Interdependent Risks Research Articles

Systematic Review of the Impact of Behavioral Health Homes on Cardiometabolic Risk Factors for Adults With Serious Mental Illness.

This systematic review examined the impact of health homes on cardiometabolic risk among adults with serious mental illness. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses procedures were used to conduct the systematic review. Databases were searched for peer-reviewed articles published between 1946 and August 2018 that compared health homes with a control condition (e.g., usual care and secondary data analyses using matched samples). Participants, interventions, comparisons, outcomes, and study design criteria were used to assess study eligibility. Studies were assessed for methodological quality by using the Quality Assessment of Before and After Studies With No Control Group and the Quality Assessment of Controlled Intervention Studies. Eighteen studies (i.e., 11 observational studies, four quasi-experimental studies, and three randomized controlled trials) reported on 17 health homes. Most studies reported increases in receipt of screening for cardiometabolic risk factors and service use. There was a modest reduction in selected cardiometabolic risk factors among people with serious mental illness, but clinical outcomes varied widely among studies. Improvement in cardiometabolic risk factors varied across the studies, and the clinical significance of these reductions was not clear. Peer support and self-management training may represent strategies to improve cardiometabolic risk factors. Colocation of services may not be enough to significantly affect cardiometabolic risk factors. Health homes that include standardized screening, peer support and self-management training, and intervention components that target interdependent risk factors may have a greater impact on clinical outcomes.

IMPACT OF BANKING SUPERVISION ON LIQUIDITY RISK AND CREDIT RISK: EVIDENCE FROM NIGERIA

This study investigates the effect of banking supervision on liquidity risk and credit risk in Nigeria. This research aims to determine the extent to which liquidity and credit risk has on banking supervision as well as to investigate the interdependence of liquidity risk, credit risk and banking supervision on themselves. It is also imperative to state that a study of this nature provides an independent platform through which the regulators can appraise fundamental tools for supervision in a bid to make reasonable adjustment where necessary. This study deployed the unit root test, VAR (vector autoregressive model), the system equation for P-value, and the autocorrelation test for its analysis. The data used in this thesis is a time series data from the National Deposit Insurance Corporation (NDIC) from the year 2007 to 2017. The implication of this study will be of great benefit not only to the Nigerian banking industry and related institution but also to the public and the economy as a whole. The result (findings) showed that banking supervision does have an impact liquidity risk as “liquidity risk in both periods 1 and 2 have a positive coefficient of 0.042402 and 0.004716 respectively has a positive relationship with banking supervision”. This research found that banking supervision has a positive impact on credit risk in the Nigerian economy. But at certain time periods they will be initially negative, thereby taking some time to make impact in the economy, as this is based on policy lag, as “credit risk in period 1 has a coefficient of 1.65 and a coefficient of -5.73 at period 2 which means a positive relationship with banking supervision and a negative relationship with banking supervision respectively. My recommend is that financial institutions should adhere to the rules and regulations guiding the banking industry, as lack of adherence can lead to bankruptcy or losing the banking license, and the central bank should ensure proper enforcement of the banking laws set by the banking regulators and the banking supervisors should abide by the laws strictly devoid of corrupt practices.

USING FUZZY ANALYTIC NETWORK PROCESS AND ISM METHODS FOR RISK ASSESSMENT OF PUBLIC-PRIVATE PARTNERSHIP: A CHINA PERSPECTIVE

The public-private partnership (PPP) has been adopted globally to meet intensifying demands for public facilities and services. However, PPP projects contain a variety of risks which may lead to project failure. Many researchers have explored risk factors associated with PPP projects in developing countries. However, these investigations have limited their aim to understanding risk impact without considering the interactions of these factors. Hence, to fill this gap, this study proposes a risk assessment method, addressing vital interrelationships and interdependencies. Two methodologies, fuzzy analytic network process (F-ANP) and interpretive structural modeling (ISM), were applied to avoid vagueness and data inaccuracies. The primary contributions of this paper were considering the relationships among risk factors and risk priority; and offering a risk analysis approach based on linguistic scales and fuzzy numbers to reflect different neutral, optimistic and pessimistic viewpoints from expert respondents’ judgments. Results from this analysis showed that legal and policy risk was the most influential and interdependent risk, and interest rate risk was the most essential risk in Chinese PPP projects. The ISM structure diagram demonstrated that most of 35 identified risk factors had high driving and dependence power. This study proposed a systematic and practical method to identify and assess PPP risk factors, utilizing an integrated approach consisting of F-ANP and ISM, which has not been used for risk assessment in the construction field. This paper provides a new risk assessment tool and a basis for risk management strategies in the construction engineering and management field.

Organizing Project Actors for Collective Decision‐Making about Interdependent Risks

The way project actors are organized is crucial in determining how they will be able to collectively cope with nontrivial complex problems and risks. Current project organizations are generally based on single‐criterion decomposition, whether product, process, or organization based. The proposed approach forms complementary clusters of actors based on the interdependencies between the risks they manage. More precisely, distinction has been made between the interdependencies connecting two risks that are owned by different actors and those owned by the same actor. We argue that interdependency between two risks managed by the same actor is less dangerous, meaning that clustering algorithm is tailored to distinguish mono‐ and biactor risk interdependencies. The complementary structure offered by interdependency‐based clustering tends to put together strongly interconnected actors, albeit they were often initially not grouped together. It increases the likelihood of a better communication, coordination, and collective decision‐making in complex situations. Some risks remain out of proposed clusters and are declared transverse, which means that their owners act as information hubs and are not involved in a single cluster. An industrial application is presented with operational results and perspectives for further work are drawn from it.

Estimating Risk Interdependency Ratio for Construction Projects: Using Risk Checklist in Pre-construction Phase

Estimating Risk Interdependency Ratio for Construction Projects: Using Risk Checklist in Pre-construction Phase

Заходи мінімізації ризиків виникнення надзвичайних ситуацій екологічної генези на ділянках будівництва нафтогазових свердловин

Охарактеризовано заходи мінімізації ризиків виникнення надзвичайних ситуацій екологічного походження на ділянках впливу нафтогазових свердловин, здійснено їхню класифікацію. Виокремлено організаційні та технічні, геологічні і біологічні групи заходів. Серед організаційних заходів виділено підгрупи кризового моніторингу, аудиту, експертизи та інспектування. До групи технічних, геологічних та біологічних заходів віднесено превентивні, оперативні та рекультиваційні. До програми кризового моніторингу потрібно віднести обґрунтування мережі пунктів спостережень, періодичності відбору проб, основну і додаткову програму лабораторних досліджень, систему оброблення інформації та систему прогнозування ризиків та реагування на них. До превентивних та оперативних технічних заходів віднесено гідроізоляцію поверхні бурового майданчика, встановлення противикидного обладнання, технічні рішення для недопущення забруднення ґрунтових вод глибинними флюїдами, мінімізацію використання особливо небезпечних компонентів бурового розчину. Серед рекультиваційних заходів виокремлено технічну та біологічну складові. Успішність виконання робіт запропоновано оцінювати аудитом та інспектуванням рекультиваційних робіт. Обґрунтовано, що всі групи заходів є взаємопов'язаними й ефективне управління ризиками залежить від їх синергетичної дії.

A social-ecological network approach for understanding wildfire risk governance

Abstract Large wildfire events (e.g. >100 square km) highlight the importance of governance systems that address wildfire risk at landscape scales and among multiple land owners and institutions. A growing body of empirical work demonstrates that environmental governance outcomes depend upon how well patterns of interaction among actors align with patterns of ecological connectivity, such as wildfire transmission. However, the factors that facilitate or inhibit this alignment remain poorly understood. It is crucial to improve understanding of the conditions under which actors establish or maintain linkages with other actors with whom they are interdependent because of ecological linkages. To this end, we introduce the concept of “risk interdependence archetypes” based on the spatial configurations by which one actor (i.e. a particular organization) is exposed to risk via the actions of another actor. We then develop a set of hypotheses to explore how different sets of conditions associated with each spatial configurations of risk interdependence may shape the likelihood that an actor coordinates with another actor in ways that promote social-ecological alignment. We test these hypotheses using network analysis of a wildfire transmission network developed through simulation of wildfires over several thousand fire seasons and a governance network created from interviews with 154 representatives of 87 organizations involved in efforts to mitigate wildfire risk in the Eastern Cascades Ecoregion, USA. Results indicate that social-ecological alignment is more likely when actors have opportunities to influence forest management practices on ignition-prone lands that they do not manage themselves, and when actors bear greater responsibility for averting losses from wildfires that spread to lands they manage independently. Importantly, not all forms of risk interdependence increase the likelihood of alignment, implying that organizations have limited capacity for interaction and may prioritize certain risk mitigation partnerships over others. While the performance of risk governance systems may hinge on the alignment of social and ecological networks, our results suggest that alignment in turn may depend on actor-level strategies for interaction with other actors.

The Dynamics of an Interorganizational Emergency Management Network: Interdependent and Independent Risk Hypotheses

AbstractThe purpose of this research is to uncover the dynamic structure of an interorganizational emergency management network after a disaster. This research tests two hypothesized network structures: interdependent risk and independent risk. While the former illustrates the importance of trust and information redundancy in coordinating and aligning emergency preparedness and response, the latter captures the tendency for local actors to seek dominant partners to bridge crucial information across the region. A stochastic actor‐based model with a forward selection strategy is used to analyze the structural effects of endogenous networks and the effects of exogenous community attributes on interorganizational ties. Based on the data sets collected before and after the 2012 typhoons in South Korea, the results support the interdependent risk hypothesis, suggesting that an interorganizational network structure tends to evolve into the notion of shared collaboration risk.

Risk matrix driven supply chain risk management: Adapting risk matrix based tools to modelling interdependent risks and risk appetite

There is a major research gap of developing a supply chain risk management process integrating the risk appetite of a decision maker and all stages of the risk management process within an interdependent network of systemic risks. We introduce an iterative process, namely risk matrix driven supply chain risk management, to bridge this gap. We make use of the recently introduced concept of utility indifference curves based risk matrix to capture the risk attitude of a decision maker. We also present algorithms for assessing and mitigating interdependent risks for risk-neutral and risk-averse/seeking decision makers and demonstrate the application of our proposed process through a simulation study. Utilising the method of cost-benefit analysis within an interdependent setting of interacting risks and risk mitigation strategies, we also propose a second approach that can help a decision maker to determine a set of Pareto-optimal risk mitigation strategies and select optimal solutions subject to the budget constraint and specific risk appetite.

THE THEORY AND PRACTICE OF RISK ASSESSMENT OF PROFESSIONAL DANGERS

In the paper, on the basis of the conducted analysis of the dynamics of the spread of dangers in the context of evolutionary development of society, it is determined that the global problems have become complex, which appears in interdependence of natural, technogenic, socio-political, economic, scientific-technological and other risks. The main source of danger, at the present stage of development of society, is an industrial environment.The analysis of known theoretical studies to appearance of dangerous is carried out and it is defined that none of considered theories can be treated as absolutely correct and generally accepted. First of all the conceptuality of given theories that is, limited practical usage, second of all the insufficient attention and underestimation of the role of the "human factor" as a fundamental factor in the process of creating dangers are the meanest drawbacks. Notice, that in the European Countries exist around 100 differents methods of assessment of the risk of occurrence dangers, according them quantitative measurement of the risks is carried out by the three meanest methods: statistical, expert and analog.British Standard BS-8800 (GB), risk assessment based on probability-loss matrix (GB, France, Latvia, the USA, Australia), construction of risk assessment scales (Germany, Finland), the methodology of the National Research Institute of Occupational Safety and Health (NRIOS) in Ukraine, risk score (the USA), risk assessment code (GB), method of verbal functions (European Union),assessment of occupational risks by the Elmer system, risk assessment based on requirements level ranking (OIR index) are the most often used methods for the risks evaluation. On basis of the analysis of the above mentioned methods, two main problems were identified. The first problem that exists in the risks evaluation of occurrence dangerous is the lack of a unique unified methodology.The second problem is the underestimation of the significance of the "human factor" in the "man-machine" system. It is pointed out that due to underestimating the role of the "human factor" as a key component of risk one cannot consider any of the known risk assessment methods to be effective and universally accepted. Based on conducted research, the need for a principallynew universal and effective methodology for quantitative risk assessment is identified.

Hierarchical Interactive Risk Hedging of Multi-TSO Power Systems

For a large interconnected power system with multiple transmission system operators (TSOs), online inter-TSO synergistic interactions are increasingly being required to hedge against system-wide operating risk. To address this issue, a novel hierarchical interactive risk hedging (HIRH) method is proposed. Under the established framework, the upper level coordinator can interact with the lower level local TSOs through target and response variables. Decentralized and interdependent risk hedging models are formulated, including a system-wide coordination optimization model for the coordinator and a set of preventive-corrective combined risk-aware optimal power flow models for local TSOs. To tackle the computational complexity of the multiple problems, a two-level decomposition-coordination algorithm based on analytical target cascading and Benders decomposition is developed. A case study of a modified three-area RTS-96 system demonstrates the effectiveness of the proposed HIRH.

The Interdependence of Risk and Moral Theory

The Interdependence of Risk and Moral Theory

Risk Factors of Postoperative Sacroiliac Joint Pain for Posterior Lumbar Surgery: ≥2-Year Follow-up Retrospective Study.

A retrospective study was conducted to clarify the risk factors of postoperative sacroiliac joint pain (SIJP) for posterior open lumbar surgery. A total of 472 patients who underwent posterior lumbar surgery between January 2011 and December 2014 were included in this analysis. We recorded basic characteristics, surgical characteristics, and SIJP information for each patient. The incidence of postoperative SIJP is 13.8% in our study. Comparison of the incidence of SIJP between diskectomy and posterior lumbar interbody fusion indicated that SIJP incidence tended to be higher in posterior lumbar interbody fusion patients (P= 0.029). Compared with the single-segment group, SIJP occurred more frequently in the multiple operative segments group (P= 0.025). Comparing the incidence of SIJP among different types of lumbar diseases, SIJP incidence is significantly higher in the lumbar stenosis group (P= 0035). Lumbar fusion surgery and multiple operative segments are interdependent risk factors for the postoperative SIJP. The incidence of postoperative SIJP also increases in patients with lumbar stenosis compared with lumbar disk herniation and lumbar spondylolisthesis.

International risk transmission of stock market movements

The Great Recession of 2007-2009 originated in the United States has brought to the surface the need for measuring and monitoring the transmission of extreme downside market risk. This paper investigates the international risk transmission mechanism between the US and major Asian stock markets. By applying two recently introduced test statistics based on cross-quantilogram function, we confirm the existence of risk spillover from the US to major Asian stock markets, as well as the feedback effect. Furthermore, we apply the multivariate quantile regression model (VAR for VaR) to quantitively uncover these tail-interdependency patterns, showing how the extreme downside risk transmits between the US and Asian markets. Our results suggest these stock markets are highly integrated in terms of risk transmission. The shocks in the US market substantially increase the Value at Risk (VaR) in the Asian markets, except China and Russia. On the other hand, price drops in the Asian markets also have a weaker but significant predictive power for risk in the US market. By investigating the time-varying pattern of the risk interdependency structure, we further show a rising trend of cross-country risk linkages over time. We also document considerable asymmetric patterns in the international transmission mechanism of stock market movements, highlighting the underlying weakness of adopting volatility to measure the market risk.

Supply chain risk network management: A Bayesian belief network and expected utility based approach for managing supply chain risks

The paper develops and operationalises a supply chain risk network management (SCRNM) process that captures interdependencies between risks, multiple (potentially conflicting) performance measures and risk mitigation strategies within a (risk) network setting. The process helps in prioritising risks and strategies specific to the decision maker's risk appetite. The process is demonstrated through a case study conducted in a global manufacturing supply chain involving semi-structured interviews and focus group sessions with experts in risk management. Theoretically grounded in the framework of Bayesian Belief Networks (BBNs) and Expected Utility Theory (EUT), the modelling approach has a number of distinctive characteristics. It utilises a top-down approach of Fault Tree Analysis (FTA). Performance measures are identified first and subsequently connected to risks. A ‘probability-conditional expected utility’ matrix is introduced to reflect the propagation impact of interdependent risks on all performance measures identified. A ‘weighted net evaluation of risk mitigation’ method is proposed and the method of ‘swing weights’ is used to capture the trade-off between the efficacy of strategies and the associated cost keeping in view the decision maker's risk appetite. The approach adapts and integrates techniques from safety and reliability engineering (FTA), decision making under uncertainty (EUT), and multi-criteria decision analysis (swing weights). The merits and challenges associated with the implementation of interdependency based frameworks are discussed. Propositions are presented to elucidate the significance of modelling interdependency between risks and strategies.

The properties of global risk networks and corresponding risk management strategies

ABSTRACTGlobal risks interconnect with one another and threaten our society as a highly interdependent system. However, knowledge on how risk materializations influence one another is limited. Thus, this study provides a network model to measure risk interdependence and presents recommendations on the integrative risk management framework.This study develops a global risk network and calculates its key indicators of structural characteristics. Results show that global risks are closely interconnected and a particular triangle relationship exists among environmental, geopolitical, and societal risks. To improve the resilience of a risk system, the systematic important risks, which are “man-made environmental catastrophes” and “interstate conflict” in this study, should be monitored and controlled. Furthermore, we simplify the risk system by entirely managing risks in the same group based on our reclassification. Our method is considerably effective in detecting upcoming crisis and assists supervisors take timely action to prevent crisis.

In-hospital mortality after acute STEMI in patients undergoing primary PCI.

Acute myocardial infarction (AMI) is the main cause of global and in-hospital mortality in patients with cardiovascular diseases. We aimed to examine the association between the coronary artery involved and the in-hospital mortality in patients who underwent primary percutaneous coronary intervention (pPCI) after ST segment elevation myocardial infarction (STEMI). The in-hospital mortality of STEMI patients who underwent pPCI was assessed at the Department of Cardiology, Harzklinik Goslar, Germany, which has no access to immediate mechanical circulatory support (MCS), between 2013 and 2017. We enrolled 312 STEMI patients, with amean age of 67.1± 13.4years, of whom 211 (68%) were male. In-hospital mortality was documented in 31patients (10%). In-hospital mortality was associated with pre-hospital cardiopulmonary resuscitation (CPR; n= 39/12.5%), older age, lower systolic blood pressure, Killip class> 1,triple-vessel disease (each p< 0.0001), female gender (p= 0.0158), and with the localization of the treated culprit lesion in the left main coronary artery (LMCA; p= 0.0083) and in the ramus circumflexus (RCX; p= 0.0141). In this monocentric cohort, all-cause in-hospital mortality of STEMI patients after pPCI was significantly higher in those patients with culprit lesions in the LMCA and in the RCX, which may prove to be asubstantial novel risk factor for STEMI-related mortality. Increasing age and female gender may be interdependent risk factors for mortality in this patient population. Furthermore, our data highlight the importance of the availability of MCS options in pPCI centers for patients after CPR.

Limits of Risk Predictability in a Cascading Alternating Renewal Process Model

Most risk analysis models systematically underestimate the probability and impact of catastrophic events (e.g., economic crises, natural disasters, and terrorism) by not taking into account interconnectivity and interdependence of risks. To address this weakness, we propose the Cascading Alternating Renewal Process (CARP) to forecast interconnected global risks. However, assessments of the model’s prediction precision are limited by lack of sufficient ground truth data. Here, we establish prediction precision as a function of input data size by using alternative long ground truth data generated by simulations of the CARP model with known parameters. We illustrate the approach on a model of fires in artificial cities assembled from basic city blocks with diverse housing. The results confirm that parameter recovery variance exhibits power law decay as a function of the length of available ground truth data. Using CARP, we also demonstrate estimation using a disparate dataset that also has dependencies: real-world prediction precision for the global risk model based on the World Economic Forum Global Risk Report. We conclude that the CARP model is an efficient method for predicting catastrophic cascading events with potential applications to emerging local and global interconnected risks.

Multiple risk factor dependence structures: Distributional properties

We introduce a class of dependence structures that we call the Multiple Risk Factor (MRF) dependence structures. On the one hand, the new constructions establish a factor model framework for analysing default risk within a risk portfolio in which the components are exposed to an arbitrary number of risk factors having dependent occurrence times. On the other hand, the MRF structures can be seen as an encompassing family of multivariate probability distributions with the univariate margins distributed Pareto of the 2nd kind, and in this role, they can be used to model dependent and heavy tailed insurance losses. In both cases, the MRF dependences provide a transparent and technically convenient basis for measuring and managing interdependent risks in the presence of predetermined sets of background risk factors that are of interest to risk managers.

Multiple risk measures for multivariate dynamic heavy–tailed models

The dynamic evolution of tail–risk interdependence among institutions is of primary importance when extreme events such as financial crisis occur. In this paper we introduce two new risk measures that generalise the Conditional Value–at–Risk and the Conditional Expected Shortfall in a multiple setting. The proposed risk measures aim to capture extreme tail co–movements among several multivariate connected market participants experiencing contemporaneous distress instances. Analytical expressions for the risk measures are obtained under a parametric model that postulates a joint dynamic evolution of the underlying institutions' losses and gains. We consider a multivariate Student–t version of Markov Switching models as a robust alternative to the usual multivariate Gaussian specification, accounting for heavy–tails and time varying non–linear correlations. An empirical application to US banks is considered to show that our model–based risk measurement framework provides a better characterisation of the dynamic evolution of the overall risk of a financial system and a more complete picture of how the risk spreads among institutions.