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Chapter 17

Chapter 17. Decision Making 17.1 Payoff Table and Decision Tree 17.2 Criteria for Decision Making. Introduction. Single criteria decisions (e.g. I want the fastest car) are easier to make than multiple criteria decisions (e.g. I want the best car).

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Chapter 17

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  1. Chapter 17 Decision Making 17.1 Payoff Table and Decision Tree 17.2 Criteria for Decision Making

  2. Introduction • Single criteria decisions (e.g. I want the fastest car) are easier to make than multiple criteria decisions (e.g. I want the best car). • Decision making: should I take a particular course of action?

  3. Four basic features: • Alternative Courses of Action. • Without options there is not much to do. • Events or States of the World. • What can happen and what is the likelihood. • Payoffs. • Value of each event must be known. • Decision Criteria.

  4. 17.1: Payoff Tables and Decision Trees • Payoff Table (PT) contains the events that could happen for each course of action. • PT also contains the payoff. • PT might contain the probabilities of events.

  5. Decision Tree • Decision Tree (DT) shows the events and courses of action. • DT also shows the payoffs. • DT also shows the probabilities of events. • The DT is constructed of branches and nodes. There can be any number of branches.

  6. Criteria and Probabilities • Even without the probabilities and payoffs, DTs are useful for communicating or inspiring thought. • With the payoffs, probabilities and a decision making criterion, you can evaluate the courses of action. • Payoffs: both Profit and Opportunity Loss (OL) can be found. • OL is the profit lost by failing to choose the best course of action. • OL = best profit for current event – profit being considered (current action and event). OL ≥ 0.

  7. 17.2: Criteria for Decision Making • Probabilities of events will be needed to calculate expected outcomes. • Where do the probabilities come from? • Four criteria: • Expected Monetary Value • Expected Opportunity Loss • Expected Value of Perfect Information • Return-to-risk Ratio

  8. Expected Monetary Value • The Expected Monetary Value or EMV is often used as a decision making criterion. • EMV = sum of the product of profit and probability for all combinations of events and actions. • Typically choose the largest EMV.

  9. Expected Opportunity Loss • Expected Opportunity Loss (EOL) is the sum of the product of the probability and opportunity loss for each event under each decision. • Formula 17.2.

  10. Expected Value of Perfect Information • If you find the expected opportunity loss (EOL) for the “best” decision, you will have the expected value of perfect information (EVPI). • EVPI = expected profit under certainty – EMV of the best alternative. • Expected profit under certainty = the sum of the product of probability and best profit for all outcomes or states.

  11. Return-to-Risk Ratio (RTRR) • EMV and EOL do not consider variability. • Use the definition of standard deviation for a random variable to approximate the risk (chapter 5!). • Calculate the Return-to-Risk ratio for each course of action = EMV divided by standard deviation. See formula 17.4. • Return-to-Risk is the reciprocal of the coefficient of variation.

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