Rational Decision Making for Managers provides students with a basic understanding of these techniques and helps them to recognize when they are appropriate. Sarah Keast and Mike Towler also show the characteristics of the decisions that can be informed by the use of each technique, thereby guiding the reader in their choice.
Rational Decision Making for Managers features:
- separate chapters on robustness analysis and game theory
- a strong contextual discussion and clear structure
- a concise mathematical appendix
The book is essential reading for students studying business decision making, quantitative methods and business research methods. There is an accompanying website <a href="[external URL] including PowerPoint slides, teaching notes, and alternative routes through the text, additional exercises and further reading.
PART 1 The Decision Context.
1 Introduction to Decision–making.
What is a Decision?
Uncertainty and Risk in Decision–taking.
Descriptive, Normative, and Prescriptive Decision–making.
Who Should Participate in a Decision Process?.
Overview of Text.
2 Time Series Forecasting.
Creating a Time Series Forecast Overview.
Finding the Seasonal Component.
Average and Moving Average Forecasts.
Simple Exponential Smoothing.
Exponential Smoothing for Data with a Trend.
Exponential Smoothing for Non–Stationary Data with Seasonality.
Standard Deviation of the Forecast.
Choosing Appropriate Forecasting Models.
Alternative Time Series Forecasting Techniques.
3 Explanatory and Qualitative Forecasting.
Quantitative Explanatory Forecasting.
Elicitation of an Expert s Probabilities.
Structured Group Processes.
PART 2 One–off and Repeat Decisions.
4 Inventory Management.
The Fixed Order Quantity Inventory System.
The Newsvendor Model.
The Economic Order Quantity Model with Known Stock–out Costs.
5 Payoff Matrices.
Payoff Matrices with Certainty.
Payoff Matrices with Multiple Future States and a Dominant Strategy.
Payoff Matrices with Strict Uncertainty.
Payoff Matrices with Uncertainty or Risk.
Choosing a Decision Criterion.
The Value of Perfect Information.
6 Linear Programming.
Solving the Linear Programme.
Changing the Objective Function.
Using Excel Solver.
Formulating Decision–making Problems as Linear Programmes.
7 Simultaneous Move Games.
Mixed Strategies for Players with Three or More Strategies.
PART 3 Sequential Decisions.
8 Robustness Analysis.
Robustness Analysis as a Framework: Literature Examples.
9 Decision Tree Analysis.
Decision Tree Notation.
Constructing a Decision Tree.
Rolling Back a Decision Tree 1: Sequential Decision and Event Nodes.
Rolling Back a Decision Tree 2: Waiting for Uncertainty to Resolve.
Rolling Back a Decision Tree 3: Exploratory Actions and Posterior Probabilities.
Introduction to Sensitivity Analysis.
Univariate Sensitivity Analysis.
Bivariate Sensitivity Analysis.
N–Way (Multivariate) Sensitivity Analysis.
Summary of the Decision Tree Analysis Method.
Chapter Appendix. A Brief Introduction to Monte Carlo Simulation.
10 Sequential Games.
Asymmetry of Information.
Signal Jamming and Screening.
Appendix: Mathematics Revision.