Rational Decision Making for Managers An Introduction

by Towler, Michael; Keast, Sarah

ISBN13:
9780470519653
ISBN10:
0470519657
Edition: 1st
Format: Paperback
Copyright: 2009-07-13
Publisher: Wiley
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Summary

The primary aim of this proposed text is to provide students with a basic understanding of rational decision making tech-niques and also to help them to recognize when they are appropriate. Once students have this ability they then need to be able to identify the characteristics of the decision to be made to guide them in their choice of techniques. While there are many introductory quantitative methods and decision-making books available, they do not tend to directly tackle this need, which is the primary aim of this proposed text. Separate chapters on robustness analysis and game theory The contextual discussion and structure is a key strength (many of the available books are collections of disjointed quanti-tative or decision making topics) Concise approach Rather than presenting techniques by similarity of methods (as most texts) this book will aim to show the characteristics of the decisions that can be informed by the use of the particular techniques.

Author Biography

Sarah Keast is a lecturer in information management at the University of Plymouth Business School. Sarah has formed an interest in the use of mathematical modelling and quantitive analysis techniques in both the economic and the general business enviornments. Michael Towler began his career in research and development and has worked in the public and private sector as well as RD management. He joined the University of Plymouth Business School in 2002 where he lectured in operations management and in business decision-making in 2008 this was followed by a move to BPP Business School.

About the Authors	p. ix
Acknowledgements	p. x
Preface	p. xi
The Decision Context	p. 1
Introduction to Decision-making	p. 3
Introduction	p. 3
What is a Decision?	p. 4
Uncertainty and Risk in Decision-taking	p. 7
Probability	p. 8
Rational Decision-taker	p. 9
Biases	p. 10
Descriptive, Normative, and Prescriptive Decision-making	p. 12
Models	p. 13
Who Should Participate in a Decision Process?	p. 15
Overview of Text	p. 17
Further Reading	p. 18
Time Series Forecasting	p. 21
Introduction	p. 21
Creating a Time Series Forecast-Overview	p. 22
Data Types	p. 22
Identifying Trends	p. 25
Decomposition	p. 31
Finding the Seasonal Component	p. 33
Average and Moving Average Forecasts	p. 39
Simple Exponential Smoothing	p. 41
Exponential Smoothing for Data with a Trend	p. 46
Exponential Smoothing for Non-Stationary Data with Seasonality	p. 49
Standard Deviation of the Forecast	p. 54
Choosing Appropriate Forecasting Models	p. 57
Transforming Data	p. 58
Alternative Time Series Forecasting Techniques	p. 59
Summary	p. 59
Further Reading	p. 60
Explanatory and Qualitative Forecasting	p. 65
Introduction	p. 65
Quantitative Explanatory Forecasting	p. 66
Linear Regression	p. 67
Elicitation of an Expert's Probabilities	p. 80
Structured Group Processes	p. 82
Scenario Analysis	p. 84
Summary	p. 85
Further Reading	p. 86
One-off and Repeat Decisions	p. 89
Inventory Management	p. 91
Introduction	p. 91
The Fixed Order Quantity Inventory System	p. 92
The Newsvendor Model	p. 110
The Economic Order Quantity Model with Known Stock-out Costs	p. 114
Summary	p. 115
Further Reading	p. 116
Payoff Matrices	p. 121
Introduction	p. 121
Payoff Matrices with Certainty	p. 123
Payoff Matrices with Multiple Future States and a Dominant Strategy	p. 123
Payoff Matrices with Strict Uncertainty	p. 124
Payoff Matrices with Uncertainty or Risk	p. 134
Choosing a Decision Criterion	p. 136
The Value of Perfect Information	p. 139
Sensitivity Analysis	p. 142
Summary	p. 144
Further Reading	p. 145
Linear Programming	p. 151
Introduction	p. 151
Solving the Linear Programme	p. 154
Corner Method	p. 160
Sensitivity Analysis	p. 166
Changing Constraints	p. 166
Changing the Objective Function	p. 169
Using Excel Solver	p. 171
Integer Programming	p. 182
Formulating Decision-making Problems as Linear Programmes	p. 185
Summary	p. 187
Further Reading	p. 188
Simultaneous Move Games	p. 193
Introduction	p. 193
Terminology	p. 194
Zero-sum Games	p. 195
Non-zero-sum Games	p. 200
Mixed Strategies for Players with Three or More Strategies	p. 207
Continuous Strategies	p. 212
N-Player Games	p. 214
Summary	p. 215
Further Reading	p. 216
Sequential Decisions	p. 223
Robustness Analysis	p. 225
Introduction	p. 225
Robustness Analysis	p. 227
Robustness Analysis as a Framework: Literature Examples	p. 234
Further Reading	p. 238
Decision Tree Analysis	p. 239
Introduction	p. 239
Decision Tree Notation	p. 240
Constructing a Decision Tree	p. 240
Rolling Back a Decision Tree 1: Sequential Decision and Event Nodes	p. 241
Rolling Back a Decision Tree 2: Waiting for Uncertainty to Resolve	p. 244
Rolling Back a Decision Tree 3: Exploratory Actions and Posterior Probabilities	p. 245
Introduction to Sensitivity Analysis	p. 250
Univariate Sensitivity Analysis	p. 251
Bivariate Sensitivity Analysis	p. 260
N-Way (Multivariate) Sensitivity Analysis	p. 260
Summary of the Decision Tree Analysis Method	p. 262
Chapter Appendix. A Brief Introduction to Monte Carlo Simulation	p. 262
Further Reading	p. 266
Sequential Games	p. 275
Introduction	p. 275
Extensive Form	p. 276
Rollback Revisited	p. 277
Asymmetry of Information	p. 280
Signals	p. 284
Signal Jamming and Screening	p. 287
Bargaining	p. 287
Summary	p. 290
Further Reading	p. 291
Appendix: Mathematics Revision	p. 297
References	p. 327
Index	p. 331
Table of Contents provided by Ingram. All Rights Reserved.

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