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planninganddecisionmakingch5class6.pptxJudgment in Managerial Decision Making 8e Chapter 5 Framing and the Reversal of Preferences
Copyright 2013 John Wiley & Sons
As noted previously, we tend to use heuristics, or rules of thumb, to reduce the complexity of our decisions.
Often, these heuristics allow us to make effective decisions in a short amount of time.
However, under the right set of circumstances they can also lead us into making biased decisions.
Avoiding the biases that come with the use of heuristics is so difficult that even the most intelligent people are prone to error.
Before introducing key biases, take a few minutes to answer the following questions. Write down your answers.
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Framing
We tend to use heuristics (rules of thumb) to reduce the complexity of our decisions.
They often lead us to effective decisions in a short amount of time.
However, under the right set of circumstances they can also lead us into making biased decisions.
Avoiding the biases that come with the use of heuristics is so difficult that even the most intelligent people are prone to error.
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The Asian Disease Problem
Imagine that the United States is preparing for the outbreak of an unusual Asian disease that is expected to kill 600 people. Two alternative programs to combat the disease have been proposed. Assume that the exact scientific estimates of the consequences of the programs are as follows.
Program A: If Program A is adopted, 200 people will be saved.
Program B: If Program B is adopted, there is a one-third probability that 600 people will be saved and a two-thirds probability that no people will be saved.
Which of the two programs would you favor?
Consider this problem.
You have a choice between two programs.
Each program is expected to save 200 people.
However, Program A is certain to save 200 people while Program B has a high degree of uncertainty, as either 200 or 0 people will be saved.
Because people are risk averse, they tend to favor Program A.
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Big Positive Gamble
You can (a) receive $10 million for sure (expected value = $10 million) or (b) flip a coin and receive $22 million for heads but nothing for tails (expected value = $11 million). An expected-value decision rule would require you to pick (b).
What would you do?
Now, consider this problem about a gamble and write down what you would do.
Essentially, you can choose between a higher expected value that is uncertain or a sure gain that is slightly lower.
Most people take the certain gain here due to risk aversion.
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Big Positive Gamble
Most people take the certain gain here due to risk aversion.
Now, consider this problem about a gamble and write down what you would do.
Essentially, you can choose between a higher expected value that is uncertain or a sure gain that is slightly lower.
Most people take the certain gain here due to risk aversion.
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Lawsuit
You are being sued for $500,000 and estimate that you have a 50 percent chance of losing the case in court (expected value = –$250,000). However, the other side is willing to accept an out-of-court settlement of $240,000 (expected value = –$240,000). An expected-value decision rule would lead you to settle out of court.
Ignoring attorney’s fees, court costs, aggravation, and so on, would you (a) fight the case, or (b) settle out of court?
Now, consider this problem.
In this case, we are considering the domain of losses rather than gains.
You can choose between a sure loss of $240,000 or a 50/50 shot at losing either $500,000 or nothing.
In this case, most people are risk-seeking and choose to fight the lawsuit in court.
When comparing to the previous problem, where you had a choice between a certain gain and a slightly larger gain that is uncertain, people tend to be risk averse while here, they tend to be risk-seeking. Interestingly, this preferences differ despite the fact that the two problems are conceptually similar.
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Lawsuit
In this case, most people are risk-seeking and choose to fight the lawsuit in court.
When comparing to the previous problem, (big positive gamble), people tend to be risk averse while here, they tend to be risk-seeking.
Interestingly, this preferences differ despite the fact that the two problems are conceptually similar.
Now, consider this problem.
In this case, we are considering the domain of losses rather than gains.
You can choose between a sure loss of $240,000 or a 50/50 shot at losing either $500,000 or nothing.
In this case, most people are risk-seeking and choose to fight the lawsuit in court.
When comparing to the previous problem, where you had a choice between a certain gain and a slightly larger gain that is uncertain, people tend to be risk averse while here, they tend to be risk-seeking. Interestingly, this preferences differ despite the fact that the two problems are conceptually similar.
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Asian Disease Problem
Imagine that the United States is preparing for the outbreak of an unusual Asian disease that is expected to kill 600 people. Two alternative programs to combat the disease have been proposed. Assume that the scientific estimates of the consequences of the programs are as follows.
Program C: If Program C is adopted, 400 people will die.
Program D: If Program D is adopted, there is a one-third probability that no one will die and a two-thirds probability that 600 people will die.
Which of the two programs would you favor?
Now, let’s return to a problem that slightly varies from the Asian Disease problem that we went over earlier.
Notice that this problem is quite similar to the one we originally encountered, except for that rather than referring to 200 people being saved in Program C or the 0 people that will be saved in Program D, it is pointing out the 400 people that will die in Program C and that 600 people will die in Program D.
From an objective numerical standpoint, these two options are identical to Programs A and B in the original version of the problem.
However, one version of the problem emphasizes lives saved while the other emphasizes deaths.
Interestingly, despite the problems being identical from the standpoint of computing the expected number of deaths, people tend to be risk-seeking in this version of the problem and select Program D even though in the prior version of the problem, people tend to be risk-averse and select Program A.
This illustrates the power of framing, a subtle change in the implicit reference point that is invoked when solving problems. Very subtle changes in the wording of a problem via framing can have a dramatic impact on preferences.
We tend to be risk-averse in the domain of gains and risk-seeking in the domain of losses.
Thus, if framing draws attention to deaths from a reference state of the world with all 600 people being alive, people will undertake significant risk to save all 600 people.
However, if it draws attention to lives saved from a reference state of the world with all 600 people dying, people will be reluctant to risk not saving anybody.
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Asian Disease Problem
Notice that this problem is quite similar to the one we originally encountered, except for that rather than referring to people being saved, its referring deaths.
From an objective numerical standpoint, these two options are identical to Programs A and B in the original version of the problem.
Interestingly, despite the problems being identical from the standpoint of computing the expected number of deaths, people tend to be risk-seeking in this version of the problem and select Program D even though in the prior version of the problem, people tend to be risk-averse and select Program A.
This illustrates the power of framing:
a subtle change in the implicit reference point that is invoked when solving problems.
Very subtle changes in the wording of a problem via framing can have a dramatic impact on preferences.
Now, let’s return to a problem that slightly varies from the Asian Disease problem that we went over earlier.
Notice that this problem is quite similar to the one we originally encountered, except for that rather than referring to 200 people being saved in Program C or the 0 people that will be saved in Program D, it is pointing out the 400 people that will die in Program C and that 600 people will die in Program D.
From an objective numerical standpoint, these two options are identical to Programs A and B in the original version of the problem.
However, one version of the problem emphasizes lives saved while the other emphasizes deaths.
Interestingly, despite the problems being identical from the standpoint of computing the expected number of deaths, people tend to be risk-seeking in this version of the problem and select Program D even though in the prior version of the problem, people tend to be risk-averse and select Program A.
This illustrates the power of framing, a subtle change in the implicit reference point that is invoked when solving problems. Very subtle changes in the wording of a problem via framing can have a dramatic impact on preferences.
We tend to be risk-averse in the domain of gains and risk-seeking in the domain of losses.
Thus, if framing draws attention to deaths from a reference state of the world with all 600 people being alive, people will undertake significant risk to save all 600 people.
However, if it draws attention to lives saved from a reference state of the world with all 600 people dying, people will be reluctant to risk not saving anybody.
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Asian Disease Problem
We tend to be risk-averse in the domain of gains and risk-seeking in the domain of losses.
Thus, if framing draws attention to deaths from a reference state of the world with all 600 people being alive, people will undertake significant risk to save all 600 people.
However, if it draws attention to lives saved from a reference state of the world with all 600 people dying, people will be reluctant to risk not saving anybody.
Now, let’s return to a problem that slightly varies from the Asian Disease problem that we went over earlier.
Notice that this problem is quite similar to the one we originally encountered, except for that rather than referring to 200 people being saved in Program C or the 0 people that will be saved in Program D, it is pointing out the 400 people that will die in Program C and that 600 people will die in Program D.
From an objective numerical standpoint, these two options are identical to Programs A and B in the original version of the problem.
However, one version of the problem emphasizes lives saved while the other emphasizes deaths.
Interestingly, despite the problems being identical from the standpoint of computing the expected number of deaths, people tend to be risk-seeking in this version of the problem and select Program D even though in the prior version of the problem, people tend to be risk-averse and select Program A.
This illustrates the power of framing, a subtle change in the implicit reference point that is invoked when solving problems. Very subtle changes in the wording of a problem via framing can have a dramatic impact on preferences.
We tend to be risk-averse in the domain of gains and risk-seeking in the domain of losses.
Thus, if framing draws attention to deaths from a reference state of the world with all 600 people being alive, people will undertake significant risk to save all 600 people.
However, if it draws attention to lives saved from a reference state of the world with all 600 people dying, people will be reluctant to risk not saving anybody.
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Asian Disease Problem
Another explanation for why people deviate from the expected value, is expected utility:
Suggest that each level of an outcome is associated with an expected degree of pleasure or benefit (called utility)
The pleasure (utility) of the second $500 K is not the same as the first $500 K; although, expected value suggests that the second $500 K is twice as much.
The second piece of pizza is tasty, but not as tasty as the first
In other words, “declining marginal utility of gains”
The more we get of something, the less pleasure it provides
Now, let’s return to a problem that slightly varies from the Asian Disease problem that we went over earlier.
Notice that this problem is quite similar to the one we originally encountered, except for that rather than referring to 200 people being saved in Program C or the 0 people that will be saved in Program D, it is pointing out the 400 people that will die in Program C and that 600 people will die in Program D.
From an objective numerical standpoint, these two options are identical to Programs A and B in the original version of the problem.
However, one version of the problem emphasizes lives saved while the other emphasizes deaths.
Interestingly, despite the problems being identical from the standpoint of computing the expected number of deaths, people tend to be risk-seeking in this version of the problem and select Program D even though in the prior version of the problem, people tend to be risk-averse and select Program A.
This illustrates the power of framing, a subtle change in the implicit reference point that is invoked when solving problems. Very subtle changes in the wording of a problem via framing can have a dramatic impact on preferences.
We tend to be risk-averse in the domain of gains and risk-seeking in the domain of losses.
Thus, if framing draws attention to deaths from a reference state of the world with all 600 people being alive, people will undertake significant risk to save all 600 people.
However, if it draws attention to lives saved from a reference state of the world with all 600 people dying, people will be reluctant to risk not saving anybody.
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Sell or Hold?
You were given 100 shares of stock in XYZ Corporation two years ago, when the value of the stock was $20 per share. Unfortunately, the stock has dropped to $10 per share during the two years that you have held the asset. The corporation is currently drilling for oil in an area that may turn out to be a big “hit.” On the other hand, they may find nothing. Geological analysis suggests that if they hit, the stock is expected to go back up to $20 per share. If the well is dry, however, the value of the stock will fall to $0 per share.
Do you want to sell your stock now for $10 per share?
Now consider this problem on whether you would like to sell or hold a stock.
Here, framing is more ambiguous.
Some people may frame this in terms of the amount that they receive for the stock above a reference point of $0 per share.
Others may frame this in terms of the amount that the stock has fallen from a reference purchase price of $20 per share.
Those who frame this in terms of gains above $0 will likely be risk averse and sell the stock while those who frame this problem in terms of losses from $20 will likely hold onto the stock out of hopes that they will break even on the stock.
This illustrates that even a single problem can be framed multiple ways and the frame one adopts can have a dramatic influence on his or her decision making despite being faced with an objectively identical problem.
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Sell or Hold?
Here, framing is more ambiguous.
Some people may frame this in terms of the amount that they receive for the stock above a reference point of $0 per share.
Others may frame this in terms of the amount that the stock has fallen from a reference purchase price of $20 per share.
Those who frame this in terms of gains above $0 will likely be
risk averse and sell the stock
Those who frame this problem in terms of losses from $20 will likely be
Risk seeking and hold onto the stock out of hopes that they will break even on the stock.
Now consider this problem on whether you would like to sell or hold a stock.
Here, framing is more ambiguous.
Some people may frame this in terms of the amount that they receive for the stock above a reference point of $0 per share.
Others may frame this in terms of the amount that the stock has fallen from a reference purchase price of $20 per share.
Those who frame this in terms of gains above $0 will likely be risk averse and sell the stock while those who frame this problem in terms of losses from $20 will likely hold onto the stock out of hopes that they will break even on the stock.
This illustrates that even a single problem can be framed multiple ways and the frame one adopts can have a dramatic influence on his or her decision making despite being faced with an objectively identical problem.
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Preference Reversals
Sub-optimal decision portfolios
“Pseudocertainty” and our judgments
Insurance
Evaluations of transactions
Ownership and framing
Mental accounting
Bonuses versus rebates
Separate versus joint evaluation
As illustrated by these problems, the way options are framed can play an important role in impacting our decisions.
As one could imagine, framing impacts our decisions in a variety of domains. We will review the following domains in which framing impacts our decision-making
Framing can have particularly strong effects when we consider the sum of our decisions as a portfolio.
Imperfect perceptions of probability can influence our choices.
Our decisions to purchase insurance are impacted by framing.
We evaluate the quality of transactions according to how we frame the them.
When we own an object, we frame it differently than when we do not.
We tend to organize our finances by tracking our spending on different categories of purchases. The manner in which we frame purchases and categorize them can influence the manner in which we frame them.
Our spending behavior is influenced by whether excess money is framed as a rebate or a bonus.
Sometimes we consider options separately while in others, we make choices while having access to all possible alternative options. This has an impact on our decisions.
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Framing and the Irrationality of the Sum of Our Choices
Imagine that you face the following pair of concurrent decisions. First, examine both decisions, and then indicate the options you prefer.
Decision A
Choose between:
a. a sure gain of $240
b. a 25 percent chance to gain $1,000 and a 75 percent chance to gain nothing
Decision B
Choose between:
c. a sure loss of $750
d. a 75 percent chance to lose $1,000 and a 25 percent chance to lose nothing
- Consider the following two decisions and then indicate your preferred choices in each option.
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What Do People Choose?
Decision A
Decision B
In combination, 73% of people choose options A and D.
As we would expect, on Decision A, which is framed in terms of potential gains, people tend to be risk averse and choose the option with a sure gain of $240.
We also see that on Decision B, which is framed in terms of potential losses, people tend to be risk-seeking and choose the option with an uncertain loss over the one with a certain loss of $750.
In combination, 73% of people choose options A and D.
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Percent Choosing Option
Series 1 Option C (sure loss) Option D (uncertain loss) 13 87
Framing and the Irrationality of the Sum of Our Choices
Choose between:
e. a 25 percent chance to win $240 and a 75 percent chance to lose $760
f. a 25 percent chance to win $250 and a 75 percent chance to lose $750
Now, think about this problem for a moment.
Not surprisingly, most people prefer option F to option E, as option E provides a better expected value with more potential for gains and less potential for losses.
If you looked at the problem carefully, you may have noticed that Option E combines the sure gain of $240 from Option A in Decision A of the previous problem with the uncertain loss of $760 from Option D in Decision B of the previous problem.
This was the preferred pattern of choices that people made when considering the decisions separately.
However, when combining choices across gains and losses, Choice F, which combines individuals’ less preferred options in the prior problem, is clearly superior.
By merely considering choices framed as gains and losses separately, people have made suboptimal decisions.
However, by jointly considering choices framed as gains and losses, people can improve the quality of their decisions.
How might all of this be relevant for our managerial decisions?
When budgeting and funding projects, managers often make allocation decisions separately.
Different departments of organizations frame projects differently:
Salespeople think in terms of acquiring corporate gains.
Credit offices think of decisions in terms of avoiding losses.
Overall, many of the decisions that occur in organizations are made sequentially or with separate frames as opposed to simultaneously and with consistent frames. This can lead to sub-optimal decisions at an organizational level.
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Framing and the Irrationality of the Sum of Our Choices
Not surprisingly, most people prefer option F to option E, as option E provides a better expected value with more potential for gains and less potential for losses.
If you looked at the problem carefully, you may have noticed that Option E combines Option A and Option D of the previous problem.
This was the preferred pattern of choices that people made when considering the decisions separately.
However, when combining choices across gains and losses, Choice F, which combines individuals’ less preferred options in the prior problem, is clearly superior.
By merely considering choices framed as gains and losses separately, people have made suboptimal decisions.
However, by jointly considering choices framed as gains and losses, people can improve the quality of their decisions.
Now, think about this problem for a moment.
Not surprisingly, most people prefer option F to option E, as option E provides a better expected value with more potential for gains and less potential for losses.
If you looked at the problem carefully, you may have noticed that Option E combines the sure gain of $240 from Option A in Decision A of the previous problem with the uncertain loss of $760 from Option D in Decision B of the previous problem.
This was the preferred pattern of choices that people made when considering the decisions separately.
However, when combining choices across gains and losses, Choice F, which combines individuals’ less preferred options in the prior problem, is clearly superior.
By merely considering choices framed as gains and losses separately, people have made suboptimal decisions.
However, by jointly considering choices framed as gains and losses, people can improve the quality of their decisions.
How might all of this be relevant for our managerial decisions?
When budgeting and funding projects, managers often make allocation decisions separately.
Different departments of organizations frame projects differently:
Salespeople think in terms of acquiring corporate gains.
Credit offices think of decisions in terms of avoiding losses.
Overall, many of the decisions that occur in organizations are made sequentially or with separate frames as opposed to simultaneously and with consistent frames. This can lead to sub-optimal decisions at an organizational level.
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Framing and the Irrationality of the Sum of Our Choices
How might all of this be relevant for our managerial decisions?
When budgeting and funding projects, managers often make allocation decisions separately.
Different departments of organizations frame projects differently:
Salespeople think in terms of acquiring corporate gains.
Credit offices think of decisions in terms of avoiding losses.
Overall, many of the decisions that occur in organizations are made sequentially or with separate frames as opposed to simultaneously and with consistent frames. This can lead to sub-optimal decisions at an organizational level.
Now, think about this problem for a moment.
Not surprisingly, most people prefer option F to option E, as option E provides a better expected value with more potential for gains and less potential for losses.
If you looked at the problem carefully, you may have noticed that Option E combines the sure gain of $240 from Option A in Decision A of the previous problem with the uncertain loss of $760 from Option D in Decision B of the previous problem.
This was the preferred pattern of choices that people made when considering the decisions separately.
However, when combining choices across gains and losses, Choice F, which combines individuals’ less preferred options in the prior problem, is clearly superior.
By merely considering choices framed as gains and losses separately, people have made suboptimal decisions.
However, by jointly considering choices framed as gains and losses, people can improve the quality of their decisions.
How might all of this be relevant for our managerial decisions?
When budgeting and funding projects, managers often make allocation decisions separately.
Different departments of organizations frame projects differently:
Salespeople think in terms of acquiring corporate gains.
Credit offices think of decisions in terms of avoiding losses.
Overall, many of the decisions that occur in organizations are made sequentially or with separate frames as opposed to simultaneously and with consistent frames. This can lead to sub-optimal decisions at an organizational level.
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