed methods that connect the dynamic capabilities of project-based organisations with risk management.

This preliminary study examines risks associated with strategic decision-making in construction projects and evaluates a proposed model that connects the dynamic capabilities of project-based organisations with risk management. Specifically, the CDRM model is evaluated, a risk management model developed by Arena et al. (2013) to better respond to risks and opportunities based on the concept of dynamic capabilities.

We argue that although the CDRM presents a promising development in that it uses dynamic capabilities prospectively in a risk management model to produce tangible results, there are, nonetheless, impediments to the CDRM being used by construction clients. The primary impediment relates to the issue of categorisation, the difficulty in assigning a specific identified risk to a particular category of dynamic capabilities.

A conceptual argument is made and not an empirical one.

The CDRM model was developed to be used in practice and this paper evaluates that model.

Contributes to both the dynamic capabilities literature as well as risk management literature. The paper ends with a discussion on the possible merits of the CDRM, and an evaluation on potential impediments to its use by construction clients.

Research and development (R&D) projects are often pursued through a project portfolio (PP). R&D PPs involve many stakeholders, and without proactive management, their interactions may lead to conflict risks. These conflict risks change dynamically with different stages of the PP life cycle, increasing the challenge of PP risk management. Existing conflict risk research mainly focuses on source identification but lacks risk assessment work. To better manage the stakeholder conflict risks (SCRs) of R&D PPs, this study employs the dynamic Bayesian network (DBN) to construct its dynamic assessment model.

This study constructs a DBN model to assess the SCRs in R&D PP. First, an indicator system of SCRs is constructed from the life cycle perspective. Then, the risk relationships within each R&D PPs life cycle stage are identified via interpretative structural modeling (ISM). The prior and conditional probabilities of risks are obtained by expert judgment and Monte Carlo simulation (MCS). Finally, crucial SCRs at each stage are identified utilizing propagation analysis, and the corresponding risk responses are proposed.

The results of the study identify the crucial risks at each stage. Also, for the crucial risks, this study suggests appropriate risk response strategies to help managers better perform risk response activities.

This study dynamically assesses the stakeholder conflict risks in R&D PPs from a life-cycle perspective, extending the stakeholder risk management research. Meanwhile, the crucial risks are identified at each stage accordingly, providing managerial insights for R&D PPs.

The aim of this paper is to provide up‐to‐date discussion of the types of factors used to assess sexual offenders risk.

The current status of the factors used to assess risk in sexual offenders is examined.

Risk factors broadly fall into two categories: static factors (i.e. generally unchangeable information such as previous offence history) from which a number of actuarial scales have been developed; and dynamic factors (i.e. psychological dispositions) that are typically identified in treatment. It is suggested that these risk factors are artefacts of the same behavioural and psychological vulnerabilities at different stages of assessment, with static factors acting as markers for underlying dispositions, while dynamic factors are the underlying dispositions.

The paper discusses in some detail the status of age as a risk factor, where even though it is typically considered a static risk factor in a number of actuarial scales (allowance typically being made if individuals are over/under 25), there is a dynamic element (i.e. change with age or the passage of time) to this aspect of assessment.

This paper may be useful to practitioners working in the field, in terms of providing a useful heuristic framework for risk conceptualisation.

It is crucial to find a better portfolio optimization strategy, considering the cryptocurrencies' asymmetric volatilities. Hence, this research aimed to present dynamic optimization on minimum variance (MVP), equal risk contribution (ERC) and most diversified portfolio (MDP).

This study applied dynamic covariances from multivariate GARCH(1,1) with Student’s-t-distribution. This research also constructed static optimization from the conventional MVP, ERC and MDP as comparison. Moreover, the optimization involved transaction cost and out-of-sample analysis from the rolling windows method. The sample consisted of ten significant cryptocurrencies.

Dynamic optimization enhanced risk-adjusted return. Moreover, dynamic MDP and ERC could win the naïve strategy (1/N) under various estimation windows, and forecast lengths when the transaction cost ranging from 10 bps to 50 bps. The researcher also used another researcher's sample as a robustness test. Findings showed that dynamic optimization (MDP and ERC) outperformed the benchmark.

Sophisticated investors may use the dynamic ERC and MDP to optimize cryptocurrencies portfolio.

To the best of the author’s knowledge, this is the first paper that studies the dynamic optimization on MVP, ERC and MDP using DCC and ADCC-GARCH with multivariate-t-distribution and rolling windows method.

The purpose of this paper is to improve risk assessment processes in airline flight operations by introducing a dynamic risk assessment method.

Fuzzy logic and Bayesian network are used together to form a dynamic structure in the analysis. One of the most challenging factors of the analyses in aviation is to get quantitative data. In this study, the fuzzy data quantification technique is used to perform dynamic risk assessment. Dynamic structure in the analysis is obtained by transforming the bow-tie model into a Bayesian network equivalent.

In this study, the probability of top-event from fault tree analysis is calculated as 1.51 × 10⁻⁶. Effectiveness of the model is measured by comparing the analysis with the safety performance indicator data that reflects past performance of the airlines. If two data are compared with each other, they are at the same order of value, with small difference (0.6 × 10⁻⁷).

This study proposes a dynamic model to be used in risk assessment processes in airline flight operations. A dynamic model for safety analysis provides real-time, autonomous and faster risk assessment. Moreover, it can help in the decision-making process and reduce airline response time to undesired states, which means that the proposed model can contribute to the efficiency of the risk management process in airline flight operations.

The purpose of this study was to explore the predictive validity of the revised Problem Identification Checklist (PIC‐R) in predicting inpatient and community violence using a retrospective design. The Historical Scale (H‐Scale) of the HCR‐20 was employed to control for static risk factors. The predictive accuracy between predictors and outcome measures was evaluated using Receiver Operating Characteristics (ROC) analysis. The PIC‐R significantly predicted inpatient violence (AUC range 0.77‐0.92) over a 12‐month follow‐up period but did not predict community violence. Conversely, the H‐Scale significantly predicted community violence (AUC 0.82) but did not predict inpatient violence over a 12‐month follow‐up period. The findings offer preliminary validation for the predictive accuracy of the PIC‐R for violence in a UK inpatient population. Additionally, the findings suggest that short‐term risk of violence within a psychiatric inpatient population may be more related to dynamic and clinical risk variables rather than to static ones.

With the rapid development of Internet technology, cybersecurity threats such as security loopholes, data leaks, network fraud, and ransomware have become increasingly prominent, and organized and purposeful cyberattacks have increased, posing more challenges to cybersecurity protection. Therefore, reliable network risk assessment methods and effective network security protection schemes are urgently needed.

Based on the dynamic behavior patterns of attackers and defenders, a Bayesian network attack graph is constructed, and a multitarget risk dynamic assessment model is proposed based on network availability, network utilization impact and vulnerability attack possibility. Then, the self-organizing multiobjective evolutionary algorithm based on grey wolf optimization is proposed. And the authors use this algorithm to solve the multiobjective risk assessment model, and a variety of different attack strategies are obtained.

The experimental results demonstrate that the method yields 29 distinct attack strategies, and then attacker's preferences can be obtained according to these attack strategies. Furthermore, the method efficiently addresses the security assessment problem involving multiple decision variables, thereby providing constructive guidance for the construction of security network, security reinforcement and active defense.

A method for network risk assessment methods is given. And this study proposed a multiobjective risk dynamic assessment model based on network availability, network utilization impact and the possibility of vulnerability attacks. The example demonstrates the effectiveness of the method in addressing network security risks.

Managers of megaprojects face social risk management challenges throughout the various design, construction, and operation stages, owing to the various conflicts of interest among stakeholders, public skepticism, and opposition. However, most existing studies have not focused on the dynamic analysis of integrating social risks in these stages. This study developed a dynamic analysis approach to explore the dynamics of critical social risk factors and related stakeholders of megaprojects and built the managerial maps for various stakeholders.

Based on the social analysis network (SNA), a dynamic network analysis approach for understanding the dynamics of social risk and related stakeholders has been developed by literature and case analysis. The approach comprises the following steps: (1) generating social risk–stakeholder networks in different stages; (2) analysis of the critical stakeholders and social risk factors; (3) dynamic analysis of social risk factors; and (4) developing social risk management maps for various stakeholders. To verify the feasibility and effectiveness of the approach, 40 megaprojects from China were analyzed.

According to the results, the local government is a critical stakeholder during all stages, inadequate information promotion (IIP) and imperfect communication and coordination mechanism (ICCM) are key social risk sources throughout the megaproject life cycle. Furthermore, the management maps for government organizations, project implementation groups, and external stakeholders were constructed.

This research has three contributions. First, a dynamic analysis approach of stakeholder-associated social risks in megaprojects is developed, which enriches the social risk management theory of megaprojects and provides inspiration for future research focus. Second, the social risk–stakeholder networks and critical social risks in different stages are confirmed to provide a more valid and accurate picture of social risk management in megaprojects. Third, the social risk managerial maps for different stakeholders built in this research will be beneficial for governments, project implementation groups, and external stakeholders to optimize management strategies.