The Psychology of Judgment and Decision Making
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Transcript of The Psychology of Judgment and Decision Making
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The Psychology of Judgment and
Decision Making
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Part 1:
Heuristics and Biases
• How they affect people’s judgments and decisions• How they affect researchers• How they affect MIS
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“ …people rely on a limited number of heurisitc principles which reduce cimplex tasks of assessing probabilities and prediciting values to sijmpler judgmental operations. In general, these heurisitcs are quite useful, but sometimes they lead to severe and systematic errors.” (from Tversky, & Kahneman, Science, 185, p.1124-1131.)
-> ‘People are systematically biased’
Definition: Heuristic and Bias
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Section 1:
Perception, Memory, and Context Biases
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A Foolish Consistency is the Hobgoblin of Small
Minds- Ralph Waldo Emerson
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Previous Beliefs and Expectations Affect
PerceptionIt Looks Red
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People Reconstruct Memories
Guess 4 NumbersNot Bad Guesses!My Numbers are1, 2, 5, and 16
Later
I Guessed 2, 3, 6 and 15I was Right!
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Save The Red Elephan
ts
Cognitive Dissonance
Later
Joe
It WAS RedYou’ll Sign
My Petition, Won’t you?
I saw red Elephant,
X
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The Halo Effect
That Elephant Has a Big Smile;
I bet He’s Red
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Contextual Clues
Small Elephant Big Elephant
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Parables of context biases and Purple Red elephants• People see what they expect to see (Mr.
Red)• People reconstruct memories (“I was right”)• People try to be “consistent” (It was red)• Nearby things affect perception (relativity)• People believe good things about good
people (The halo effect)
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Escaping Context Biases
• Take note of context• Know yourself• Consider the possibility of
alternative outcomes
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How to get the results you want from an
experiment, capitalizing on Perception, Memory
and Context(A roll play emphasizing the impact
perception, memory, and context can have in a research setting)
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Halo Effect
Their Tool
•Host uses bad grammar
•Host has unkempt appearance
•Hosts uses poor body language (slouches)
Our Tool
•Host smiles and conveys excitement about the new tool
•Host is nicely dressed
•Host greets people as they enter the experiment
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Create Expectations
Their Tool
•Host says “there is a chance our tool might work”
•Host says “we think our tool produces marginally better search results”
Our Tool
•Host expresses confidence about the performance of the new search tool.
•Host says “ we are excited about how effective our tool is”
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Control Comparatives
Their Tool
•Begin with a warm-up exercise using state-of-the-art technology that is well polished.
•Show the group the best of breed searching tools available.
Our Tool
•Run the warm-up exercise on an old, slow computer attempting an impossible task.
•Provide a poor tool to achieve the task.
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Get Them to Commit to Your Result
Their Tool
Conduct the following pre-experiment survey:
A. I am a good searcher who gets good results.
B. I am a jerk
(Please choose only A or B)
Our Tool
Conduct the following pre-experiment survey:
A. I learn quickly and do well with new tools.
B. I am a jerk
(Please choose only A or B)
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Give Them Cues About How They Did
Their Tool
•Host frowns when he/she looks at the screen.
•Host shakes head and makes low grunting noises.
Our Tool
•Host smiles as he/she looks at the participants screen.
•Host takes notes by noticeably checking items off a list while nodding head.
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Give Them Time to Reconstruct Memory
Their Tool
•Host ends the session by saying “Wow that took a long time….um…come back next week to fill out the survey.
Our Tool
•Host ends the session by saying “we were doing so well, we lost track of time. Oh well, just come back next week to fill out the survey.”
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Section 2:
Survey Question Biases
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Question phrasing, what answer choices are presented and how they
are presented...
Survey Questions Biases
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On September 27, 2001, President Bush put forth the UN Hostile Powers resolution forbidding UN
Humanitarian Economic aid to Afghanistan. Was President Bush within his powers as the President of the US to enact such a United Nations Resolution?
a. President Bush was definitely within his power. b. President Bush overstepped his authority.
Will you vote in favor of a special finance package costing the average taxpayer $475 to finance
Operation Enduring Freedom?a. Yes, since it is likely Congress with provide for another tax rebate when the economy turns around.b. No, $475 in taxes negates the recent tax rebate.I would need to understand more about the finance package.
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On September 27, 2001, President Bush put forth the UN Hostile Powers resolution forbidding UN Humanitarian Economic aid to Afghanistan.
Was President Bush within his powers as the President of the US to enact such a United Nations Resolution?
a. President Bush was definitely within his power. b. President Bush overstepped his authority.
Will you vote in favor of a special finance package costing the average taxpayer $475 to finance Operation Enduring Freedom?
a. Yes, since it is likely Congress with provide for another tax rebate when the economy turns around.b. No, $475 in taxes negates the recent tax rebate.I would need to understand more about the finance package.
Framing
Gain/Loss
Filtering
Ordering
Forbid vs. not allowingAttitude/
Behavior
pseudo-opinion
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Research Life Cycle: Observation
• Through the use of surveys, observations verify or contradict MIS research hypotheses.– If the survey is biased, the research is nullified.
• Valid theories could be unnecessarily quashed.– If the survey is manipulated to reinforce the
hypothesis, the research will not withstand further investigation.• This will hider the acceptance of MIS as a discipline
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Section 3:
Models of Decision Making
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Expected Utility Theory
Wealth
Utility
--A “normative” theory of behavior
--Rational decision making principles
•Ordering of alternatives
•Dominance
•Cancellation
•Transitivity
•Continuity
•Invariance
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The Allais Paradox-- Violation of Cancellation Principle
The paradox is that anyone choosing Alternative A in the first situation should also choose Alternative A in the second—otherwise, the Cancellation Principle is violated.
Alternative A: $1,000,000 for sureAlternative B: A 10% chance of getting $2,500,000,
an 89% chance of getting $1,000,000, and a 1% chance of getting $0
Alternative A:Alternative A: An 11% chance of getting $1,000,000, An 11% chance of getting $1,000,000, and an 89% chance of getting $0and an 89% chance of getting $0
Alternative B:Alternative B: A 10% chance of getting $2,500,000, A 10% chance of getting $2,500,000, and a 90% chance of getting $0and a 90% chance of getting $0
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Intransitivity
If the difference in intelligence between any two applicants is greater than 10 points, choose the more intelligent applicant. If the difference between applicants is equal to or less than 10 points, choose the applicant with more experience.
IQ Experience (Yrs)
Fritz 120 1
Gertrude 110 2
Ralph 100 3
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Prospect Theory--Improvement
– replaces notion of utility with value
– different value functions exist for gains and losses(Endowment Effect)
GrainsLosses
Valu
e
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Prospect Theory--Improvement
• People’s tendency to overweight small probabilities.
• A reduction of the probability of an outcome by a constant factor has more impact when the outcome was initially certain than when it was merely probable—Certainty Effect
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Other Alternatives to Expected Utility Theories
• Satisficing• Regret Theory• Multi-attribute Choice• Non-compensatory Strategies
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Conclusions in MIS Field
• Take caution in making assumptions and principles—they are easily violated.
• Design as many experiments as you can, and consider as many conditions as you can to make your principle complete.
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Section 4:
RepresentativenessAvailabilityRiskAnchoringRandomnessCausationAttribution
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Heuristics And Biases
• People rely on heuristic when facing complicate decision• Advantage: normally “optimal” answer; reduce time and energy• Disadvantage: lead to biases and inconsistency• Focus: the process reaching the conclusion+consequent biases
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Representativeness Heuristic
Definition:Judge probability by the degree to which A is representation of B
Example1:P(A) > P(AB)• Don’t be misled by highly detailed scenarios
Example2: The law of small numbersgambler’s fallacy vs. the hot hand• Remember that chance is not self correcting• Don’t expect too much alternations
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Example3:use base rate information only when it’s consistent with their intuitive theories of cause and effect• Whenever possible, pay attention to base rates
Example4:tendency to make “nonregressive” predictions• Don’t misinterpret regression toward the mean
Representativeness Heuristic (2)
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Availability HeuristicDefinition: judge probability by the ease with which the instance can be brought to mind
Examples: media, difficult to generate, visualize
The limits of imagination: difficult-to-imagine extremely negative outcome
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Vividness Heuristic
Definition:concrete or imaginable; emotionally interesting or exciting; close in space or time
Examples: individual testimonials
it does exist, but is limited(time, laboratory research) how to conquer: explicitly comparing
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Probability and Risk
• Bias in heuristic – More statistics: Bayes’ theory; – Wishful thinking: “happens to me? Never!”– Compound events: Welcome to the real world!
• Each of all 500 components has the rate of 99% working great, ….now you feel better?
– I am the expert…..so what?• Perception of risk are strongly biased in the direction of
preexisting view.
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Probability and Risk (2)
• Managing the information system– Deal with new information
• Maintain accurate records• Avoid conservatism• Avoid convenience
– Be objective• Be aware of wishful thinking• Break component events into simple events
– Realize different perspectives– Reduce risk in system building
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• Introductory example: Average January temperature in Pocatello, Idaho
• The insufficient adjustment up or down from an original starting value, or anchor.
• Very Robust– Works with extreme anchors
• Examples– Real estate– Software development
• “Give me a preliminary estimate…”
Anchoring and Adjustment
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Anchoring and Adjustment in Research
• Possible problems– Anchoring on previous research– Anchoring on a “hunch”
• Solutions– Be skeptical of previous research– Be thorough with methodology
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Perception of Randomness
• Coincidence– Odds of particular episode happening
are low, but odds of some similar episode happening somewhere are high
– Examples• Dr. Booker’s story of meeting Dr.
Nunamaker• Which one is more random?
– 0111001000111001011011– 0010101010110101000101
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Randomness and Research• Finding patterns in research data
that don’t exist– Stick to the methodologies and
statistical analysis
• Coincidences happen– Take advantage of those coincidences
that happen– Increase the odds of coincidences by
networking
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Correlation, Causation and Control (CCC)
• Correlation: whether two variables are related.– Illusory correlations
• Common sense dominated• bacon-tiger vs. bacon-egg
– Invisible correlations:• Absence of expectation• meat consumption vs. colon cancer
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CCC (2)
• Causation– Correlation and Causation
• Control– Self confident: I can control myself
better!– Helps that harms: connections
between health and a sense of control
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CCC (3)
• Take-aways– Bias in information colleting and
decision making– Focus on more than confirming and
positive cases– Observation vs. expectation– Distinguish between correlation and
causation
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Attribution Theory
• Definition: Attribution theory is a psychological theory about how people make “causal attribution,” or explanations for the causes of actions and outcomes
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Important Exception
• Attribution theory works most of the time, but there are several important exceptions
• When people disregard consensus information
• Salience information has more impact• Behavior is the most salient thing in a
social setting
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Important Exception (2)
• Difference in focus between actors and observers
• People rely heavily on the most salient factors at the time
• Other attributional biases
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Methods to Avoid Attributional Pitfalls
• Pay close attention to consensus information
• Ask how you would have behaved if thrust into the same circumstance
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Section 5:
Biases in Decision Making in Social and Group Contexts
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Group Influences
• Social facilitation (Mastery vs. Performance, 1965)
• Social loafing (Work in group vs. Work alone, 1965)
• Bystander intervention (Are you above 9?)
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Group influences (2)
• Taking cues from those who are similar;
• Social analgesia (Influenced by perceptions of others);
• GroupThink: loyalty and pressures to conform;
• Minority influence on majority.
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Biases in Group Research
• Individual-level biases exist in groups as well;
• Preexisting tendencies are amplified;• The less permissive the leader is, the
worse the group performs;• The group performs no better than the
best member;• Brainstorming in group is less effective
than conducting with people individually.
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Section 6:
Common Traps
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• Overconfidence• Self-fulfilling prophecies• Behavioral Trap
Common Problems
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Overconfidence (OC)• A belief in ability or understanding
that adversely affects a decision– Space Shuttle Challenger– Pearl Harbor
• Heuristics– Measure or assessment of confidence
level– Accuracy of decision
• Bias– Discrepancies between accuracy and
confidence
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Overconfidence: Causes & Impacts
• Possible Causes– When judgment difficult (no right answer)– Ignorance (initial phases of research)
• Impacts– Extreme
• Overconfidence when essentially certain• Not just a consequence of underestimating risk or
misunderstanding
– Social• Wrongful convictions• Societal/moral losses due to decision maker
overconfidence• more confidence & belief in what U are doing
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Overconfidence Fixes• Calibration
– Bringing decision maker’s confidence in line with accuracy
– People can learn– Lots of feedback after decision making– Takeaway:
“Stop to consider reasons why your judgment might be wrong”
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Overconfidence and MIS• Design system -> feel good -> overlook
bug
• Literature review -> feel informed -> faulty conclusion
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Overconfidence and MIS• May reduce flexibility in judgment
May Reduce
• Dissertation -> ask questions to learn -> ask yourself questions to verify your thoughts
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Self-Fulfilling Prophecies (SFP)
• Confirmation Bias– A positive testing pattern (confirmation
bias) leading to difficulties in decision making
Answer
Biased decision space
Total Decision space
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SFP Model
Source: http://www.mhhe.com/socscience/social/ibank/set-1.htm
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Pygmalion Affect (SFP)
• A false definition of a situation causing a new behavior making an original false conception true
• Cause:– Stereotypes, perceptions
• Advantage (if used properly):– Treat people what they ought to be and
you help them become what they are capable of being
• Disadvantage:– Self fulfilling prophecies, if not careful
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SFP Impacts• Pygmalion Affect
– Favoritism in classroom by teacher towards “gifted” students• Gifted students excel
• Perceptions of women by men – Male subject presented with snapshot of
attractive womenand unattractive woman• Attractive women favored after phone
conversation
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SFP Impacts (2)
•Interview process based on race
–Minorities performing differently during interview process when interviewer is postured “defensively” or with “distance”
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SFP Fixes
• Focus on motivational factors– Warning interviewers about questions
that indicate closed-mindedness– Can be used to motivate “problem”
students
• Request “disconfirming” information during interviews– Similar to proving null-hypothesis
before conclusion??
• Possibly by asking asking why judgments might be wrong
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SFP and MIS• Research question produces results found in
context of original research question• Avoid testing techniques/methodologies that are
too narrow – confirmation bias– System design– Research hypothesis
• Favoritism based on expected or forecasted performance – Pygmalion affect– Design technique– “Upcoming” technology
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Behavioral Traps• A course of action that starts out as
promising, but later becomes undesirable– Traps
• Avoiding potentially beneficial behavior– Waiting on hold for tech-support– Exercise
– Counter-Traps• Potentially harmful behavior
– Avoiding chores– Cigarette smoking
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Behavioral Trap Categories
• Time delay– Instant gratification vs. long term
consequences• Smoking one more cigarette
• Ignorance– Result of action not understood or predictable
at start of action• Smokers in the 19th century• Starting a new job only to find out that it
sucks.
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Behavioral Trap Categories (2)
•Investment
–Prior investment of resources (e.g., time, money) leading to choices not normally made
•Vietnam war
•R & D investment (time, money) only to be out done by competition
–Should project continue????
–Lead to “sunk-costs”
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Behavioral Trap Categories (3)
• Deterioration– Similar to Investment traps, but
benefits and costs change over time
Avoid crop loss ($$) even though negative environmental and social impacts
Kill bugs, Increase Crop Yields
Insecticide Use
Avoid withdrawalEnjoymentHeroin User
Over timeStartSymptom
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Behavioral Trap Categories (4)
•Collective
–Quest for self interests having negative impacts on group
•Two criminals offered choice: confess or go to jail
–1 Confesses no jail -> partner gets 10 years
–2 Confess -> both get 5 years
–No confession -> both get 1 year
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Behavioral Trap Fixes
• These traps often don’t last long– People learn and move on
• Corporate leaders stop wasting money• Girlfriend dumps boyfriend (he calls old
girlfriend)
• Set limits in advance– Use limits to assess continuation
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Behavioral Traps and MIS
• Starting system design before jumping to code
• Gather facts before making conclusions• Identifying scope of project before
starting and assessing status and progress regularly
• Identifying that research question may not take expected path and adapting.
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Part 2:
Decision Making and Heuristics in a Complex World
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Heuristics in a Complex World• Humans are “boundedly rational”
given the amount of information necessary for rationality and human cognitive abilities
• Future is difficult to predict, both externally (states of the world) and internally (future preferences)
-> Humans use simple heuristics to satisfice rather than optimize
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“Simple Heuristics that Make Us Smart…”
Heuristics are … frugal: get away with little
information… fast: don’t need long computation… cheap: don’t need costly information
search, storage, and computation… robust: perform better than
“optimal” regression on new data sets; less affected by noise
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Overconfidence Revisited
• Questions in overconfidence studies are not randomly sampled from the environment, but selected by researchers
• Frequency judgments of correct answers are quite well-calibrated
-> Should researchers focus on finding biases or explaining normal functioning?
-> Which perspective is better for MIS researchers?
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Heuristics and Biases: A Paradigm
• Tversky and Kahneman’s heuristics and biases has been the dominating paradigm in JDM research for about the last 30 years
• What are the benefits and costs of a strong paradigm?
• When does a discipline need a paradigm shift? (When researchers get bored?)
• What is the ruling paradigm in MIS? How “strong” is it? What is its effect?
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New Perspective in JDM: Emotions &
Neuroscience
• “Risk as Feeling”• “Regret Avoidance” • Mood and Decision Making• “Descartes’ Paradox”• “Emotion as Information”
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