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avail3v3 Lehman Benson III, University of Arizona, 2006 1
In a previous class session, you
completed a questionnaire that included two questions.
Today, I will present the results and discuss some of the reasons that you may have answered the questions the way that you did.
The Availability Heuristic
avail3v3 Lehman Benson III, University of Arizona, 2006 2
Question One Which causes more deaths in the
United States?
(A) shark attacks (B) getting hit by falling
airplane parts
avail3v3 Lehman Benson III, University of Arizona, 2006 3
How Your Class Answered The percentage of students in this
class who selected: Shark attack: (write the percentage of
the students who selected sharks)% Getting hit by falling airplane parts:
(write in the percentage of students who selected falling airplane parts)%
avail3v3 Lehman Benson III, University of Arizona, 2006 4
Typical Results Typically, more people (when
asked this question) select option (a), shark attack, over option (b), getting hit by falling airplane parts.
Actual data, however, suggest that one is 30 times more likely to die from being hit by falling airplane parts.
avail3v3 Lehman Benson III, University of Arizona, 2006 5
What Influenced Your Choice?
What are some plausible reasons that most people think that shark attacks cause more deaths in the United States than getting hit by falling airplane parts?
avail3v3 Lehman Benson III, University of Arizona, 2006 6
Typical Answers “I can recall more shark deaths.” “I read in the newspaper about a
terrible shark attack.” “I cannot recall any instances of a
person getting hit by falling airplane parts.”
“I can easily imagine going swimming and getting attacked by a shark.”
avail3v3 Lehman Benson III, University of Arizona, 2006 7
Heuristics A rule of thumb is an easily learned
and easily applied procedure for estimating, recalling some value, or making some determination.
In decision making, it is generally accepted that heuristics are simple, efficient rules of thumb that help people make decisions or judgments, and help them solve problems.
avail3v3 Lehman Benson III, University of Arizona, 2006 8
Heuristics, Cont’d Heuristics are typically used when
decision makers face complex problems or incomplete information, or are short on time.
In certain situations, however, rules of thumb or heuristics can lead to systematic cognitive biases and less-than-optimal decisions.
avail3v3 Lehman Benson III, University of Arizona, 2006 9
Availability Heuristic This module discusses one
mechanism that can support but sometimes distort judgments, the availability heuristic.
According to Tversky and Kahneman (1973, p. 208):
A person is said to employ the availability heuristic whenever he estimates frequency or probability by the ease with which instances or associations could be brought to mind.
avail3v3 Lehman Benson III, University of Arizona, 2006 10
Availability Heuristic, Cont’d
Thus, when people make judgments about how likely an event is, readily available, vividly described, recent, or emotionally laden instances are often perceived as being especially likely to occur.
avail3v3 Lehman Benson III, University of Arizona, 2006 11
Availability Heuristic, Cont’d Question One was a demonstration
of the availability heuristic. In forming some judgments, we
tend to rely on information that is readily available in memory (e.g., recent, salient, vivid), but fail to discount the quality of that information.
avail3v3 Lehman Benson III, University of Arizona, 2006 12
Question Two Should we expect decision makers
to use the availability heuristic when making business-related judgments or decisions?
Let’s see. Here are the results of the second question your class answered.
avail3v3 Lehman Benson III, University of Arizona, 2006 13
Results: Availability In Memory
CompanyAmerisourceBergen
Oracle*Ingram Micro
Nike*Starbucks *
Southwest Airlines *SupervaluTechData
AMRHilton Hotels *
McKessoneBay*
Median Estimate1520102420158
1015171719
Actual54.6011.7928.8013.756.397.54
19.5320.5420.714.43
80.514.55
Question Two: Estimate the sales revenues (note: sales revenues, not profits) of the following Fortune 500 firms for 2005-2006.
Results: Availability In Memory, Again
Avg. Estimate Avg. Actual
High Name RecognitioneBay, Hilton Hotels, Nike,Oracle, Southwest Airlines,Starbucks
19.16 8.07
Low Name RecognitionAmerisourceBergen, AMRIngram Micro, McKesson,SUPERVALU, Tech Data
12.50 37.44
avail3v3 Lehman Benson III, University of Arizona, 2006 15
The Availability Heuristic in Action
The two questions that we discussed today demonstrated the availability heuristic in quite different contexts.
We also discussed specific types of factors that might have influenced availability and hence the answers students gave to the two questions (things like ease of recall, vividness, ease of imagining a scenario).
avail3v3 Lehman Benson III, University of Arizona, 2006 16
The Heuristic in Action, Cont’d Another business example: A venture capitalist may
evaluate the probability that a given business venture will succeed by the assessing the ease of imagining various clients who will want to purchase a product produced by the venture.
Frank Yates (Yates, 1990) describes the process in the following manner: Single Event A Scenario Construction (e.g., client wishing to make a purchase) Metacognition (e.g., assessed ease of scenario construction) Judged Likelihood of Future Events Similar to Event A (e.g., real clients actually wishing to make purchases)
avail3v3 Lehman Benson III, University of Arizona, 2006 17
Summary People often use rules of thumb or
heuristics to make judgments. Some judgmental heuristics, including
the availability heuristic, rest on meta-cognitions—our thoughts about our own thinking (Yates, 1990).
Several factors can distort a person’s perceptions about their meta-knowledge (Russo, 2002).
avail3v3 Lehman Benson III, University of Arizona, 2006 18
Managing the Availability Heuristic
Challenge: “Can decision makers protect themselves from the risks associated with judgment via the availability heuristic?”
One answer: “Yes. Decision makers can train themselves to ask ‘The Three Q’s’ when making frequency estimates or probability judgments.”
avail3v3 Lehman Benson III, University of Arizona, 2006 19
The Three Q’s 1) Question the importance of the problem:
“How accurate do I need to be?” “Does it matter that I am using a rule of thumb?”
2) Question the quality of the information being used to inform frequency estimates or probability judgments: “How good are our data?” “How complete are these scenarios?”
3) Question how much meta-knowledge one has: “How do I know whether I really know?”
avail3v3 Lehman Benson III, University of Arizona, 2006 20
When Considering the Three Q’s
Tradeoffs: Would the ease of using the availability heuristic offset its risk of yielding inaccurate judgments?
Stakes: Is the cost of making a judgment error so high that gathering more data or creating more scenarios is warranted, to avoid such an error?
Influences: What kinds of things might be influencing my judgments (e.g., vividness, ease of recall, ease of imagining scenarios), perhaps at the expense of “the truth?”
avail3v3 Lehman Benson III, University of Arizona, 2006 21
The Bottom Line Good decision making requires
both good meta-knowledge and good factual knowledge.
avail3v3 Lehman Benson III, University of Arizona, 2006 22
References and More Reading Carroll, J. S. (1978). The effect of imagining an event on expectations
for the event: An interpretation in terms of the availability heuristic. Journal of Experimental Social Psychology, 14, 88-96.
Combs, B., & Slovic, P. (1979). Newspaper coverage of causes of death. Journalism Quarterly, 56, 837-843.
Ruscio, J. (2002). Clear thinking with psychology: Separating sense from nonsense. Pacific Grove, CA: Wadsworth.
Schwarz, N. (2004). Metacognitive experiences in consumer judgment and decision making. Journal of Consumer Psychology, 14, 332-348.
Russo, J.E., & Schoemaker P.J. (2002). Winning Decisions. New York, NY: Doubleday.
Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive Psychology, 5, 207-232.
Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185, 1124-1130.
Yates, J. F. (1990). Judgment and decision making. Englewood Cliffs, NJ: Prentice-Hall.