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Applied Decision-Making by Mauricio A. Sanchez,Leocundo Aguilar,Manuel Castañón-Puga,Antonio Rodríguez Pdf
This book gathers a collection of the latest research, applications, and proposals, introducing readers to innovations and concepts from diverse environments and systems. As such, it will provide students and professionals alike with not only cutting-edge information, but also new inspirations and potential research directions. Each chapter focuses on a specific aspect of applied decision making, e.g. in complex systems, computational intelligence, security, and ubiquitous computing.
Business Research for Decision Making by Duane Davis Pdf
This Fifth Edition reflects the ever-increasing changes in the tools and technology available today. Duane Davis teaches students and managers how to develop ways to efficiently and effectively plan, collect, organize, and assimilate information to make informed business decisions. This book covers the fundamentals of conducting research as well as the recent advancements in the field of business research such as the use of the Internet, qualitative research, and modern analytical tools (SPSS and Excel). The new edition is available packaged with the SPSS Student Version Software.
Strategic Decision Making by Navneet Bhushan,Kanwal Rai Pdf
Strategic Decision Making provides an effective, formal methodology that provides help with decision making problems, especially strategic ones with high stakes involving human perceptions and judgements. Focusing on applying the AHP to decision-making problems, Strategic Decision Making covers problems in the realms of business, defence and governance. Using case studies drawn from years of experience, the book discusses decision making for real life problems and includes many worked examples and solutions to problems throughout. The reader will gain comprehensive exposure to the extent of assistance that a formal methodology, such as AHP, can provide to the decision maker in evolving decisions in complex and varied domains.
How should one choose the best restaurant to eat in? Can one really make money at gambling? Or predict the future? Naive Decision Making presents the mathematical basis for making decisions where the outcome may be uncertain or the interests of others have to taken into consideration. Professor Körner takes the reader on an enjoyable journey through many aspects of mathematical decision making, with pithy observations, anecdotes and quotations. Topics include probability, statistics, Arrow's theorem, Game Theory and Nash equilibrium. Readers will also gain a great deal of insight into mathematics in general and the role it can play within society. Intended for those with elementary calculus, this book is ideal as a supplementary text for undergraduate courses in probability, game theory and decision making. Engaging and intriguing, it will also appeal to all those of a mathematical mind. To aid understanding, many exercises are included, with solutions available online.
Human Judgment and Decision Processes in Applied Settings by Martin F. Kaplan,Steven Schwartz Pdf
Human Judgment and Decision Processes in Applied Settings is the second to two volumes that attempt to define the areas of progress in the understanding of human decision making processes. The first volume, Human Judgment and Decision Processes (Academic Press, 1975) was concerned with formal and mathematical approaches to the problems of judgment and decision making. The major theoretical orientations (information integration theory, signal detection theory, portfolio theory, and multiattribute-utility measurement) were presented and their rationales discussed. The present volume is concerned with the application of these theories, and the various techniques derived from them, to the problems of decision making in the everyday world. The chapters reflect the many modifications and adjustments that must be made to mathematical rules in order to apply decision theory models in the real world. The tools described serve a broad variety of interests: those of the urban health or social planner, the organizational manager, the researcher, the educator, and, in fact, all of those who must weight evidence to reach decisions. Planner, manager, researcher, teacher, policymaker—all will find assistance in overcoming the commonly encountered roadblocks when one must choose between alternatives in what remains an uncertain world.
Multi-criteria Decision Making Methods by Evangelos Triantaphyllou Pdf
Multi-Criteria Decision Making (MCDM) has been one of the fastest growing problem areas in many disciplines. The central problem is how to evaluate a set of alternatives in terms of a number of criteria. Although this problem is very relevant in practice, there are few methods available and their quality is hard to determine. Thus, the question `Which is the best method for a given problem?' has become one of the most important and challenging ones. This is exactly what this book has as its focus and why it is important. The author extensively compares, both theoretically and empirically, real-life MCDM issues and makes the reader aware of quite a number of surprising `abnormalities' with some of these methods. What makes this book so valuable and different is that even though the analyses are rigorous, the results can be understood even by the non-specialist. Audience: Researchers, practitioners, and students; it can be used as a textbook for senior undergraduate or graduate courses in business and engineering.
Decision Making And Problem Solving by Sachi Nandan Mohanty Pdf
In Decision Making and Problem Solving: A Practical Guide for Applied Research, the author utilizes traditional approaches, tools, and techniques adopted to solve current day-to-day, real-life problems. The book offers guidance in identifying and applying accurate methods for designing a strategy as well as implementing these strategies in the real world. The book includes realistic case studies and practical approaches that should help readers understand how the decision making occurs and can be applied to problem solving under deep uncertainty.
Applied Intelligent Decision Making in Machine Learning by Himansu Das,Jitendra Kumar Rout,Suresh Chandra Moharana,Nilanjan Dey Pdf
The objective of this edited book is to share the outcomes from various research domains to develop efficient, adaptive, and intelligent models to handle the challenges related to decision making. It incorporates the advances in machine intelligent techniques such as data streaming, classification, clustering, pattern matching, feature selection, and deep learning in the decision-making process for several diversified applications such as agriculture, character recognition, landslide susceptibility, recommendation systems, forecasting air quality, healthcare, exchange rate prediction, and image dehazing. It also provides a premier interdisciplinary platform for scientists, researchers, practitioners, and educators to share their thoughts in the context of recent innovations, trends, developments, practical challenges, and advancements in the field of data mining, machine learning, soft computing, and decision science. It also focuses on the usefulness of applied intelligent techniques in the decision-making process in several aspects. To address these objectives, this edited book includes a dozen chapters contributed by authors from around the globe. The authors attempt to solve these complex problems using several intelligent machine-learning techniques. This allows researchers to understand the mechanism needed to harness the decision-making process using machine-learning techniques for their own respective endeavors.
Judgment and Decision Making at Work by Scott Highhouse,Reeshad S. Dalal,Eduardo Salas Pdf
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.
Applied Decision Analysis by Francisco Javier Girón Pdf
Taking advantage of the many specialists visiting Spain prior to the INFORMS Meeting in Barcelona, hold from July 14th to July 17th 1997, we organized a work shop on Decision Analysis Applications at the Real Academia de Ciencias, Madrid, Spain, from J uly 11th to 12th 1997, under the sponsorship of de the Instituto Espaiia. This workshop had a precedent in the International Conference Decision Making: Towards the 21st Century also held at the Real Academia de Ciencias in 1993. The idea of organizing an event, this time devoted to applications of Decision Analysis, was due to Prof. Sixto Rfos, who some four years ago, .sponsored and encouraged by the Royal Academy of Sciences, was the creator of an Interdisciplinary Working Group on Decision Analysis -formed with researchers from within and outside this Academy- which has been active since then, organizing periodical meetings, and whose last project has tumed out into this Workshop. The workshop turned out to be an stimulating opportunity for communicating and discussing the enormous variety of applications of Decision Sciences. In this volume we have included most of the invited papers and a selection of refereed contributed papers. Due to the varied nature of the applications, we have grouped them into five groups ending, as way of an epilog, with a paper by Sarin which contains important insights and reftections on the nature of Decision Analysis in public and private sectors.
Customer and Business Analytics by Daniel S. Putler,Robert E. Krider Pdf
Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying open-source software, how advanced analytical tools can address various business problems. It also gives insight into some of the challenges faced when deploying these tools. Extensively classroom-tested, the tex
Applied Decision Analysis and Economic Behaviour by Andrew J. Hughes Hallett Pdf
The optimisation of economic systems over time, and in an uncertain environment, is central to the study of economic behaviour. The behaviour of rational decision makers, whether they are market agents, firms, or governments and their agencies, is governed by decisions designed to seeure the best outcomes subject to the perceived information and economic responses (inlcuding those of other agents). Economic behaviour has therefore to be analysed in terms of the outcomes of a multiperiod stochastic optimisation process containing four main components: the economic responses (the dynamic constraints, represented by an economic model); the objec tive function (the goals and their priorities); the conditioning information (expected exogenous events and the expected future state of the economy); and risk manage ment (how uncertainties are accommodated). The papers presented in this book all analyse some aspect of economic behaviour related to the objectives, information, or risk components of the decision process. While the construction of economic models obviously also has a vital role to play, that component has received much greater (or almost exclusive) attention elsewhere. These papers examine optimising behaviour in a wide range of economic problems, both theoretical and applied. They reflect a variety of concerns: economic responses under rational expectations; the Lucas critique and optimal fiscal or monetary poli eies; market management; partly endogenous goals; evaluating government reactions; locational decisions; uncertainty and information structures; and forecasting with endogenous reactions.
Use the latest data mining best practices to enable timely, actionable, evidence-based decision making throughout your organization! Real-World Data Mining demystifies current best practices, showing how to use data mining to uncover hidden patterns and correlations, and leverage these to improve all aspects of business performance. Drawing on extensive experience as a researcher, practitioner, and instructor, Dr. Dursun Delen delivers an optimal balance of concepts, techniques and applications. Without compromising either simplicity or clarity, he provides enough technical depth to help readers truly understand how data mining technologies work. Coverage includes: processes, methods, techniques, tools, and metrics; the role and management of data; text and web mining; sentiment analysis; and Big Data integration. Throughout, Delen's conceptual coverage is complemented with application case studies (examples of both successes and failures), as well as simple, hands-on tutorials. Real-World Data Mining will be valuable to professionals on analytics teams; professionals seeking certification in the field; and undergraduate or graduate students in any analytics program: concentrations, certificate-based, or degree-based.
