An Emerging Process Of Building Models For Management Decision Makers
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An Emerging Process Of Building Models For Management Decision Makers Classic Reprint
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Author : Glen L. Urban
language : en
Publisher: Forgotten Books
Release Date : 2016-11-16
An Emerging Process Of Building Models For Management Decision Makers Classic Reprint written by Glen L. Urban and has been published by Forgotten Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-16 with Business & Economics categories.
Excerpt from An Emerging Process of Building Models for Management Decision Makers With a lack of full knowledge of implementation, it is difficult to explicitly define the state of the art, but based on the author's discussion with practitioners'in.companies, the literature, and management seminar discussions over the last five years, figure one seems to be a reasonable description. Implementation is divided into: 1) experimental use first trial, (2) emerging use wider testing, (3) continuing use by one manager, and (4) institutionalization use by many managers on a continuing basis as part of their decision procedure. Decisions from control to strategic planning are represented on the second dimension. The graph should be interpreted analogously to a regression line based on individual applications representing points. Very simple models often used to present data to managers are not included in figure one. For example, a pro - forma balance sheet reflects the accounting model of the firm and sales reports may reflect a geographic model of the market. Many firms use simple format models to display data to decision makers. Some decision makers rely on such data and use it in their decision making. This would imply a high degree of implementation. It should be noted, however, that one is amazed at how very little of the data Spued out by information systems is used. Figure one does not consider the simple structures used to retrieve and display data since consideration in this paper will center around formal mathematical models. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.
An Emerging Process Of Building Models For Management Decision Makers
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Author : Glen L. Urban
language : en
Publisher:
Release Date : 1972
An Emerging Process Of Building Models For Management Decision Makers written by Glen L. Urban and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1972 with Decision making categories.
Building Models For Marketing Decisions
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Author : Peter S.H. Leeflang
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-29
Building Models For Marketing Decisions written by Peter S.H. Leeflang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-29 with Business & Economics categories.
This book is about marketing models and the process of model building. Our primary focus is on models that can be used by managers to support marketing decisions. It has long been known that simple models usually outperform judgments in predicting outcomes in a wide variety of contexts. For example, models of judgments tend to provide better forecasts of the outcomes than the judgments themselves (because the model eliminates the noise in judgments). And since judgments never fully reflect the complexities of the many forces that influence outcomes, it is easy to see why models of actual outcomes should be very attractive to (marketing) decision makers. Thus, appropriately constructed models can provide insights about structural relations between marketing variables. Since models explicate the relations, both the process of model building and the model that ultimately results can improve the quality of marketing decisions. Managers often use rules of thumb for decisions. For example, a brand manager will have defined a specific set of alternative brands as the competitive set within a product category. Usually this set is based on perceived similarities in brand characteristics, advertising messages, etc. If a new marketing initiative occurs for one of the other brands, the brand manager will have a strong inclination to react. The reaction is partly based on the manager's desire to maintain some competitive parity in the mar keting variables.
Growth Dynamics In New Markets
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Author : Martin F. G. Schaffernicht
language : en
Publisher: John Wiley & Sons
Release Date : 2018-04-16
Growth Dynamics In New Markets written by Martin F. G. Schaffernicht and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-16 with Business & Economics categories.
An innovative simulation-based approach for strategic decision making when launching new products Growth Dynamics in New Markets contains a dynamic case study and simulations that reveal what it takes to successfully introduce a product into a new market. Written by experts in the field, the text and companion website include a compelling simulation game and a variety of simulation models. Using the simulation game and computer models, readers are challenged to design and put in place a strategy about product introduction and competitive behavior. The simulation models build on each other to help to arrive at a comprehensive understanding of product uptake as well as market development and competitive dynamics. The authors present different approaches for enhancing the models and offer guidance for applying them to real-world problems. This groundbreaking text clearly shows how to develop maps of dynamic systems, formulate candidate policies and evaluate them based on the simulations. It also reveals how to use computer simulations to understand what decisions could and should be made, when to make them and how intensive they should be. The authors present an interactive approach that: Contains an innovative combination of a case study, simulation game and simulation models for developing the skills to introduce a product to the marketplace Offers targeted questions that help to enhance the understanding of the material presented Presents detailed answers and solutions to a number or real-world business challenges Features video tutorials that explain how the simulation experiments are implemented and interpreted Aids in the development an action-oriented, pragmatic understanding of the underlying forces in business Designed for students of business administration, management, industrial engineering, informatics, engineering, and public policy, Growth Dynamics in New Markets offers an innovative approach that combines the practice of dynamic reasoning and the use of simulation to design and test possible policies.
Managing Project Risk And Uncertainty
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Author : Chris Chapman
language : en
Publisher: John Wiley & Sons
Release Date : 2002-10-11
Managing Project Risk And Uncertainty written by Chris Chapman and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-10-11 with Business & Economics categories.
This title confidently puts forward a practical, new approach to decision making in an uncertain business world. Many variables are accounted for and the authors are innovative in integrating previous types of decision-making approaches with a more fluid, and therefore realistic model that can be applied across a wide range of contexts and decisions. A new title on a important topic that not only stands well on its own, but also complements Chapman and Ward's previous title Project Risk Management. This book is practical and rigorous yet written in an engaging way. It is perfect for courses, or to be used by practitioners.
Models Of Scenario Building And Planning
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Author : A. Martelli
language : en
Publisher: Springer
Release Date : 2014-10-01
Models Of Scenario Building And Planning written by A. Martelli and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-01 with Business & Economics categories.
Models of Scenario Building and Planning offers a unique and innovative exploration of the scenario approach. The book focuses on the analysis of the competitors' behavior; the analysis of risk and uncertainty; and the link between scenarios and strategies.
Management Decision Making Big Data And Analytics
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Author : Simone Gressel
language : en
Publisher: SAGE
Release Date : 2020-10-12
Management Decision Making Big Data And Analytics written by Simone Gressel and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-12 with Business & Economics categories.
An exciting new textbook examining big data and business analytics to look at how they can help managers become more effective decision-makers.
A Professional S Guide To Decision Science And Problem Solving
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Author : Frank A. Tillman
language : en
Publisher: FT Press
Release Date : 2012
A Professional S Guide To Decision Science And Problem Solving written by Frank A. Tillman and has been published by FT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Business & Economics categories.
A Professional's Guide to Decision Science and Problem Solving provides an integrated, start-to-finish framework for more effective problem solving and decision making in corporations. Drawing on vast experience in the field, the authors show how to apply state-of-the-art decision science, statistical modeling, benchmarking, and processing modeling techniques together to create a robust analytical framework for better decision making in any field, especially those that rely on advanced operations management. They integrate both newly-developed and time-tested techniques into a logical, structured approach for assessing corporate issues, developing solutions, and making decisions that drive the successful achievement of corporate objectives. Coverage includes: defining objectives, exploring the environment; scoping problems and evaluating their importance; bringing data mining and statistical analysis to bear; solving problems and measuring the results; evaluating the results and performing sensitivity analysis, and more. The book concludes with three case study chapters that walk through the effective use of its methods, step-by-step. Representing a wide variety of corporate environments, these case studies underscore and demonstrate the method's exceptional adaptability. This book will be valuable in a wide range of industries, notably finance, pharmaceutical, healthcare, economics, and manufacturing.
Model Based Decision Support Methodology With Environmental Applications
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Author : Andrzej P. Wierzbicki
language : en
Publisher: Springer
Release Date : 2010-12-15
Model Based Decision Support Methodology With Environmental Applications written by Andrzej P. Wierzbicki and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-12-15 with Mathematics categories.
The complexity of issues requiring rational decision making grows and thus such decisions are becoming more and more difficult, despite advances in methodology and tools for decision support and in other areas of research. Globalization, interlinks between environmental, industrial, social and political issues, and rapid speed of change all contribute to the increase of this complexity. Specialized knowledge about decision-making processes and their support is increasing, but a large spectrum of approaches presented in the literature is typically illustrated only by simple examples. Moreover, the integration of model-based decision support methodologies and tools with specialized model-based knowledge developed for handling real problems in environmental, engineering, industrial, economical, social and political activities is often not satisfactory. Therefore, there is a need to present the state of art of methodology and tools for development of model-based decision support systems, and illustrate this state by applications to various complex real-world decision problems. The monograph reports many years of experience of many researchers, who have not only contributed to the developments in operations research but also succeeded to integrate knowledge and craft of various disciplines into several modern decision support systems which have been applied to actual complex decision-making processes in various fields of policy making. The experience presented in this book will be of value to researchers and practitioners in various fields. The issues discussed in this book gain in importance with the development of the new era of the information society, where information, knowledge, and ways of processing them become a decisive part of human activities. The examples presented in this book illustrate how how various methods and tools of model-based decision support can actually be used for helping modern decision makers that face complex problems. Overview of the contents: The first part of this three-part book presents the methodological background and characteristics of modern decision-making environment, and the value of model-based decision support thus addressing current challenges of decision support. It also provides the methodology of building and analyzing mathematical models that represent underlying physical and economic processes, and that are useful for modern decision makers at various stages of decision making. These methods support not only the analysis of Pareto-efficient solutions that correspond best to decision maker preferences but also allow the use of other modeling concepts like soft constraints, soft simulation, or inverse simulation. The second part describes various types of tools that are used for the development of decision support systems. These include tools for modeling, simulation, optimization, tools supporting choice and user interfaces. The described tools are both standard, commercially available, and nonstandard, public domain or shareware software, which are robust enough to be used also for complex applications. All four environmental applications (regional water quality management, land use planning, cost-effective policies aimed at improving the European air quality, energy planning with environmental implications) presented in the third part of the book rely on many years of cooperation between the authors of the book with several IIASA's projects, and with many researchers from the wide IIASA network of collaborating institutions. All these applications are characterized by an intensive use of model-based decision support. Finally, the appendix contains a short description of some of the tools described in the book that are available from IIASA, free of charge, for research and educational purposes. The experiences reported in this book indicate that the development of DSSs for strategic environmental decision making should be a joint effort involving experts in the subject area, modelers, and decision support experts. For the other experiences discussed in this book, the authors stress the importance of good data bases, and good libraries of tools. One of the most important requirements is a modular structure of a DSS that enhances the reusability of system modules. In such modular structures, user interfaces play an important role. The book shows how modern achievements in mathematical programming and computer sciences may be exploited for supporting decision making, especially about strategic environmental problems. It presents the methodological background of various methods for model-based decision support and reviews methods and tools for model development and analysis. The methods and tools are amply illustrated with extensive applications. Audience: This book will be of interest to researchers and practitioners in the fields of model development and analysis, model-based decision analysis and support, (particularly in the environment, economics, agriculture, engineering, and negotiations areas) and mathematical programming. For understanding of some parts of the text a background in mathematics and operational research is required but several chapters of the book will be of value also for readers without such a background. The monograph is also suitable for use as a text book for courses on advanced (Master and Ph.D.) levels for programs on Operations Research, decision analysis, decision support and various environmental studies (depending on the program different parts of the book may be emphasized).
Multi Level Decision Making
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Author : Guangquan Zhang
language : en
Publisher: Springer
Release Date : 2015-02-07
Multi Level Decision Making written by Guangquan Zhang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-07 with Technology & Engineering categories.
This monograph presents new developments in multi-level decision-making theory, technique and method in both modeling and solution issues. It especially presents how a decision support system can support managers in reaching a solution to a multi-level decision problem in practice. This monograph combines decision theories, methods, algorithms and applications effectively. It discusses in detail the models and solution algorithms of each issue of bi-level and tri-level decision-making, such as multi-leaders, multi-followers, multi-objectives, rule-set-based, and fuzzy parameters. Potential readers include organizational managers and practicing professionals, who can use the methods and software provided to solve their real decision problems; PhD students and researchers in the areas of bi-level and multi-level decision-making and decision support systems; students at an advanced undergraduate, master’s level in information systems, business administration, or the application of computer science.
