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This book contains an edited selection of papers presented at the Eighth Research Conference on Subjective Probability, Utility and Decision Making, held in Budapest. Together they span a wide range of new developments in studies of decision making, the practice of decision analysis and the development of decision-aiding technology.The volume is arranged in sections: Societal Decision Making; Organizational Decision Making; Aiding the Structuring of Small Scale Decision Problems, and Tracing Decision Processes.The emphasis is on decision processes and structures and their applications, rather than formal modelling in isolation, thus reflecting current developments in research and practice which follow from the understanding of the nature and operation of decision theoretical models gained during the 1970's.The fifth section, A Symposium on the Validity of Studies on Heuristics and Biases, is of a different nature. The papers take stock of the considerable volume of work investigation ``heuristics and biases'' in decision making over the past decade, and their implication for theory and practice.
Some years ago we, the editors of this volume, found out about each other's deeply rooted interest in the concept of time, the usage of time, and the effects of shortage of time on human thought and behavior. Since then we have fostered the idea of bringing together different perspectives in this area. We are now, there fore, very content that our idea has materialized in the present volume. There is both anecdotal and empirical evidence to suggest that time con straints may affect behavior. Managers and other professional decision makers frequently identify time pressure as a major constraint on their behavior (Isen berg, 1984). Chamberlain and Zika (1990) provide empirical support for this view, showing that complaints of insufficient time are the most frequently report ed everyday minor stressors or hassles for all groups of people except the elderly. Similarly, studies in occupational settings have identified time pressure as one of the central components of workload (Derrich, 1988; O'Donnel & Eggemeier, 1986).
J. CIimaco and C. H. Antunes After the pleasure which has been to host the community of researchers and practitioners in the area of multicriteria analysis (MA) in Coimbra in August 1994, this volume of proceedings based on the papers presented at the conference is the last step of that venture. Even though this may not be the appropriate place we cannot resist, however, the temptation to express herein some brief feelings about the conference. Almost everything concerning the conference organisation has been "handcrafted" by a small number of people, with the advantages and disadvantages that this approach generates. Our first word of acknowledgement is of course due to those who have had a permanent and active role in the multiple aspects which make the success of a conference: Maria Joao Alves, Carlos Henggeler Antunes (who is a co author of this introduction since he has closely collaborated with me in the scientific programme), Joao Paulo Costa, Luis Dias (who greatly contributed to the organisation of this volume) and Paulo Melo, as well as Leonor Dias, from the Faculty of Economics, who has shown an outstanding dedication. To those who collaborated with the organisers in the framework of their professional activity, special thanks due to Adelina whose dedication greatly exceeded her duties. As you probably know from your own experience every small detail of the conference organisation required a lot of "sweating", but the atmosphere of joy and friendship then generated has been a generous "pay-off".
Multiple Criteria Decision Making (MCDM) is the study of methods and procedures by which concerns about multiple conflicting criteria can be formally incorporated into the management planning process. A key area of research in OR/MS, MCDM is now being applied in many new areas, including GIS systems, AI, and group decision making. This volume is in effect the third in a series of Springer books by these editors (all in the ISOR series), and it brings all the latest developments in MCDM into focus. Looking at developments in the applications, methodologies and foundations of MCDM, it presents research from leaders in the field on such topics as Problem Structuring Methodologies; Measurement Theory and MCDA; Recent Developments in Evolutionary Multiobjective Optimization; Habitual Domains and Dynamic MCDM in Changeable Spaces; Stochastic Multicriteria Acceptability Analysis; and many more chapters.
This book offers an exciting new collection of recent research on the actual processes that humans use when making decisions in their everyday lives and in business situations. The contributors use cognitive psychological techniques to break down the constituent processes and set them in their social context. The contributors are from many different countries and draw upon a wide range of techniques, making this book a valuable resource to cognitive psychologists in applied settings, economists and managers.
This book provides an overview of the main methods and results in the formal study of the human decision-making process, as defined in a relatively wide sense. A key aim of the approach contained here is to try to break down barriers between various disciplines encompassed by this field, including psychology, economics and computer science. All these approaches have contributed to progress in this very important and much-studied topic in the past, but none have proved sufficient so far to define a complete understanding of the highly complex processes and outcomes. This book provides the reader with state-of-the-art coverage of the field, essentially forming a roadmap to the field of decision analysis. The first part of the book is devoted to basic concepts and techniques for representing and solving decision problems, ranging from operational research to artificial intelligence. Later chapters provide an extensive overview of the decision-making process under conditions of risk and uncertainty. Finally, there are chapters covering various approaches to multi-criteria decision-making. Each chapter is written by experts in the topic concerned, and contains an extensive bibliography for further reading and reference.
This book is unique in identifying and presenting tools to environmental decision-makers to help them improve the quality and clarity of their work. These tools range from software to policy approaches, and from environmental databases to focus groups. Equally of value to environmental managers, and students in environmental risk, policy, economics and law.
The essence of decision-aiding software is that it consists of various forms of microcomputer programming designed to enable users to process a set of (1) goals to be achieved, (2) alternatives available for achieving them, and (3) relations between goals and alternatives in order to choose the best alternative, combination, allocation, or predictive decision-rule. Benefits from using decision-aiding software include (1) being more explicit about goals to be achieved, alternatives available for achieving them, and relations between goals and alternatives; (2) being stimulated to think of more goals, alternatives, and relations than one would otherwise be likely to do; (3) being prepared to handle multiple goals, alternatives, and relations without getting confused and without feeling the need to resort to a single composite goal or a single go/no-go alternative; (4) being encouraged to experiment with changes in the inputs into one's thinking to see how one's conclusions are affected; and (5) being better able to achieve or exceed one's goals when choosing among alternatives or allocating scarce resources. There are five parts to the book covering: (1) a broad overview of decision-aiding packages, including criteria for evaluating them; (2) approaches that are based on management science and operations research, including linear programming and decision trees; (3) spreadsheet-based software, generally with goals on the columns, alternatives on the rows, relations in the cells, overall totals for each alternative at the far right, and a capability for indicating how the totals would be altered as a result of changes in the inputs; (4) expert systems software including rule-based and knowledge-based expert systems; and (5) general applications of decision-aiding software and a discussion of the increasing utilization of such software.
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.