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This book describes the new perspective of naturalistic decision making. The point of departure is how people make decisions in complex, time-pressured, ambiguous, and changing environments. The purpose of this book is to present and elaborate on past models developed to explain this type of decision making. The central philosophy of the book is that classical decision theory has been unproductive since it is so heavily grounded in economics and mathematics. The contributors believe there is little to be learned from laboratory studies about how people actually handle difficult and interesting tasks; therefore, the book presents a critique of classical decision theory. The models of naturalistic decision making described by the contributors were derived to explain the behavior of firefighters, business people, jurors, nuclear power plant operators, and command-and-control officers. The models are unique in that they address the way people use experience to frame situations and adopt courses of action. The models explain the strengths of skilled decision makers. Naturalistic decision research requires the examination of field settings, and a section of the book covers methods for conducting meaningful research outside the laboratory. In addition, since his approach has applied value, the book covers issues of training and decision support systems.
Goal-Directed Decision Making: Computations and Neural Circuits examines the role of goal-directed choice. It begins with an examination of the computations performed by associated circuits, but then moves on to in-depth examinations on how goal-directed learning interacts with other forms of choice and response selection. This is the only book that embraces the multidisciplinary nature of this area of decision-making, integrating our knowledge of goal-directed decision-making from basic, computational, clinical, and ethology research into a single resource that is invaluable for neuroscientists, psychologists and computer scientists alike. The book presents discussions on the broader field of decision-making and how it has expanded to incorporate ideas related to flexible behaviors, such as cognitive control, economic choice, and Bayesian inference, as well as the influences that motivation, context and cues have on behavior and decision-making. - Details the neural circuits functionally involved in goal-directed decision-making and the computations these circuits perform - Discusses changes in goal-directed decision-making spurred by development and disorders, and within real-world applications, including social contexts and addiction - Synthesizes neuroscience, psychology and computer science research to offer a unique perspective on the central and emerging issues in goal-directed decision-making
This new study presents exciting international research developments on personal control and self-regulation. Each chapter examines the subject at a different level of analysis to foster a complete understanding. Brief synopses of each chapter are provided as introductions to the three major sections of the book. These sections cover the person as an agent of control, affective and cognitive mechanisms of executive agency, and reactions to threatened control.
Decision making is the process of selecting a possible course of action from all the available alternatives. In almost all such problems the multiplicity of criteria for judging the alternatives is pervasive. That is, for many such problems, the decision maker (OM) wants to attain more than one objective or goal in selecting the course of action while satisfying the constraints dictated by environment, processes, and resources. Another characteristic of these problems is that the objectives are apparently non commensurable. Mathematically, these problems can be represented as: (1. 1 ) subject to: gi(~) ~ 0, ,', . . . ,. ! where ~ is an n dimensional decision variable vector. The problem consists of n decision variables, m constraints and k objectives. Any or all of the functions may be nonlinear. In literature this problem is often referred to as a vector maximum problem (VMP). Traditionally there are two approaches for solving the VMP. One of them is to optimize one of the objectives while appending the other objectives to a constraint set so that the optimal solution would satisfy these objectives at least up to a predetermined level. The problem is given as: Max f. ~) 1 (1. 2) subject to: where at is any acceptable predetermined level for objective t. The other approach is to optimize a super-objective function created by multiplying each 2 objective function with a suitable weight and then by adding them together.
Simulations are widely used in the military for training personnel, analyzing proposed equipment, and rehearsing missions, and these simulations need realistic models of human behavior. This book draws together a wide variety of theoretical and applied research in human behavior modeling that can be considered for use in those simulations. It covers behavior at the individual, unit, and command level. At the individual soldier level, the topics covered include attention, learning, memory, decisionmaking, perception, situation awareness, and planning. At the unit level, the focus is on command and control. The book provides short-, medium-, and long-term goals for research and development of more realistic models of human behavior.
-Identify your critical decisions. Focus on those that matter most to your company's performance. --
This breakthrough study examines how business decisions explain successful and unsuccessful performance. Real world and academic research is evaluated, including interviews and cases studies, to create a model of how decisions and performance are connected for businesses of all sizes. Recommendations are made to optimize decision making and projections about the future of decision making and performance are provided.
Naturalistic Decision Making is an important area of research in applied psychology. This book comes from selected topics at the 1998 conference on NDM, held in Virginia.
Building on lecture notes from his acclaimed course at Stanford University, James March provides a brilliant introduction to decision making, a central human activity fundamental to individual, group, organizational, and societal life. March draws on research from all the disciplines of social and behavioral science to show decision making in its broadest context. By emphasizing how decisions are actually made -- as opposed to how they should be made -- he enables those involved in the process to understand it both as observers and as participants. March sheds new light on the decision-making process by delineating four deep issues that persistently divide students of decision making: Are decisions based on rational choices involving preferences and expected consequences, or on rules that are appropriate to the identity of the decision maker and the situation? Is decision making a consistent, clear process or one characterized by ambiguity and inconsistency? Is decision making significant primarily for its outcomes, or for the individual and social meanings it creates and sustains? And finally, are the outcomes of decision processes attributable solely to the actions of individuals, or to the combined influence of interacting individuals, organizations, and societies? March's observations on how intelligence is -- or is not -- achieved through decision making, and possibilities for enhancing decision intelligence, are also provided. March explains key concepts of vital importance to students of decision making and decision makers, such as limited rationality, history-dependent rules, and ambiguity, and weaves these ideas into a full depiction of decision making. He includes a discussion of the modern aspects of several classic issues underlying these concepts, such as the relation between reason and ignorance, intentionality and fate, and meaning and interpretation. This valuable textbook by one of the seminal figures in the history of organizational decision making will be required reading for a new generation of scholars, managers, and other decision makers.
Employees are constantly making decisions and judgments that have the potential to affect themselves, their families, their work organizations, and on some occasion even the broader societies in which they live. A few examples include: deciding which job applicant to hire, setting a production goal, judging one’s level of job satisfaction, deciding to steal from the cash register, agreeing to help organize the company’s holiday party, forecasting corporate tax rates two years later, deciding to report a coworker for sexual harassment, and predicting the level of risk inherent in a new business venture. In other words, a great many topics of interest to organizational researchers ultimately reduce to decisions made by employees. Yet, numerous entreaties notwithstanding, industrial and organizational psychologists typically have not incorporated a judgment and decision-making perspective in their research. The current book begins to remedy the situation by facilitating cross-pollination between the disciplines of organizational psychology and decision-making. The book describes both laboratory and more “naturalistic” field research on judgment and decision-making, and applies it to core topics of interest to industrial and organizational psychologists: performance appraisal, employee selection, individual differences, goals, leadership, teams, and stress, among others. The book also suggests ways in which industrial and organizational psychology research can benefit the discipline of judgment and decision-making. The authors of the chapters in this book conduct research at the intersection of organizational psychology and decision-making, and consequently are uniquely positioned to bridging the divide between the two disciplines.