Description : How to improve decision-making skills in realistic situations and do it in a reasonably nonmathematical fashion. Develops practical techniques for deciding upon the best strategies in a variety of situations. Provides methods for reducing complex problems to easily-drawn decision diagrams (trees), supported by real-world examples. Includes detailed cases that employ the methods described in the text. Each chapter contains illustrative examples and exercises.
Description : This Book Is Designed To Serve As A Text For Management, Economics, Accountancy (Chartered And Cost Accountancy), And Commerce Students. The Book Covers Concepts, Illustrations And Problems In Statistics And Operations Research. Part I Deals With Statistical Techniques For Decision Making. Part Ii Studies Various Operations Research Techniques For Managerial Decisions.The Book Contains Illustrations And Problems, Drawn Extensively From Various Functional Areas Of Management, Viz., Production, Finance, Marketing And Personnel, Which Are Designed To Understand Real Life Decision Making Situations. In Order To Make The Book Self-Contained, All Relevant Mathematical Concepts And Their Applications Have Been Included. To Enhance The Understanding Of The Subject Matter By The Students Belonging To Different Disciplines, The Approach Adopted In This Book, Both In Statistics And Operations Research, Is Conceptional Rather Than Mathematical. Hence Complicated Mathematical Proofs Have Been Avoided.This Book Would Be An Ideal Reference To Executives, Computer Professionals, Industrial Engineers, Economic Planners And Social Scientists. The Other Books By The Same Authors Are: Operations Research For Management And Business Statistics.
Description : These authors draw on nearly 50 years of combined teaching and consulting experience to give readers a straightforward yet systematic approach for making estimates about the likelihood and consequences of future events -- and then using those assessments to arrive at sound decisions. The book's real-world cases, supplemented with expository text and spreadsheets, help readers master such techniques as decision trees and simulation, such concepts as probability, the value of information, and strategic gaming; and such applications as inventory stocking problems, bidding situations, and negotiating.
Description : Professor Dreze is a highly respected mathematical economist and econometrician. This book brings together some of his major contributions to the economic theory of decision making under uncertainty, and also several essays. These include an important essay on 'Decision theory under moral hazard and state dependent preferences' that significantly extends modern theory, and which provides rigorous foundations for subsequent chapters. Topics covered within the theory include decision theory, market allocation and prices, consumer decisions, theory of the firm, labour contracts, and public decisions.
Description : This text focuses on how decision analysis can be used to support the managerial decision process. It supports professors and students in the classroom with extensive case studies and problem sets, and with Arborist software and documentation.
Description : This custom edition is published for the University of Newcastle. The content in this custom book has been chosen specifically for your course by Associate Professor Martin Fitzgerald. The information comes from a range of different publications to provide you with a single source of academic writings on managerial decision-making.
Description : Decision making plays a crucial role in managerial life. But too often, our decisions are clouded by personal biases and uncertainty. This brief book shows readers how to identify their own biases in order to make better decisions. Experimental in approach, the book teaches decision making by involving the reader in decision quizzes.
Description : The decision to invest in oil field development is an extremely complex problem, even in the absence of uncertainty, due to the great number of technological alternatives that may be used, to the dynamic complexity of oil reservoirs - which involves mul- phase flows (oil, gas and water) in porous media with phase change, and to the c- plicated combinatorial optimization problem of choosing the optimal oil well network, that is, choosing the number and types of wells (horizontal, vertical, directional, m- tilateral) required for draining oil from a field with a view to maximizing its economic value. This problem becomes even more difficult when technical uncertainty and e- nomic uncertainty are considered. The former are uncertainties regarding the existence, volume and quality of a reservoir and may encourage an investment in information before the field is developed, in order to reduce these uncertainties and thus optimize the heavy investments required for developing the reservoir. The economic or market uncertainties are associated with the general movements of the economy, such as oil prices, gas demand, exchange rates, etc. , and may lead decision-makers to defer - vestments and wait for better market conditions. Choosing the optimal investment moment under uncertainty is a complex problem which traditionally involves dynamic programming tools and other techniques that are used by the real options theory.
Description : Unlike most introductory texts in statistics, Introduction toStatistical Decision Theory integrates statistical inference withdecision making and discusses real-world actions involving economic payoffs and risks.