842 resultados para Qualitative model of risk management


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OBJECTIVE: To investigate whether better management of chronic conditions by family practices reduces mortality risk. DATA: Two random samples of 5 million patients registered with over 8,000 English family practices followed up for 4 years (2004/5-2007/8). Measures of the quality of disease management for 10 conditions were constructed for each family practice for each year. The outcome measure was an indicator taking the value 1 if the patient died during a specified year, 0 otherwise. STUDY DESIGN: Cross-section and multilevel panel data multiple logistic regressions were estimated. Covariates included age, gender, morbidity, hospitalizations, attributed socio-economic characteristics, and local health care supply measures. PRINCIPAL FINDINGS: Although a composite measure of the quality of disease management for all 10 conditions was significantly associated with lower mortality, only the quality of stroke care was significant when all 10 quality measures were entered in the regression. CONCLUSIONS: The panel data results suggest that a 1 percent improvement in the quality of stroke care could reduce the annual number of deaths in England by 782 [95 percent CI: 423, 1140]. A longer study period may be necessary to detect any mortality impact of better management of other conditions.

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This paper presents the current state and development of a prototype web-GIS (Geographic Information System) decision support platform intended for application in natural hazards and risk management, mainly for floods and landslides. This web platform uses open-source geospatial software and technologies, particularly the Boundless (formerly OpenGeo) framework and its client side software development kit (SDK). The main purpose of the platform is to assist the experts and stakeholders in the decision-making process for evaluation and selection of different risk management strategies through an interactive participation approach, integrating web-GIS interface with decision support tool based on a compromise programming approach. The access rights and functionality of the platform are varied depending on the roles and responsibilities of stakeholders in managing the risk. The application of the prototype platform is demonstrated based on an example case study site: Malborghetto Valbruna municipality of North-Eastern Italy where flash floods and landslides are frequent with major events having occurred in 2003. The preliminary feedback collected from the stakeholders in the region is discussed to understand the perspectives of stakeholders on the proposed prototype platform.

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The main purpose of this study was to analyze how stress tests are used in risk management in the Finnish banking and insurance sectors. In order to enhance understanding of the topic, stress testing was explored in the context of corporate governance and regulato-ry implications of Basel II and Solvency II on stress testing were examined. In addition, the effects of the global financial crisis on stress testing were mapped and the differences in stress testing practices between the banking and insurance sector were discussed. The research method was qualitative case study and it was conducted by interviewing risk managers from ten institutions and a representative from FIN-FSA. Findings pointed out that stress testing practices vary significantly between different institutions. Interesting observations were made in terms of stress testing practices in the banking and insurance sectors. The increasing importance and use of stress tests were recognized as a result of the financial crisis. Stress testing was even considered more like art than science given the amount of challenges it involves. In general, improvements in stress tests were suggested, with an emphasis on stress concentration between different types of risks.

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Rust, caused by Puccinia psidii, is one of the most important diseases affecting eucalyptus in Brazil. This pathogen causes disease in mini-clonal garden and in young plants in the field, especially in leaves and juvenile shoots. Favorable climate conditions for infection by this pathogen in eucalyptus include temperature between 18 and 25 ºC, together with at least 6-hour leaf wetness periods, for 5 to 7 consecutive days. Considering the interaction between the environment and the pathogen, this study aimed to evaluate the potential impact of global climate changes on the spatial distribution of areas of risk for the occurrence of eucalyptus rust in Brazil. Thus, monthly maps of the areas of risk for the occurrence of this disease were elaborated, considering the current climate conditions, based on a historic series between 1961 and 1990, and the future scenarios A2 and B2, predicted by IPCC. The climate conditions were classified into three categories, according to the potential risk for the disease occurrence, considering temperature (T) and air relative humidity (RH): i) high risk (18 < T < 25 ºC and RH > 90%); ii) medium risk (18 < T < 25 ºC and RH < 90%; T< 18 or T > 25 ºC and RH > 90%); and iii) low risk (T < 18 or T > 25 ºC and RH < 90%). Data about the future climate scenarios were supplied by GCM Change Fields. In this study, the simulation model Hadley Centers for Climate Prediction and Research (HadCm3) was adopted, using the software Idrisi 32. The obtained results led to the conclusion that there will be a reduction in the area favorable to eucalyptus rust occurrence, and such a reduction will be gradual for the decades of 2020, 2050 and 2080 but more marked in scenario A2 than in B2. However, it is important to point out that extensive areas will still be favorable to the disease development, especially in the coldest months of the year, i.e., June and July. Therefore, the zoning of areas and periods of higher occurrence risk, considering the global climate changes, becomes important knowledge for the elaboration of predicting models and an alert for the integrated management of this disease.

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VTT Jouni Meriluodon valtio-opin alaan kuuluva väitöskirja Systems between information and knowledge : in a memory management model of an extended enterprise tarkastettiin 21.6.2011 Helsingin yliopistossa.

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This thesis reveals the topic of reputational risk management as a key element for business continuity and value maximization. The purpose of the work is to investigate reputational risk from the side of its definition, management (including legal requirements on this risk category) and measurement and to analyse reputational risk’s impact on business continuity and value maximization. To be able to do this, different respective articles, reports of financial institutions are gathered and constructive summaries and analysis are made. In order to deeply investigate the impact of reputational risk on business continuity and value maximization, it was chosen to study it from three aspects: 1) check the impact of stock valuation of 7 companies that experienced reputational catastrophe / risk, 2) analyse a case study on disagreements in management of reputational risk among case companies and impact on their respective performance, and 3) conduct a survey of financial sector companies in Liechtenstein to see how reputational risk management works in practice. The findings of the research showed a significant impact of reputation decadence on company’s value and trading volume, and showed crucial importance of post-crisis management for the company’s financial performance. The results of the qualitative research based on survey proved that companies consider reputational risk management as a one of the key elements for their business continuity and value maximization.

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Emerging markets of Northern Africa and Turkey provide growth opportunities for logistics service companies in the middle of low growth environment of European Union. The purpose of this research is to explore and analyze the risk factors in container shipping industry and third party logistics (3PL) services. The research empirically examined the risk factors, which are related within the interaction between these two parties in emerging markets of Mediterranean area. The previous studies have provided a valuable insight into the operational risks faced by container shipping industries. However, most of these studies have focused on one or several operational risk factors from a single point of view, and no studies have inclusively examined the possible operational risks faced in the container shipping industry from dual perspective of 3PL provider and its customers. A questionnaire has been deployed to collect related data; and the impacts of the risks were then be assessed and ranked using the method of risk mapping. Respondents were located in Turkey, Algeria, Tunisia, and Libya. Research presents the most important risk factors identified, and compares them between 3PL provider and its customers. The research also provide some risk mitigation strategies for the key risk factors, and tried to figure out a common risk picture, which guides the managers in both sides to have a better decisions and as a result, improve the performance of the container shipping operations. Challenge during project execution time was that customers identified vast amount of more risks than what was the case with logistics service operator.

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The purpose of this study is to examine and explore the level of risk that CAMI workers confront under their existing labour-management partnership arrangement. Risk is explored using two distinct categories, distributive and political. Distributive risk is expressed as tangibly substantive, reflecting the real terms and conditions of employment, and the changing social relations of production on the floor. The second type of risk is political and is concerned with the effects that labour-management partnerships have on the displacement of unions as legitimate agents of/for workers within the workplace. Data was collected using three methods; content analysis, cross-sectional survey and focus group interviews. The study revealed that CAMI workers are exposed to both distributive and political risk under their current LMP arrangement.

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People with intellectual disability who sexually offend commonly live in community-based settings since the closing of all institutions across the province of Ontario. Nine (n=9) front line staff who provide support to these individuals in three different settings (treatment setting, transitional setting, residential setting) were interviewed. Participants responded to 47 questions to explore how sex offenders with intellectual disability can be supported in the community to prevent re-offenses. Questions encompassed variables that included staff attitudes, various factors impacting support, structural components of the setting, quality of life and the good life, staff training, staff perspectives on treatment, and understanding of risk management. Three overlapping models that have been supported in the literature were used collectively for the basis of this research: The Good Lives Model (Ward & Gannon, 2006; Ward et al., 2007), the quality of life model (Felce & Perry, 1995), and variables associated with risk management. Results of this research showed how this population is being supported in the community with an emphasis on the following elements: positive and objective staff attitude, teamwork, clear rules and protocols, ongoing supervision, consistency, highly trained staff, and environments that promote quality of life. New concepts arose which suggested that all settings display an unequal balance of upholding human rights and managing risks when supporting this high-risk population. This highlights the need for comprehensive assessments in order to match the offender to the proper setting and supports, using an integration of a Risk, Need, Responsivity model and the Good Lives model for offender rehabilitation and to reduce the likelihood of re-offenses.

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This research was undertaken with an objective of studying software development project risk, risk management, project outcomes and their inter-relationship in the Indian context. Validated instruments were used to measure risk, risk management and project outcome in software development projects undertaken in India. A second order factor model was developed for risk with five first order factors. Risk management was also identified as a second order construct with four first order factors. These structures were validated using confirmatory factor analysis. Variation in risk across categories of select organization / project characteristics was studied through a series of one way ANOVA tests. Regression model was developed for each of the risk factors by linking it to risk management factors and project /organization characteristics. Similarly regression models were developed for the project outcome measures linking them to risk factors. Integrated models linking risk factors, risk management factors and project outcome measures were tested through structural equation modeling. Quality of the software developed was seen to have a positive relationship with risk management and negative relationship with risk. The other outcome variables, namely time overrun and cost over run, had strong positive relationship with risk. Risk management did not have direct effect on overrun variables. Risk was seen to be acting as an intervening variable between risk management and overrun variables.

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We design a financial network model that explicitly incorporates linkages across institutions through a direct contagion channel, as well as an indirect common exposure channel. In particular, common exposure is setup so as to link the financial to the real sector. The model is calibrated to balance sheet data on the colombian financial sector. Results indicate that commercial banks are the most systemically important financial institutions in the system. Whereas government owned institutions are the most vulnerable institutions in the system.

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Despite the many models developed for phosphorus concentration prediction at differing spatial and temporal scales, there has been little effort to quantify uncertainty in their predictions. Model prediction uncertainty quantification is desirable, for informed decision-making in river-systems management. An uncertainty analysis of the process-based model, integrated catchment model of phosphorus (INCA-P), within the generalised likelihood uncertainty estimation (GLUE) framework is presented. The framework is applied to the Lugg catchment (1,077 km2), a River Wye tributary, on the England–Wales border. Daily discharge and monthly phosphorus (total reactive and total), for a limited number of reaches, are used to initially assess uncertainty and sensitivity of 44 model parameters, identified as being most important for discharge and phosphorus predictions. This study demonstrates that parameter homogeneity assumptions (spatial heterogeneity is treated as land use type fractional areas) can achieve higher model fits, than a previous expertly calibrated parameter set. The model is capable of reproducing the hydrology, but a threshold Nash-Sutcliffe co-efficient of determination (E or R 2) of 0.3 is not achieved when simulating observed total phosphorus (TP) data in the upland reaches or total reactive phosphorus (TRP) in any reach. Despite this, the model reproduces the general dynamics of TP and TRP, in point source dominated lower reaches. This paper discusses why this application of INCA-P fails to find any parameter sets, which simultaneously describe all observed data acceptably. The discussion focuses on uncertainty of readily available input data, and whether such process-based models should be used when there isn’t sufficient data to support the many parameters.