The "Assessment of Assessments" (AoA) is a start-up phase of a regular process for global reporting and assessment of the state of the marine environment including socio-economic aspects. AoA represents the most comprehensive initiative undertaken to date by the UN system to better coordinate ocean governance. Its central recommendation calls for a mechanism that builds on existing global, regional and national institutions and processes while integrating all available information, including socio-economic data, on how our seas and oceans are actually being used.--Publisher's description.
Many regulations issued by the U.S. Environmental Protection Agency (EPA) are based on the results of computer models. Models help EPA explain environmental phenomena in settings where direct observations are limited or unavailable, and anticipate the effects of agency policies on the environment, human health and the economy. Given the critical role played by models, the EPA asked the National Research Council to assess scientific issues related to the agency's selection and use of models in its decisions. The book recommends a series of guidelines and principles for improving agency models and decision-making processes. The centerpiece of the book's recommended vision is a life-cycle approach to model evaluation which includes peer review, corroboration of results, and other activities. This will enhance the agency's ability to respond to requirements from a 2001 law on information quality and improve policy development and implementation.
Decision making in environmental projects is typically a complex and confusing process characterized by trade-offs between socio-political, environmental, and economic impacts. Comparative Risk Assessment (CRA) is a methodology applied to facilitate decision making when various activities compete for limited resources. CRA has become an increasingly accepted research tool and has helped to characterize environmental profiles and priorities on the regional and national level. CRA may be considered as part of the more general but as yet quite academic field of multi-criteria decision analysis (MCDA). Considerable research in the area of MCDA has made available methods for applying scientific decision theoretical approaches to multi-criteria problems, but its applications, especially in environmental areas, are still limited. The papers show that the use of comparative risk assessment can provide the scientific basis for environmentally sound and cost-efficient policies, strategies, and solutions to our environmental challenges.
Risk assessment has become a dominant public policy tool for making choices, based on limited resources, to protect public health and the environment. It has been instrumental to the mission of the U.S. Environmental Protection Agency (EPA) as well as other federal agencies in evaluating public health concerns, informing regulatory and technological decisions, prioritizing research needs and funding, and in developing approaches for cost-benefit analysis. However, risk assessment is at a crossroads. Despite advances in the field, risk assessment faces a number of significant challenges including lengthy delays in making complex decisions; lack of data leading to significant uncertainty in risk assessments; and many chemicals in the marketplace that have not been evaluated and emerging agents requiring assessment. Science and Decisions makes practical scientific and technical recommendations to address these challenges. This book is a complement to the widely used 1983 National Academies book, Risk Assessment in the Federal Government (also known as the Red Book). The earlier book established a framework for the concepts and conduct of risk assessment that has been adopted by numerous expert committees, regulatory agencies, and public health institutions. The new book embeds these concepts within a broader framework for risk-based decision-making. Together, these are essential references for those working in the regulatory and public health fields.
This book is about the practice of decision making by school principals and about ways to improve this practice by capitalizing on evaluation dimensions. Much has been written on decision making but surprisingly little on decision making in the school principalship. Much has been also written on evaluation as well as on evaluation and decision making, but not much has been written on evaluation in decision making, especially decision making in the principalship. This book presents two messages. One is that decision making in the principalship can be studied and improved and not only talked about in abstract terms. The other message is that evaluation can contribute to the understanding of decision making in the principalship and to the improvement of its practice. In this book we call for the conception of an evaluation-minded principal, a principal who has a wide perspective on the nature of evaluation and its potential benefits, a principal who is also inclined to use evaluation perceptions and techniques as part of his/her decision-making process. This book was conceived in 1985 with the idea to combine thoughts about educational administration with thoughts about educational evaluation. Studies of decision making in the principalship had already been on their way. We decided to await the findings, and in the meantime we wrote a first conceptual version of evaluation in decision making. As the studies were completed we wrote a first empirical version of same.
Economists, decision analysts, management scientists, and others have long argued that government should take a more scientific approach to decision making. Pointing to various theories for prescribing and rational izing choices, they have maintained that social goals could be achieved more effectively and at lower costs if government decisions were routinely subjected to analysis. Now, government policy makers are putting decision science to the test. Recent government actions encourage and in some cases require government decisions to be evaluated using formally defined principles 01' rationality. Will decision science pass tbis test? The answer depends on whether analysts can quickly and successfully translate their theories into practical approaches and whether these approaches promote the solution of the complex, highly uncertain, and politically sensitive problems that are of greatest concern to government decision makers. The future of decision science, perhaps even the nation's well-being, depends on the outcome. A major difficulty for the analysts who are being called upon by government to apply decision-aiding approaches is that decision science has not yet evolved a universally accepted methodology for analyzing social decisions involving risk. Numerous approaches have been proposed, including variations of cost-benefit analysis, decision analysis, and applied social welfare theory. Each of these, however, has its limitations and deficiencies and none has a proven track record for application to govern ment decisions involving risk. Cost-benefit approaches have been exten sively applied by the government, but most applications have been for decisions that were largely risk-free.
This book offers new transparent views and step-by-step methods for performance evaluation of a set of units using Data Envelopment Analysis (DEA). The book has twelve practical chapters. Elementary concepts and definitions are gradually built in Chapters 1-6 based upon four examples of one input and one output factors, two input factors, two output factors, and four input and three output factors. Simultaneously, the mathematical foundations using linear programming are also introduced without any prerequisites. A reader with basic knowledge of mathematics and computers is able to understand the contents of the book. In addition, to prevent pre-judgment about the available concepts and definitions in the DEA literature, some new phrases are introduced and, after elucidating each phrase in detail in Chapters 1-6, they are reintroduced for industry-wide accuracy in Chapter 7. After that, some of the more advanced DEA topics are illustrated in Chapters 8-12, such as: production-planning problems, output-input ratio analysis, efficiency over different time periods, Malmquist efficiency indexes, and a delta neighborhood model. A clear overview of many of the elementary and advanced concepts of DEA is provided, including Technical Efficiency, Relative Efficiency, Cost/Revenue/Profit Efficiency, Price/Overall Efficiency, the DEA axioms, the mathematical background to measure technical efficiency and overall efficiency, the multiplier/envelopment form of basic DEA models in input/output-orientation, the multiplier/envelopment of Additive DEA model, the multiplier/envelopment of slacks-based models, and others. The book also covers a variety of DEA techniques, input-output ratio analysis, the natural relationships between DEA frontier and the ratio of output to input factors, production-planning problems, planning ideas with a centralized decision-making unit, context-dependent DEA, Malmquist efficiency index, efficiency over different time periods, and others. End-of-chapter exercises are provided for each chapter.
