Book contents
- Making Decisions: Analytics, Cognition, and Application
- Making Decisions: Analytics, Cognition, and Application
- Copyright page
- Dedication
- Contents
- Figures
- Tables
- Preface
- Acknowledgments
- Copyright Acknowledgements
- Part I Analytics: Probability, Evaluation, Decision Trees, and Strategies for Decision Making
- 1 Introduction to Decision Theory and Decision Making
- 2 Thinking Like a Gambler: For All the Gambles of Life
- 3 Using Decision Trees to See through the Forest Ahead
- 4 Strategies for Decision Making in an Environment of Risk: How to Get the Most and Avoid the Worst, No Matter What
- Introduction to Part II: Cognitive Processes of Decision Making
- Part III Applications, Examples, and Selected Topics
- References
- Index
4 - Strategies for Decision Making in an Environment of Risk: How to Get the Most and Avoid the Worst, No Matter What
from Part I - Analytics: Probability, Evaluation, Decision Trees, and Strategies for Decision Making
Published online by Cambridge University Press: 23 October 2025
Book contents
- Making Decisions: Analytics, Cognition, and Application
- Making Decisions: Analytics, Cognition, and Application
- Copyright page
- Dedication
- Contents
- Figures
- Tables
- Preface
- Acknowledgments
- Copyright Acknowledgements
- Part I Analytics: Probability, Evaluation, Decision Trees, and Strategies for Decision Making
- 1 Introduction to Decision Theory and Decision Making
- 2 Thinking Like a Gambler: For All the Gambles of Life
- 3 Using Decision Trees to See through the Forest Ahead
- 4 Strategies for Decision Making in an Environment of Risk: How to Get the Most and Avoid the Worst, No Matter What
- Introduction to Part II: Cognitive Processes of Decision Making
- Part III Applications, Examples, and Selected Topics
- References
- Index
Summary
Decision makers are often faced with situations where they have several choices from which to select, and each will produce a different outcome based on an external event. There are several prescriptive strategies that can be implemented in such situations depending on the desired outcome.
The strategy of expected value will produce the highest long-term-average results when the situation is repeated many times. If the decision maker wishes only to have the opportunity for the highest payoff one time, no matter what the risk, the maximax strategy will make that possible. If the goal is to avoid the worst-case outcome, the maximin strategy will be best. With pairwise comparisons, inadmissible alternatives can be eliminated. By calculating the expected value of perfect information, the decision maker can determine the upward limit on what they should be willing to pay to know the future with certainty.
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- Making Decisions: Analytics, Cognition, and Application , pp. 45 - 60Publisher: Cambridge University PressPrint publication year: 2025
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