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.
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.