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CD-ROM Chapter 17 Introduction to Decision Analysis.

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Presentation on theme: "CD-ROM Chapter 17 Introduction to Decision Analysis."— Presentation transcript:

1 CD-ROM Chapter 17 Introduction to Decision Analysis

2 Chapter 17 - Chapter Outcomes After studying the material in this chapter, you should be able to:  Describe the decision-making environments of certainty and uncertainty.  Construct both a payoff table and an opportunity loss table.  Define the expected value criterion.  Apply the expected value criterion in decision situations.  Compute the value of perfect information.

3 Chapter 17 - Chapter Outcomes (continued) After studying the material in this chapter, you should be able to:  Develop a decision tree and explain how it can aid decision making in an uncertain environment.  Discuss the difference between risk seeking and risk avoiding behavior.  Construct an individual risk preference function.

4 Decision-Making Environments Certainty Certainty refers to a decision environment in which the results of selecting each alternative are known before the decision is made.

5 Decision-Making Environments Uncertainty Uncertainty refers to a decision environment in which the decision maker does not know what outcome will occur when an alternative is selected.

6 Decision-Making Environments The goal of decision analysis is to focus on making good decisions, which in the long run should result in an increased number of good outcomes.

7 Decision Criteria states of nature The states of nature are the possible outcomes in a decision situation over which the decision maker has no control.

8 Decision Criteria payoff payoff table A payoff is the outcome (profit or loss) for any combination of alternative states of nature. The outcomes of all possible combinations of alternatives and states of nature constitute a payoff table.

9 Decision Criteria (Table 17-2) Fisher Fabrication Payoff Table DEMAND (STATES OF NATURE) AlternativeS 11 Large IncreaseS 22 Moderate IncreaseS 33 Small Increase A 11 Large Investment $6,000,000$4,000,000$-2,600,000 A 22 Medium Investment 2,500,0005,000,000-1,000,000 A 33 Small Investment 2,000,0001,500,0001,200,000

10 Decision Criteria maximax criterion The maximax criterion is an optimistic decision criterion for dealing with uncertainty without using probability. For each option, the decision maker finds the maximum possible payoff and then selects the option with the greatest maximum payoff.

11 Decision Criteria maximin criterion The maximin criterion is a pessimistic (conservative) decision criterion for dealing with uncertainty without using probability. For each option, the decision maker finds the minimum possible payoff and then selects the option with the greatest minimum payoff.

12 Decision Criteria opportunity loss The opportunity loss is the difference between the actual payoff that occurs for a decision and the optimal payoff for the same decision.

13 Decision Criteria minimax regret criterion The minimax regret criterion is a decision criterion that considers the costs of selecting the “wrong” alternative. For each sate of nature, the decision maker finds the difference between the best payoff and each other alternative and uses these values to construct an opportunity-loss table. The decision maker then selects the alternative with the minimum opportunity loss (or regret).

14 Decision Criteria (Table 17-3) Fisher Fabrication Opportunity-Loss Table

15 Decision Criteria (Table 17-4) Fisher Fabrication Maximum Regret Table

16 Decision Criteria expected-value criterion The expected-value criterion is a decision criterion that employs probability to select the alternative that will produce the greatest average payoff or minimum average loss.

17 Decision Criteria EXPECTED VALUE where: x i = The i th outcome of the specified alternative measured in some units, such as dollars P( x i ) = The probability of outcome x i occurring k = number of potential outcomes and:

18 Decision Criteria CLASSICAL PROBABILITY ASSESSMENT

19 Decision Criteria RELATIVE FREQUENCY OF OCCURRENCE PROBABILITY where:

20 Decision Criteria (Table 17-5)

21 Decision Criteria (Table 17-6)

22 Decision-Tree Analysis decision tree A decision tree is a diagram that illustrates the correct ordering of actions and events in a decision-analysis problem. Each act or event is represented by a node on the decision tree.

23 Decision-Tree Analysis (Figure 17-1) Don’t sign Sign Contract Decision

24 Decision-Tree Analysis (Figure 17-2) Don’t sign Sign Contract Unfavorable Review Favorable Review Decision Event

25 Decision-Tree Analysis (Figure 17-3) Don’t sign Sign Contract Unfavorable Review Favorable Review Hardcover Paperback Decision Event Decision

26 Decision-Tree Analysis (Figure 17-4) Don’t sign Sign Contract Unfavorable Review Favorable Review Hardcover Paperback 100,000 copies 1,000,000 copies 50,000 copies 1,500,000 copies Decision Event Decision Event

27 Risk Preference Attitudes risk-neutral attitude A risk-neutral attitude refers to the preference for risk under which the alternative with the highest expected payoff or lowest expected cost will be selected.

28 Risk Preference Attitudes (Figure 17-11) Buy Don’t Buy Merger No Merger $0 $10 Xircom Stock Purchase Example (0.5) -$5

29 Risk Preference Attitudes (Figure 17-12) Buy Don’t Buy Merger No Merger $0 $100 Xircom Stock Purchase Example (0.5) -$50

30 Risk Preference Attitudes (Figure 17-13) Buy Don’t Buy Merger No Merger $0 $10,000 Xircom Stock Purchase Example (0.5) -$5,000

31 Risk Preference Attitudes risk-averse attitude A risk-averse attitude refers to the preference for risk such that the decision maker could select an alternative with a lower expected payoff in order to avoid the possibility of an undesirable outcome.

32 Risk Preference Attitudes Certainty equivalent Certainty equivalent is the value that would make a decision maker indifferent between taking an uncertain gamble versus receiving that value instead of taking the gamble.

33 Risk Preference Attitudes risk-seeking attitude A risk-seeking attitude refers to the preference for risk such that the decision maker could select an alternative with a lower expected payoff in hopes of achieving an outcome with a more desirable result.

34 Risk Preference Attitudes risk preference function The risk preference function is the graph that describes a decision maker’s preference for risk over the range of possible payoffs.

35 Risk Preference Attitudes standard gamble approach A standard gamble approach is the approach for assessing risk-preference functions that involves setting up a series of 50-50 gambles between two payoffs and determining the certainty equivalent for each gamble.

36 Risk Preference Attitudes preference quotient A preference quotient refers to the measure of the relative utility for the outcomes of a decision on a scale between 0.0 and 1.0.

37 Risk Preference Attitudes (Figure 17-16) Play Don’t Play End Values CE = ? $10,000 Assessing the Risk-Preference Function: Standard Gamble 1 0.5 -$2,000 q Values 1.0 0.0

38 Risk Preference Attitudes (Figure 17-17) Play Don’t Play End Values CE = ? $10,000 Assessing the Risk-Preference Function: Standard Gamble 2 0.5 $4,000 q Values 1.0 0.5

39 Risk Preference Attitudes (Figure 17-18) Play Don’t Play End Values CE = ? $4,000 Assessing the Risk-Preference Function: Standard Gamble 3 0.5 -$2,000 q Values 0.5 0.0

40 Risk Preference Attitudes Risk premium Risk premium is the difference between the expected value of an event and the certainty equivalent. The risk premium will be zero for a risk-neutral decision maker, positive for a risk-averse decision maker, and negative for a risk-seeking decision maker.

41 Risk Preference Attitudes (Figure 17-19) $0$2,000$4,000$6,000$8,000$10,000 0 0.25 0.50 0.75 1 -$2,000 Risk-Neutral Preference Function

42 Risk Preference Attitudes (Figure 17-23) $0$2,000$4,000$6,000$8,000$10,000 0 0.25 0.50 0.75 1 -$2,000 Risk-Averse Preference Function

43 Risk Preference Attitudes (Figure 17-26) $0$2,000$4,000$6,000$8,000$10,000 0 0.25 0.50 0.75 1 -$2,000 Risk-Seeking Preference Function

44 Key Terms Certainty Certainty Equivalent Decision Tree Expected Value Expected-Value Criterion Maximax Criterion Maximin Criterion Minimax Regret Criterion Opportunity Loss Payoff Preference Quotient Risk-Averse Attitude Risk-Neutral Attitude Risk-Preference Function Risk Premium Risk-Seeking Attitude

45 Key Terms (continued) Standard Gamble Approach State of Nature Uncertainty


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