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Lecture notes

Complete lecture notes Consumer Behavior (590032-B-6), scored a 8.5 in the exam

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Complete lecture notes of the course Consumer Behavior (590032-B-6), including all given material and additional explanations from the lectures. Contains the main pictures and graphs to better understand the content

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May 20, 2025
Number of pages
54
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2024/2025
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D. r. amasino and dr. j. nolte
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Consumer Behavior
LECTURE 1 Consumer Behavior introduction
Preferences
Thinking clearly about... preferences • What is a preference? • The degree of liking for something; ranking of options in
choice, How much you like something, preferring one thing over another
Rational choice theory (file-drawer model)
• People have well-defined preferences • They make decisions to fit their preferences
I know what i like or not like and that is indicated by what i choose, don’t ask what they prefer just look what they choose
Stable across contexts (not in the real world)
Preferences influenced by our needs goals and desires→Preferences affect consumer behavior
Decisions in real world
50 options, consider many options and factors that pay a role (on sale, budget, lasting) →of we were purely rational we
would know immediately how we feel about each one and choose the best option
We usually consider an attribute most relevant eg. price
Context also matters, where is the product placed, next to what
Study→Attending a free poetry reading
Condition 1→ Pay condition (N=75) Pay $2 to attend? →• Attend for $0?
If you had to pay 2 dollars to attend the poetry reading would you go?
Condition 2→ Get paid condition (N=71) Get paid $2 to attend? →• Attend for $0?
→Then say to both groups it is actually for free and you don't get any money
More want to go if the alternative is paying 2 dollars→preferences do depend on context
Results:
1. Pay condition • Pay $2 to attend? 3% yes • Attend for $0? 35% yes
2. Get paid condition • Get paid $2 to attend? 59% yes • Attend for $0? 8% yes
Same exact question, but very different responses based on opportunities we have different preferences
It is not about attitudes because how we feel about poetry is not dependent on the options. But here we compare different
opportunities and consider the context in the process of making the decision
Preference reversals are common
Alternative view: Preference construction Slovic (1995)
• “preferences are labile, inconsistent, subject to factors we are unaware of, and not always in our own best interests”
• “the very notion of a “true” preference must, in many situations, be rejected”
Context matters
Brain has limited firing capacities, so the brain adjusts on the context
For example how we see colors is influenced by what is surrounding it
The same thing with consumer decisions, 5 dollars in the context of 1k feels very different than 5 dollars in 5 cents.
Theories
• Thinking clearly about... theories
• What is a theory? • A system of ideas intended to explain something, bringing together to try to explain something
Why did I buy the chocolate bar? Many theories
• Because I prefer chocolate bars over fruit
• Because chocolate triggers chemical reactions in my brain that I experience as pleasurable
• Because in humans’ ancestral past, preferring high-caloric foods was adaptive which is why humans evolved to seek out
foods high on sugar or fat
There is different levels of explanation and different ways to explain something
• A model→does not explain every single specific case, all models make some assumptions but are still useful to
organize the ways we think about
Patat vs. Friet
Why do some people call fries patat or friet
Patat in the north and friet in the south→what is the explanation?
Rivers around that boundary (geographic reasons), region (fits but probably not), cultural differences
Many things might be correlated but not good explanations
• All theories have blind spots



1

,What makes a theory useful?
• Internally consistent (=doesn’t contradict itself) a very specific definition refined over time
• Testable predictions→if there is no way to test predictions or are not specific enough then we have a problem
Eg einstein's theory was difficult to test
• Empirically supported (=likely to be true) →if you have testable predictions you have to test them to see if it holds to
what's happening and if the theory holds. In psychology we see conflicting findings, harder to know if something is
supported or not
Theories - example 1
Theory of Ego depletion (Baumeister et al., 2007):
• Self-control is a limited resource: engaging in one task that requires self-control reduces ability to use self-control in a
second task→we run out of self control after a bit→plausible intuitively
• Glucose is the limited resource that is depleted by self-control
1) Internally consistent (=doesn’t contradict itself) but issue is what exactly is self control
• What is the definition of self-control? Working memory? Suppressing distractions/attention? Emotional reaction/
Frustration with a difficult task? Can be circular—anything that induces the ego depletion effect. Data influence definition
• Same task (3 x 3 multiplication used to induce ego depletion and as control in different papers)
→there should be more precision in defining what a theory actually means
• 2) Testable predictions
• Doing a self-control depleting task before another should result in worse self-control performance on a 2 nd task (YES)
• Ingesting glucose after the first task should improve performance on the 2nd task (can be tested)
• Boundary conditions? How long does the 1 st task need to be? How intensive does it need to be? Not so clear,
something that can be refined with data, but needs to be more specifically defined
• 3) Empirically supported (=likely to be true)
• Glucose mechanism is biologically implausible on timescales tested, and not supported by evidence (Vadillo et al.)
• Psychological effect does not replicate it larger tests (Hagger et al., 2016; Vohs et al., 2021) has not replicated
Another issue in theories: Generality-specificity tradeoff
• General: covers many phenomena & behaviors
• Specific: able to predict behavior with high precision
Physics can do both of them→covers big phenomena with specific predictions
Evolution is high in generality and low in specific
Theories – example 3
• Gambler’s fallacy: Erroneous belief that a random event is less or more likely to happen based on the results from a
previous series of events
• Example: I flip a coin and it keeps landing on heads, you might it will land on tails with higher than 50% chance
• Assuming it is a truly random coin, each coin flip is independent.
Generality-specificity tradeoff→ not general but is very specific
It would be more useful to have more general theories rather than too many for specific situations, but still specific
A cautionary note on highly specific explanations
• Sometimes they are tautological (“optimism bias” not explaining something it is just an observation, explanation is not
deep enough to cover more context, it is not really a theory, it is just naming something, not the ending point)
• This can be masked by “dressing things up” in different names
• They often make you think: But WHY?
• What is the proximate mechanism? The “how” behavior is generated
• What is the ultimate mechanism? The “why” behavior is favored
Example→Why did I buy the chocolate bar?
o Because I prefer chocolate bars over fruit
o Because chocolate triggers chemical reactions in my brain that I experience as pleasurable
o Because in humans’ ancestral past, preferring high-caloric foods was adaptive which is why humans evolved to seek
out foods high on sugar or fat




2

,Ultimate and proximal explanations Scott-Phillips et al., 2011




LECTURE 2 Heuristics, biases, & nudging
High specificity (then cognition, less specific, then evolution very general)
Rational choice theory
The traditional view: Rational choice theory→ People...• have well-defined preferences (file drawer model)
• process all information • weigh the relevant information (know how important in the decision)
• consistently choose according to their preferences (can always decide what they prefer)
Decisions in the real world→some people might actually calculate and weight preferences, but it is really time consuming,
and when stakes are low it is not worth it, for high stakes try to decide in a more optimal way
• People often deviate from the principles of rational choice theory→ People sometimes
• Construct their preferences in the moment
• Ignore or avoid relevant information (not seek out all the information we need to make a choice)
• Rely on irrelevant information (that tells nothing about the quality of the product) • Make mistakes
Experiment 1
Decide between small coffee for 2,50 or bigger one for 3,50→What do you choose? Very split
If we add a third option → small coffee for 2,50 , medium for 3,50, large 5$ →clear preference for the medium option
BUT why did you need to have an additional option to prefer the medium over the small? Against the rational theory,
adding one item should not matter on your preferences and decision
• People often deviate from the principles of rational choice theory [EXPERIMENT 1]
Preferences are influenced by context
• Compromise effect: An option is chosen more often when its attributes are not at the extremes (medium option>>)
Experiment 2
Choose between small popcorn 3.50 or large for 6,50→vast majority preferred the small
If we add a medium option for 6$ →3,50 6 6,50→shift more to the large one because we added the medium option
• People often deviate from the principles of rational choice theory [EXPERIMENT 2]
• Attraction/decoy effect: Option A is more strongly preferred over Option B if A obviously dominates another option
→larges is just a bit more expensive but a lot bigger than the big one, and just because we have a medium the large
looks more appealing, even if they would’ve chosen the small one in the first place
Context matters
Compromise and attraction effects summarized:
• Compromise: middle option chosen more often • Attraction/decoy: option that dominates is chosen more often




Context does matter, add an option nobody would choose that still affects your decision



3

, Heuristics & biases
Heuristics & biases program→ Kahneman & Tversky→• Study how people actually make decisions, without considering
how we should make decision (rational choice theory) • Integrate psychological principles
• Biases: systematic deviations from rationality
• Heuristics: mental short-cuts,process in which people get to the decision, not evaluating and weighting all the options,
sometimes we rule out certain options to come up with a decision faster, get a good enough option relatively quickly
Biases
Endowment effect • People value something more when they feel a sense of ownership
If you have a mug, how much would you sell it for? If you don't have it how much would you pay for it?
People who have it want to sell it to a higher price than people who do not own it are willing to pay
Once people buy something it is difficult for them to send it back because they own it already, free trials also work by
making people not giving up what they have, once you experienced it it is hard to give up
Framing effect • Preferences can shift depending on how information is presented
If you want people to buy vegetarian meat you should pack it like normal meat, more likely to think of it as meat and
approach it the same way.
In medical decisions→90% chance of success of surgery is more likely to be positively perceived than 10% chance of
lack of success, whether we present positive or negative point of view matters in decisions
Framing example→Pandemic outbreak, expected to kill 600 dying, there are 2 alternative programs to adress it
Gain frame: • If program A is adopted, 200 people will be saved [72% choose]
• If program B is adopted, there is a 1/3 probability that 600 people will be saved and 2/3 probability that no people will be
saved [28% choose]
Loss frame: • If program C is adopted, 400 people will die [22% choose]
• If program D is adopted, there is a 1/3 probability that nobody will die and ⅔ probability that 600 people will die [78%]
When saving 200 you were also letting 400 die, but then most people switch their choice from safe to risky option
When choosing of saving 200 you were not thinking of the 400 you were letting die
Sunk-cost fallacy→• “throwing good money after bad”
• Investing money or effort into something because some amount of money or effort was already invested→keep putting
more and more money into it because you already invested so much
• Recency of payment increases effect
If you pay a lot to go to a sky vacation but the weather is really bad, you go anyway because you spent so much even
though there is an additional cost to add and you would have rather stayed home
Can be used for good outcomes→paying a monthly membership to commit to going, if you pay per year or per visit you
are not gonna feel the same sunk cost obligation
→there is Dozens of biases Why? Too much info information, not enough meaning, need to act fast
Heuristics & biases
• Biases are labels for behaviors, not theories for explaining it, not a deeper understanding why is it that
• “X bias”, “X preference”, “X effect” • Be aware of circular explanations (e.g., “lying aversion”)
• What causes biases in consumer behavior?
• Tversky & Kahneman (1974): heuristics→mental shortcuts people adopt to make faster decisions
Availability heuristic
• People judge the likelihood of events by the ease with which they can generate an instance of that event
• Retrieve from memory, imagine, generate examples, ability to visualize
• More general application: people rely on things that come to mind easily (cognitive ease)
People thought shark attacks were more likely to happen than plane crashes because they heard more of it in the news,
but in reality it is the opposite
Postcode lottery, if you neighbour wins you think it is way more common than it actually is
Anchoring and adjustment
• People start from an initial value (the anchor) • Then adjust upwards or downwards
• But adjustment is often insufficient→stuck to whatever value they started with
• By manipulating the anchor, final judgments can be manipulated
Estimate the population of Chicago? • More or less than 200,000? How many? • More or less than 5 million? How many?




4

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