Models And Applications In The Decision Sciences

NEW ADVANCES IN THE SCIENCE OF DECISION MAKING: Practical and relevant research from DSI, the field’s leading organization 14 OUTSTANDING PAPERS APPLYING RIGOROUS RESEARCH METHODS TO IMPORTANT SOCIETAL AND BUSINESS DECISION ENVIRONMENTS NEW OPPORTUNITIES TO IMPROVE PERFORMANCE IN STRATEGY, TACTICS, AND OPERATIONS FOR ALL DECISION MAKERS, AND ALL DECISION SCIENCE RESEARCHERS AND STUDENTS More than 1,000 papers were submitted to the Decision Science Institute’s 2015 annual conference. This book presents the 14 papers chosen as most insightful and useful. This peer-reviewed research addresses a richly diverse set of business topics, illuminating opportunities to improve decision making at strategic, tactical, and operational levels. Spanning analytics, information systems and technology, supply chain operations management, and other disciplines, these papers identify multiple opportunities for immediate and long-term performance improvement. The authors address challenges ranging from talent management to lean transformation, mobile app marketing to corporate ethics, driving change to predicting stock prices. Their work reflects both the intellectual vibrancy of the discipline of decision science and its immense practical value. Decision sciences research leads to improved decision outcomes. This volume brings together peer-reviewed papers chosen as “best of the best” by the field’s leading organization, the Decision Sciences Institute. Authored by respected researchers worldwide, these papers were presented at DSI’s 46th Annual Meeting in Seattle. They describe new methods and approaches in the decision sciences, with a special focus on translating theoretical impact into practical relevance to improve decision making within business, public policy, non-profit organizations, and beyond. Assess willingness to learn ERP systems based on knowledge update and other factors Exploit application integration to improve ERP’s value after implementation Discover how mobile users decide whether to search for and adopt a new app Quantify links between absenteeism and hostile environment/sexual harassment Assess correlations between employee development and worker outcomes Explore perceptions of change, intentions to leave, and the role of cynicism Promote lean transformation by evolving HR performance management systems Understand how links between corporate ethical values and firm performance are mediated Bring a global sourcing perspective to issues of ethical consumption Improve quality by choosing practices with the best cultural fit Use Multilayer Perceptron (MLP) and Bayesian Networks (BN) to predict diabetes Apply a comprehensive empirical framework for assessing patient care quality Promote sharing of clinical knowledge among a practice group’s physicians Forecast variable impacts in S&P 500 equity prices

Multi-criteria decision-making (MCDM) has gained vast popularity for its ability to help make decisions in the presence of various similar and conflicting choices.This new volume applies the MCDM theory to solving problems and challenges in manufacturing environments. It discusses using MCDM computational methods to evaluate and select the most optimal solution or method for real-world, real-time manufacutring engineering issues. It details the decision-making process in relation materials selection; identification, assessment, and evaluation of risk; sustainability assessment; selection of green suppliers; and more. The chapter authors demonstrate the application of myriad MCDM techniques in decision-making, including MADM (multiple attribute decision-making), DEA (data envelopment analysis), fuzzy TOPSIS (technique for order preference by similarities to ideal solution), fuzzy-VIKOR (multicriteria optimization and compromise solution); MOORA (multi-objective optimization on the basis of ratio analysis), EWM (entropy weight method), (AHP) analytic hierarchy process, TODIM (TOmada de Decisao Interativa Multicriterio), and others. The volume illustrates these MCDM models in several industries and industrial processes, including for experimental analysis and optimization of drilling of glass fiber reinforced plastic, in the textile industries, for selection of refrigerants for domestic applications, and others.

This book presents best practices involving applications of decision sciences, business tactics and behavioral sciences for COVID-19. Addressing concrete problems in these vital fields, it focuses on theoretical and methodological investigations of managerial decisions that drive production and service enterprises’ productivity and success. Moreover, it presents optimization techniques and tools that can also be adopted for other applications in various research areas after a thorough analysis of the specific problem. The book is intended for researchers and practitioners seeking optimum solutions to real-life problems in various application areas concerning COVID-19, helping them make scientifically founded decisions.

Decision science is the discipline that is concerned with the development and applications of quantitative methods and techniques to support decision making processes. This extensively revised edition of two former versions of the book discusses the general principles and often used optimization techniques such as linear programming, integer programming, dynamic programming, non-linear programming, network theory, simulation and stochastic programming. This book aims to fill in the gap between theory and practice. It discusses the theoretical background of important quantitative methods and techniques as well as how they can be applied to practical decision making problems. Therefore, the modeling process is illustrated with examples of firms, consumers, governments and other non-profit organizations in agriculture related sectors. The authors have used their vast didactical experience to find a proper balance between mathematical exactness, knowledge and readability on the one hand and offer understanding, insights and applicability of the subjects on the other hand. The book is therefore an essential asset in introductory courses on decision science in undergraduate, postgraduate and research programmes.

"This book will provide relevant theoretical and practical frameworks and the latest research findings in the area of decision sciences and applications in the transportation sector for researchers, executives and practitioners who want to enrich their scientific knowledge and improve their understanding of the decision-making process in facing real-world problems in the transportation sector"--

One of the goals of artificial intelligence (AI) is creating autonomous agents that must make decisions based on uncertain and incomplete information. The goal is to design rational agents that must take the best action given the information available and their goals. Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions provides an introduction to different types of decision theory techniques, including MDPs, POMDPs, Influence Diagrams, and Reinforcement Learning, and illustrates their application in artificial intelligence. This book provides insights into the advantages and challenges of using decision theory models for developing intelligent systems.

Discover recent powerful advances in the theory, methods, and applications of decision and risk analysis Focusing on modern advances and innovations in the field of decision analysis (DA), Breakthroughs in Decision Science and Risk Analysis presents theories and methods for making, improving, and learning from significant practical decisions. The book explains these new methods and important applications in an accessible and stimulating style for readers from multiple backgrounds, including psychology, economics, statistics, engineering, risk analysis, operations research, and management science. Highlighting topics not conventionally found in DA textbooks, the book illustrates genuine advances in practical decision science, including developments and trends that depart from, or break with, the standard axiomatic DA paradigm in fundamental and useful ways. The book features methods for coping with realistic decision-making challenges such as online adaptive learning algorithms, innovations in robust decision-making, and the use of a variety of models to explain available data and recommend actions. In addition, the book illustrates how these techniques can be applied to dramatically improve risk management decisions. Breakthroughs in Decision Science and Risk Analysis also includes: An emphasis on new approaches rather than only classical and traditional ideas Discussions of how decision and risk analysis can be applied to improve high-stakes policy and management decisions Coverage of the potential value and realism of decision science within applications in financial, health, safety, environmental, business, engineering, and security risk management Innovative methods for deciding what actions to take when decision problems are not completely known or described or when useful probabilities cannot be specified Recent breakthroughs in the psychology and brain science of risky decisions, mathematical foundations and techniques, and integration with learning and pattern recognition methods from computational intelligence Breakthroughs in Decision Science and Risk Analysis is an ideal reference for researchers, consultants, and practitioners in the fields of decision science, operations research, business, management science, engineering, statistics, and mathematics. The book is also an appropriate guide for managers, analysts, and decision and policy makers in the areas of finance, health and safety, environment, business, engineering, and security risk management.