1 1 Slide © 2001 South-Western College Publishing/Thomson Learning Anderson Sweeney Williams Anderson Sweeney Williams Slides Prepared by JOHN LOUCKS QUANTITATIVE METHODS FOR BUSINESS 8e QUANTITATIVE METHODS FOR BUSINESS 8e

2 2 Slide Chapter 5 Utility and Decision Making n The Meaning of Utility n Developing Utilities for Monetary Payoffs n Summary of Steps for Determining the Utility of Money n Risk Avoiders versus Risk Takers n Expected Monetary Value versus Utility as an Approach to Decision Making

3 3 Slide Meaning of Utility n n Utilities are used when the decision criteria must be based on more than just expected monetary values. n n Utility is a measure of the total worth of a particular outcome, reflecting the decision maker’s attitude towards a collection of factors. n n Some of these factors may be profit, loss, and risk. n n This analysis is particularly appropriate in cases where payoffs can assume extremely high or extremely low values.

4 4 Slide Expected Utility Approach n n Once a utility function has been determined, the optimal decision can be chosen using the expected utility approach. n n Here, for each decision alternative, the utility corresponding to each state of nature is multiplied by the probability for that state of nature. n n The sum of these products for each decision alternative represents the expected utility for that alternative. n n The decision alternative with the highest expected utility is chosen.

5 5 Slide Risk Avoiders vs. Risk Takers n n A risk avoider will have a concave utility function when utility is measured on the vertical axis and monetary value is measured on the horizontal axis. Individuals purchasing insurance exhibit risk avoidance behavior. n n A risk taker, such as a gambler, pays a premium to obtain risk. His/her utility function is convex. This reflects the decision maker’s increasing marginal value of money. n n A risk neutral decision maker has a linear utility function. In this case, the expected value approach can be used.

6 6 Slide Risk Avoiders vs. Risk Takers n n Most individuals are risk avoiders for some amounts of money, risk neutral for other amounts of money, and risk takers for still other amounts of money. n n This explains why the same individual will purchase both insurance and also a lottery ticket.

7 7 Slide Example 1 Consider the following three-state, four-decision problem with the following payoff table in dollars: s 1 s 2 s 3 s 1 s 2 s 3 d ,000+40,000-60,000 d 2 +50,000+20,000-30,000 d 3 +20,000+20,000-10,000 d 4 +40,000+20,000-60,000 The probabilities for the three states of nature are: P( s 1 ) =.1, P( s 2 ) =.3, and P( s 3 ) =.6.

8 8 Slide Example 1 n n Risk-Neutral Decision Maker If the decision maker is risk neutral the expected value approach is applicable. EV( d 1 ) =.1(100,000) +.3(40,000) +.6(-60,000) = -$14,000 EV( d 2 ) =.1( 50,000) +.3(20,000) +.6(-30,000) = -$ 7,000 EV( d 3 ) =.1( 20,000) +.3(20,000) +.6(-10,000) = +$ 2,000 Note the EV for d 4 need not be calculated as decision d 4 is dominated by decision d 2. The optimal decision is d 3.

9 9 Slide Example 1 n n Decision Makers with Different Utilities Suppose two decision makers have the following utility values: Utility Amount Decision Maker IDecision Maker II $100, $50, $40, $20, $10, $30, $60,

10 Slide Example 1 n n Graph of the Two Decision Makers’ Utility Curves Decision Maker I Decision Maker II Monetary Value (in $1000’s) Utility

11 Slide Example 1 n n Decision Maker I Decision Maker I has a concave utility function.Decision Maker I has a concave utility function. He/she is a risk avoider. He/she is a risk avoider. n n Decision Maker II Decision Maker II has convex utility function.Decision Maker II has convex utility function. He/she is a risk taker.He/she is a risk taker.

12 Slide Example 1 n n Expected Utility: Decision Maker I Expected s 1 s 2 s 3 Utility d d d Probability n n Optimal Decision: Decision Maker I The largest expected utility is Note again that d 4 is dominated by d 2 and hence is not considered. Decision Maker I should make decision d 3.

13 Slide Example 1 n n Expected Utility: Decision Maker II Expected s 1 s 2 s 3 Utility d d d Probability n n Optimal Decision: Decision Maker II The largest expected utility is Note again that d 4 is dominated by d 2 and hence is not considered. Decision Maker II should make decision d 1.

14 Slide Example 2 Suppose the probabilities for the three states of nature in Example 1 were changed to: P( s 1 ) =.5, P( s 2 ) =.3, and P( s 3 ) =.2. What is the optimal decision for a risk-neutral decision maker?What is the optimal decision for a risk-neutral decision maker? What is the optimal decision for Decision Maker I?What is the optimal decision for Decision Maker I?... for Decision Maker II?... for Decision Maker II? What is the value of this decision problem to Decision Maker I?... to Decision Maker II?What is the value of this decision problem to Decision Maker I?... to Decision Maker II? What conclusion can you draw?What conclusion can you draw?

15 Slide Example 2 n n Risk-Neutral Decision Maker EV( d 1 ) =.5(100,000) +.3(40,000) +.2(-60,000) = 50,000 EV( d 2 ) =.5( 50,000) +.3(20,000) +.2(-30,000) = 25,000 EV( d 3 ) =.5( 20,000) +.3(20,000) +.2(-10,000) = 14,000 The risk-neutral optimal decision is d 1.

16 Slide Example 2 n n Expected Utility: Decision Maker I EU( d 1 ) =.5(100) +.3(90) +.2( 0) = 77.0 EU( d 2 ) =.5( 94) +.3(80) +.2(40) = 79.0 EU( d 3 ) =.5( 80) +.3(80) +.2(60) = 76.0 Decision Maker I’s optimal decision is d 2.

17 Slide Example 2 n n Expected Utility: Decision Maker II EU( d 1 ) =.5(100) +.3(50) +.2( 0) = 65.0 EU( d 2 ) =.5( 58) +.3(35) +.2(10) = 41.5 EU( d 3 ) =.5( 35) +.3(35) +.2(18) = 31.6 Decision Maker II’s optimal decision is d 1.

18 Slide Example 2 n Value of the Decision Problem: Decision Maker I Decision Maker I’s optimal expected utility is 79.Decision Maker I’s optimal expected utility is 79. He assigned a utility of 80 to +$20,000, and a utility of 60 to -$10,000.He assigned a utility of 80 to +$20,000, and a utility of 60 to -$10,000. Linearly interpolating in this range 1 point is worth $30,000/20 = $1,500.Linearly interpolating in this range 1 point is worth $30,000/20 = $1,500. Thus a utility of 79 is worth about $20, ,500 = $18,500.Thus a utility of 79 is worth about $20, ,500 = $18,500.

19 Slide Example 2 n Value of the Decision Problem: Decision Maker II Decision Maker II’s optimal expected utility is 65.Decision Maker II’s optimal expected utility is 65. He assigned a utility of 100 to $100,000, and a utility of 58 to $50,000.He assigned a utility of 100 to $100,000, and a utility of 58 to $50,000. In this range, 1 point is worth $50,000/42 = $1190.In this range, 1 point is worth $50,000/42 = $1190. Thus a utility of 65 is worth about $50, (1190) = $58,330.Thus a utility of 65 is worth about $50, (1190) = $58,330. The decision problem is worth more to Decision The decision problem is worth more to Decision Maker II (since $58,330 > $18,500). Maker II (since $58,330 > $18,500).

20 Slide The End of Chapter 5