865 resultados para Work driving risk management


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A useful strategy for improving disaster risk management is sharing spatial data across different technical organizations using shared information systems. However, the implementation of this type of system requires a large effort, so it is difficult to find fully implemented and sustainable information systems that facilitate sharing multinational spatial data about disasters, especially in developing countries. In this paper, we describe a pioneer system for sharing spatial information that we developed for the Andean Community. This system, called SIAPAD (Andean Information System for Disaster Prevention and Relief), integrates spatial information from 37 technical organizations in the Andean countries (Bolivia, Colombia, Ecuador, and Peru). SIAPAD was based on the concept of a thematic Spatial Data Infrastructure (SDI) and includes a web application, called GEORiesgo, which helps users to find relevant information with a knowledge-based system. In the paper, we describe the design and implementation of SIAPAD together with general conclusions and future directions which we learned as a result of this work.

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Time, cost and quality achievements on large-scale construction projects are uncertain because of technological constraints, involvement of many stakeholders, long durations, large capital requirements and improper scope definitions. Projects that are exposed to such an uncertain environment can effectively be managed with the application of risk management throughout the project life cycle. Risk is by nature subjective. However, managing risk subjectively poses the danger of non-achievement of project goals. Moreover, risk analysis of the overall project also poses the danger of developing inappropriate responses. This article demonstrates a quantitative approach to construction risk management through an analytic hierarchy process (AHP) and decision tree analysis. The entire project is classified to form a few work packages. With the involvement of project stakeholders, risky work packages are identified. As all the risk factors are identified, their effects are quantified by determining probability (using AHP) and severity (guess estimate). Various alternative responses are generated, listing the cost implications of mitigating the quantified risks. The expected monetary values are derived for each alternative in a decision tree framework and subsequent probability analysis helps to make the right decision in managing risks. In this article, the entire methodology is explained by using a case application of a cross-country petroleum pipeline project in India. The case study demonstrates the project management effectiveness of using AHP and DTA.

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Enterprise resource planning (ERP) projects are risky. But if they are implemented appropriately, they can provide competitive advantage to organisations. Therefore, ERP implementation has become one of the most critical aspects of today's information management research. The main purpose of this article is to describe a new ERP risk assessment framework (RAF) that can be used to increase the success of ERP implementation. In this article, through a case study based in a leading UK-based energy service provider, we demonstrate the new RAF, which has been shown to help identify and mitigate risks in ERP implementation. In contrast to other research, this RAF identifies risks hierarchically in external engagement, programme management, work stream and work package levels across technical, schedule, operational, business and organisational categories. This not only helped to develop responses to mitigate risks but also facilitates on-going risk control.

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Context The internet is gaining popularity as a means of delivering employee-based cardiovascular (CV) wellness interventions though little is known about the cardiovascular health outcomes of these programs. In this review, we examined the effectiveness of internet-based employee cardiovascular wellness and prevention programs. Evidence Acquisition We conducted a systematic review by searching PubMed, Web of Science and Cochrane library for all published studies on internet-based programs aimed at improving CV health among employees up to November 2012. We grouped the outcomes according to the American Heart Association (AHA) indicators of cardiovascular wellbeing – weight, BP, lipids, smoking, physical activity, diet, and blood glucose. Evidence Synthesis A total of 18 randomized trials and 11 follow-up studies met our inclusion/exclusion criteria. Follow-up duration ranged from 6 – 24 months. There were significant differences in intervention types and number of components in each intervention. Modest improvements were observed in more than half of the studies with weight related outcomes while no improvement was seen in virtually all the studies with physical activity outcome. In general, internet-based programs were more successful if the interventions also included some physical contact and environmental modification, and if they were targeted at specific disease entities such as hypertension. Only a few of the studies were conducted in persons at-risk for CVD, none in blue-collar workers or low-income earners. Conclusion Internet based programs hold promise for improving the cardiovascular wellness among employees however much work is required to fully understand its utility and long term impact especially in special/at-risk populations.

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International audience

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The paper presents the development of a decision support system for the management of geotechnical and environmental risks in oil pipelines using a geographical information system. The system covers a 48.5 km long section of the So Paulo to Brasilia (OSBRA) oil pipeline, which crosses three municipalities in the northeast region of the So Paulo state (Brazil) and represents an area of 205.8 km(2). The spatial database was created using geo-processing procedures, surface and intrusive investigations and geotechnical reports. The risk assessment was based mainly on qualitative models (relative numeric weights and multicriteria decision analysis) and considered pluvial erosion, slope movements, soil corrosion and third party activities. The maps were produced at a scale of 1:10,000.

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Australia's Great Barrier Reef is one of the world's most popular scuba diving destinations. Unfortunately, a series of recent diving injuries and deaths has tarnished the region's safety record. In particular, media attention surrounding the disappearance of American divers Thomas and Eileen Lonergan has focused attention on dive operators' legal responsibilities and the consequences of failing to discharge their duty of care to customers. This paper briefly examines the relevant Australian law for recreational diving operations, and reviews risk management strategies that may reduce or prevent the occurrence of future problems. (C) 2000 Elsevier Science Ltd. All rights reserved.

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The purpose of this study is to analyze the Controllership relevance as support risk management in non-financial companies. Risk management is a widely discussed and disseminated subject amongst financial institutions. It is obvious that economic uncertainties and, consequently, prevention and. control must also exist in non-financial companies. To enable managers to take safe-decisions, it is essential for them to be able to count on instrumental support that provides timely and adequate information, to ensure lower levels of mistakes and risk exposure. However, discussion concerning risk management in non-financial companies is still in its early stages in Brazil. Considering this gap, this study aims at assessing how Controllership has been acting in? companies under the insight of risk and how it can contribute to risk management in non-financial companies. To achieve the proposed goal, a field research was. carried-out with non-financial companies that are located in the city Sao Paulo and listed in the Sao Paulo Stock Exchange (Bovespa). The research was carried out using questionnaires, which were sent do Risk Officers and Controllers of those companies with the purpose of evaluating their perception on the subject. The results,of the research allow us to conclude that Controllership offers support to risk management, through information that contributes to the mitigation of the risks in non-financial companies.

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Risk management can be considered as part of the Occupational Health and Safety System (OHS) of an organization and can be used to develop and implement the OHS policy and manage the associated risks. The success of the integration of risk management in OHS depends on both technical and human aspects. Thus, this paper presents and discusses the case of a company working in the area of solid waste treatment. This company was certified in 2009 with an Integrated Management Systems for Quality, Environment, Occupational Health and Safety. The evolution of accidents before and after the implementation of the integrated system was analysed and a questionnaire was used to capture the perceptions of the technicians on the risk management system. The analysis of the findings showed that the frequency of accidents increased since 2009 but the severity has been reduced. Several interrelated causes and consequences were analysed and discussed. Furthermore, the analysis of the opinions of the company’s technicians permitted to highlight some important aspects on the integration of risk management in the OHS system of the company. In line with this discussion some hypothesis have been formulated.

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Long-term contractual decisions are the basis of an efficient risk management. However those types of decisions have to be supported with a robust price forecast methodology. This paper reports a different approach for long-term price forecast which tries to give answers to that need. Making use of regression models, the proposed methodology has as main objective to find the maximum and a minimum Market Clearing Price (MCP) for a specific programming period, and with a desired confidence level α. Due to the problem complexity, the meta-heuristic Particle Swarm Optimization (PSO) was used to find the best regression parameters and the results compared with the obtained by using a Genetic Algorithm (GA). To validate these models, results from realistic data are presented and discussed in detail.