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Decision support system for risk management a case study

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Decision support system for risk management: a case study

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How Systems Support (or Undermine) Good Decision-Making

Thanks for helping us catch any problems with articles on DeepDyve. We'll do our best to fix them. Check all that apply - Please note that only the first page is available if you have not selected a reading option after clicking "Read Article". Include any more information that will help us locate the issue and fix it faster for you. This study demonstrates a quantitative approach to construction risk management through analytic hierarchy process and decision tree analysis.
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Decision Support System Case study

Decision Support Systems for Risk-Based Management of Contaminated Sites addresses decision making in environmental risk management for contaminated sites, focusing on the potential role of decision support systems in informing the management of chemical pollutants and their effects. Considering the environmental relevance and the financial impacts of contaminated sites all over the post-industrialized countries and the complexity of decision making in environmental risk management, decision support systems can be used by decision makers in order to have a more structured analysis of a problem at hand and define possible options of intervention to solve the problem. Accordingly, the book provides an analysis of the main steps and tools for the development of decision support systems, namely: environmental risk assessment, decision analysis, spatial analysis and geographic information system, indicators and endpoints. Sections are dedicated to the review of decision support systems for contaminated land management and for inland and coastal waters management.
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Determine which aspect of your governance system is truly at the heart of the problem and start moving toward the path to improvement. Breaking down the types of decisions being made across your organization is a good way to begin. Finally, be sure to build in metrics to monitor their effectiveness. Despite the extensive body of research on decision making , it remains a source of great frustration for many leaders and companies. This may be because decision science often zeroes in on the decision-maker deeply examining their biases , anxieties, and instincts.
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