Values, Choices and Frames

Session 10Decision Making and Risk Sp2006

Role of Memory and Processing Biases in Decision Making

In-Class Exercise – Generating Probability Estimates

Generate examples of probability estimation situations in which the estimates could be biased (previous lecture), and come up with ways to correct such estimates.

Output: A table with three columns, first column, the name of

the bias, second column, a business situation which exemplifies the bias (this has to be somewhat descriptive), third column that makes specific recommendations about how the bias can be avoided.

New Product Development Situation The product development team for NexTech Inc., a toy

manufacturer and marketer is in a new products ideation meeting featuring several participants.

The goal is the following: Identify as many new product ideas that will go into the

‘decision option’ pool. They have to come up with decision criteria, and

importance assessed to each criterion thereof, that will help them evaluate the decision options they generate.

How should they go about the task? Specifically, what would limit/expand the number of new

ideas generated? What would affect their ability to go closer to/away from

the true decision criteria?

Part-List Cueing Effect Time 1:

Learn a list of items in a category

Time 2: Unrelated activity

Time 3: Split into two groups.

One group studies a random selection of half the items of again (Re-Study Group)

The other group does not (No Study Group). Time 4:

Unrelated activity

Time 5: Both groups asked to recall as many items from the original list.

Results:

For items studied at time 3 Re-Study Group > No Study Group

For items not studied at time 3Re-Study Group < No Study Group

Part-List Cueing

If there are “n” options in an option space, S.

Let rn be the number of options recalled from memory; rn ≤ n.

If a few options, say, c, are provided as a memory cue, then, rc, the number of items recalled from S when ‘c’ items are provided, will be such that: rc << rn - c.

How Structure Affects Importance of Decision Criteria

ProblemsPercentage Choosing Each AnswerOpen Question Closed Question

Quality of Public Schools

Legalized Abortion

Energy Shortage All Other

Responses

1100

98

321486

40Source: Schumann and Scott (1987)

What is Important and What is not? Highly affected by availability.

Factors that are listed, get inflated importance scores. Importance of factors generated by pulling

from memory tends to correlate better with true importance.

Take away? For idea generation For importance assessment

Elementary Information Processing Model

InputCognitive and

Emotional Processes

Output

What you remember from a list? Time 1:

Learn a list of items in a category

Time 2: Unrelated activity

Time 3: Recall as many items from the

original list.

What factors will Affect What is Recalled? Vivid items Items that came early on in the list. Items that came toward the end of the

list. Self-relevant items. Mood-congruent recall.

Memory Biases in Information Processing

InputCognitive and

Emotional Processes

Output

VividnessSelf-relevancePrimacy-Recency

Mood Congruent Recall

Simulating Competitor Behavior Company A is trying to assess risk

factors for success of a product. It is also concerned about the moves of

Company B. How would their risk estimates vary? How would their ability to process risk

increasing/decreasing factors vary?

Some Issues when Thinking of Others’ Risk Self-Other discrepancy in risk estimates

Vague competitor, i.e., ‘the competition’ tend to be judged more unfavorably than one’s own firm behavior, success probability etc. Individuate ‘the competition’ to a ‘particular

competitor’ Same thing applies to ‘the customer’. It often arises from:

inability to visualize risk increasing factors being realized for one’s own firm, and risk decreasing factors being realized for competing firm.

Selective memory for risk decreasing factors for one’s firm and risk increasing factors for competitor.

Dizziness and Brain Tumor

Which cells of the table are needed in order to determine whether dizziness is associated with brain tumors in this sample of people? (Check all that apply.)

Upper Left Lower Left Upper Right Lower Right

According to the data in the table, is dizziness associated with brain tumors? Yes No Not sure

Brain Tumor

Present Absent

Present 160 40 Dizziness

Absent 40 10

What Information is Needed for Assessing Correlation?

50

55

60

65

70

75

80

85

90

95

D-Present, BT-Present

D-Absent BT-Present

D-Present BT-Absent

D-Absent, BT-Present

Percent indicating quadrant for which information is needed

Illusory Correlation?

0

10

20

30

40

50

60

Related Unrelated

Percent indicating absence/presence of a relationship between Brain Tumor and Dizziness

SuperTire Discounters

Tire A: 40,000 mile warranty, $60.

Tire B: 50,000 mile warranty, $75.

Without changing the warranty and price (or any other attribute) of Tires A and B, how can one affect market share of Brand A?

Decision before Decision One group gets to choose

between: Tire A’: 55,000 and $85 Tire B’: 75,000 and $91

Another group gets to choose between:

Tire A’’: 30,000 and $25 Tire B’’: 35,000 and $49

Now both groups choose between:

Tire A: 40,000 and $60 Tire B: 50,000 and $75

0

10

20

30

40

50

60

70

80

90

Big Bang Small Bang

Lo-LoHi-HiLo-LoHi-HiLo-LoHi-Hi

Background Tradeoff Contrast Effect Pre-decision choice:

Big versus small bang for the buck Very high increase in value for unit increase in money

compared to the

Target choice set: Tradeoff functions will be contrasted.

With big bang for buck as the background, the increase in quality for money in the target set looks anemic by contrast, so choice is for the low quality low price brand.

With small bang for buck in the background, the increase in quality for money in the target set looks very good by contrast, so choice is for the high quality high price brand.

Local Contrast Effect

Suppose people are trying to choose between: Tire A: 40,000 and $60 Tire B: 50,000 and $75

Introduce Tire A’ which is inferior to Tire A, say, 35,000 and $60.

Tire A’ is dominated by Tire A, but not by Tire B.

A significantly greater proportion choose Tire A when the choice is A, A’ and B, than when the choice is A and B.

Review – Session 10 (April 4) Structuring the Decision

Memory Biases Part List Cuing – How available stimuli limit what is retrieved from memory.

Unstructured – private Unstructured – public Structured – public/private

Inflation of Importance Context of discovery/confirmation

Primacy and Recency Vividness

Self-relevance Mood-congruent recall

Processing Biases Self-other discrepancy in risk estimates, ability to visualize risk increasing

and decreasing factors, ability to use them Illusory correlation.

Value and Choices Value Maximization

Independence of Irrelevant Alternatives Tradeoff Contrasts

Background Contrast Local Contrast