This article develops multiobjective models of hospital decision making that incorporate the internal decision process in both a for-profit and a non-profit hospital (NPH). Predicted output and quality for an NPH differ from those for a for-profit hospital under some conditions but converge under others. Convergence may be the result of a complex internal decision structure with decision control primarily by physicians, similar objectives across different organizational forms, or differing constraints. The mechanisms underlying these outcomes provide explanations for conflicting results in empirical studies of non-profit and for-profit hospitals and provide a different rationale for convergence than non-profit response to competition from for-profit hospitals. Understanding the source of convergence is important for policies directed toward the tax treatment of NPHs.

At the core of the many debates throughout cognitive science concerning how decisions are made are the processes governing the time course of preference formation and decision. From perceptual choices, such as whether the signal on a radar screen indicates an enemy missile or a spot on a CT scan indicates a tumor, to cognitive value-based decisions, such as selecting an agreeable flatmate or deciding the guilt of a defendant, significant and everyday decisions are dynamic over time. Phenomena such as decoy effects, preference reversals and order effects are still puzzling researchers. For example, in a legal context, jurors receive discrete pieces of evidence in sequence, and must integrate these pieces together to reach a singular verdict. From a standard Bayesian viewpoint the order in which people receive the evidence should not influence their final decision, and yet order effects seem a robust empirical phenomena in many decision contexts. Current research on how decisions unfold, especially in a dynamic environment, is advancing our theoretical understanding of decision making. This Research Topic aims to review and further explore the time course of a decision - from how prior beliefs are formed to how those beliefs are used and updated over time, towards the formation of preferences and choices and post-decision processes and effects. Research literatures encompassing varied approaches to the time-scale of decisions will be brought into scope: a) Speeded decisions (and post-decision processes) that require the accumulation of noisy and possibly non-stationary perceptual evidence (e.g., randomly moving dots stimuli), within a few seconds, with or without temporal uncertainty. b) Temporally-extended, value-based decisions that integrate feedback values (e.g., gambling machines) and internally-generated decision criteria (e.g., when one switches attention, selectively, between the various aspects of several choice alternatives). c) Temporally extended, belief-based decisions that build on the integration of evidence, which interacts with the decision maker's belief system, towards the updating of the beliefs and the formation of judgments and preferences (as in the legal context). Research that emphasizes theoretical concerns (including optimality analysis) and mechanisms underlying the decision process, both neural and cognitive, is presented, as well as research that combines experimental and computational levels of analysis.

In the current fast-paced and constantly changing business environment, it is more important than ever for organizations to be agile, monitor business performance, and meet with increasingly stringent compliance requirements. Written by pioneering consultants and bestselling authors with track records of international success, The Decision Model: A

This unique volume introduces and discusses the methods of validating computer simulations in scientific research. The core concepts, strategies, and techniques of validation are explained by an international team of pre-eminent authorities, drawing on expertise from various fields ranging from engineering and the physical sciences to the social sciences and history. The work also offers new and original philosophical perspectives on the validation of simulations. Topics and features: introduces the fundamental concepts and principles related to the validation of computer simulations, and examines philosophical frameworks for thinking about validation; provides an overview of the various strategies and techniques available for validating simulations, as well as the preparatory steps that have to be taken prior to validation; describes commonly used reference points and mathematical frameworks applicable to simulation validation; reviews the legal prescriptions, and the administrative and procedural activities related to simulation validation; presents examples of best practice that demonstrate how methods of validation are applied in various disciplines and with different types of simulation models; covers important practical challenges faced by simulation scientists when applying validation methods and techniques; offers a selection of general philosophical reflections that explore the significance of validation from a broader perspective. This truly interdisciplinary handbook will appeal to a broad audience, from professional scientists spanning all natural and social sciences, to young scholars new to research with computer simulations. Philosophers of science, and methodologists seeking to increase their understanding of simulation validation, will also find much to benefit from in the text.

This book fills a void for a balanced approach to spreadsheet-based decision modeling. In addition to using spreadsheets as a tool to quickly set up and solve decision models, the authors show how and why the methods work and combine the user's power to logically model and analyze diverse decision-making scenarios with software-based solutions. The book discusses the fundamental concepts, assumptions and limitations behind each decision modeling technique, shows how each decision model works, and illustrates the real-world usefulness of each technique with many applications from both profit and nonprofit organizations. The authors provide an introduction to managerial decision modeling, linear programming models, modeling applications and sensitivity analysis, transportation, assignment and network models, integer, goal, and nonlinear programming models, project management, decision theory, queuing models, simulation modeling, forecasting models and inventory control models. The additional material files Chapter 12 Excel files for each chapter Excel modules for Windows Excel modules for Mac 4th edition errata can be found at https://www.degruyter.com/view/product/486941