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CEP lecture 2
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Complete transcript of lecture 2 Consumer and economic psychology
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CEP Lecture 2 22-11-2018My situation yesterday, hearing that I have to give a lecture today, sort of fts the topic that we are looking at today, namely how
people make spontaneous decisions if they have to and how that compares to more controlled decisions when they have more
time. We’ll also look at decisions that have short-term consequences versus more long-term consequences.
Homo oeconomicus
The starting point for much of the research that I am going to present is this traditional economic model of very rational human
being that acts in line with their self-interest and has the goal to maxime the outcome for him- or herself. This is of course a very
rational model that’s underlying many economic models. The idea is that there’s something like a cost-beneft analysis going on.
You compare different options and choose the one that has the least costs and highest benefts. That’s a very nice model and as I
mentioned it’s the basis for many economic models. You can have a mathematical function for each decision and so on. But
pretty quickly it was realized that that is not what people tend to do. Often times more things go on. People for example can be
very angry for potentially missing out on an attractive product that they want to buy or attractive sale that is going on. People
can be very lost in these situations. Often times people have to make very quick decisions and do not have the time to make all
these calculations. Of course often times people don’t have the full set of information. Sometimes you have subsets of
information, you have read some information in the news paper or you see an add on tv and so on. But you don’t have the full
background information on a specifc product or on a specifc company and so on. People also have companies that they like and
lots of people like products from let’s say Apple or some people like products like products from other tech companies. And often
times it doesn’t really play such a big role whether the product is really the best in a certain domain, so whether this is really the
best wireless headphone set, but it looks nice and it’s from a certain company so people buy it. That’s a very unrational decision.
We’ll look at these kind of decisions today.
First doubts about economic model arose in the context of a theory that has a weird name, it’s called prospect theory. It’s one of
the biggest challenges towards the traditional economic model. What usally the research in that area did is very simple studies.
Risk aversion and risk seeking. People had to make decisions between option A and option B. In the frst case you would have to
decide whether you take 4000 dollars with a probability of 80 percent or you get 3000 dollars straight away. Most people would
actually go for 3000 dollars because that’s a certain thing and would not go for the more risky option which could potentially
yield higher outcome. The other situation would be about a loss. When you have the option to lose either 500 dollars for sure or
1000 dollars with a certain probability connected to it, people would usually show a different kind of behavior. They would usually
tend to go for more risky option here because it seems like you still can minimize your losses. This is indeed what is found. In the
frst case, most people go for the 3000 dollars and skip the frst option. In the second case, the pattern is reversed. People tend
to go for the more risky option simply because it seems like you have more to gain or less to loose in this situation. These
decisions are not very rational if you apply a more mathematical model to that decision. That type of result has led to a lot of
research that looked at why people and how people make these irrational decisions.
One effect that is quite popular in behavioral economics, which is the area that studies this kind of decisions, is the effect that is
called the endowment effect. It is a sub-effect in the area of loss aversion. People try to avoid losses. The endowment effect is
nice and interesting effect because the studies that are done investigating it are very simple, very nice for the participant, but
they show a quite intriguing pattern that once you have something people attach more value to it. Endowment effect = people
attach more value to goods they own. The studies often times consist of a situation where I would for example give one of you a
pen and then would ask whether you would sell me that pen and I would offer the actual prize frst and people are reluctant to it
and then I would go higher than the actual prize of then pen so you have something to win. But what is shown is that people tend
to overestimate the actual prize of the product they have. They quite value what they have at some point. They are very
reluctant to sell something and if they sell something the price needs to be quite high. Losses bite more than equivalent gains.
Average factor: 2.25. Uit mail Epstude: This statement on the slide means that according to prospect theory (and the related
studies) losses are experienced more strongly than gains. The afectiie response to losses is about twice (or 2.25 times) as
strong as the one to gains. So that’s the endowment effect.
What we look at today is different types of heuristical judgments that people make in any kind of decision context but we’ll look
at how that applies to a consumer context in specifc. And we will look at some more recent developments there (additional
heuristics). In the end we’ll look at how people process the information for decisions with short-term outcomes and with long-
term outcomes.
When we talk about heuristics, as you can see, we frst need to defne it. You might have heard this concept before. A heuristic is
simply a quick rule for a decision, these decisions are not super rational, super elaborate, they are just very quick decisions.
Sometimes it’s called rules of thumb. These decisions lead to a certain outcome.
The outcome is usually described as a bias or a wrong judgment. A bias is a judgment that is fawed in the sense that it doesn’t
match a formal logic or criterium that you can establish. So if you can come up with a situation where for objective reasons one
option is really the best choice and people would continuously not choose the best choice but something else, then that would be
called a bias. The problem with that term bias is in my example already, if everybody does it, if everybody makes this wrong
judgment, it’s very difcult to describe it. Major critique in that area is that these fawed judgments just because they don’t
conform to a logical norm might not necessarily be a fawed judgment, they might be a very functional judgment. They might be
what makes sense to most people in whatever situation. So whenever you hear this term bias you always need to keep in mind
that somebody has set up a criterium that this decision does not match and this mismatch is termed bias, but when somebody
else comes up and says another option is the best then the bias will be very differently. So the bias is determined by the person
who set up the criteria for match/mismatch. But in most cases that we examine now the bias is simply a mismatch between the
actual decision and the decision that would formally be logic or the best decision according to objective criteria.
Uit mail Epstude: Gigerenzer’s critique. He has published a whole lot of books about it. But his main critique is that it can't be a
bias if eieryone shows it. His research on things like the recognition heuristic show that heuristical judgments of lay persons
oftentimes beat expert's iery rational considerations (e.g. in predicting the stock market, or predicting the outcome of the
Wimbledon tournament).
Often times these heuristical judgments have been examined in quite artifcial ways. This is an example, the Linda problem.
Description of a woman. The description is geared towards left-wing feminist person who is very much concerned about social
justice concerns. The decision that participants have to make is to answer what is more likely, that this person is a banker or a
banker and a member of the feminist movement. As you can see the whole description is very much geared towards feminist
movement so most people would say that option B (banker and member of feminist movement) is more likely.
However, the overlap between the large group of bankers and the very small group of feminist bankers is not very big. Feminist
bankers is a very tiny subgroup. It is in general not very likely that someone is a feminist banker, it’s much more likely that a
, person is a banker than a feminist banker. What happens in this situation is that people ignore the base rate of the tiny group of
feminist bankers and therefore go for that option even though the group of bankers is much bigger. This is called the conjunction
fallacy. It has been investigated in different contexts. This is just the most famous example.
A more consumer-related example is this one. People in a gambling situation are asked to predict or to choose for heads or tails.
This situation has been made famous in the movie “No country for old men” where the killer asks each of his victims to make this
choice. They think they have a chance of surviving but in reality they don’t but each victim has to makes this choice. Here, in the
typical study on the gambling fallacy or gambler’s fallacy, what would happen is that you would be encountered with a situation
where 5 times the same outcome happened after this coin toss and your task is to predict the 6th time. What most people would
do is, what quite often happens is, that people predict that in the 6th case the other side of the coin should emerge because in
general people know that it’s a 50/50 chance. However, what is ignored in this situation is that all of these coin tosses are
independent events so they are not related to each other. The chance for each of them is 50/50 and therefore the chance for the
6th coin toss is also 50/50. It’s completely independent of the other 5 but most people would predict in this situation that here
another outcome should emerge simply because it seems likely to happen. And also here, again, this is an example of ignorance
of base rate, namely the base rate that these are independent events that have a 50/50 base rate and it’s still a 50/50 chance for
the 6th coin toss.
All of these fndings have led to the formulation of the representative heuristic which is by far the most complicated heuristic we
are talking about today. Here the idea is that in general people ignore base rates and rely more on what Kahneman and Tversky
call representatitiveness of an event. So is an event representative for a certain category. You can also study that in a different
context. If you study for example how people categorize birds in that case, people also have a certain heuristic of categorizing
birds (if it lays eggs it must be a bird). However, not everything that lays eggs is a bird of course. If you apply that logic to the
situation that we discussed these decisions that are made, the core idea of the representative heuristic is that base rates are
ignored. So the actual distribution of an event in real life is ignored and therefore a decision is made that is not optimal. So
joining an anti-discrimination demonstration is more representative for feminist bankers than for bankers in general, but feminist
bankers are not a very common category or something very common in society. And, expecting heads after 5 times tails is
representative for the general 50-50 distribution, but overall these are independent events and that is ignored in the end. This is
the most complex heuristic, complex thinking. Why is that important? In the consumer context you can study this kind of
situation. For example in dynamic pricing or sales that a certain company does. If a company has a sale every few months and
consumers know that, that this will happen, they will infer that sale is a very common event and they might wait until the next
potential sale to buy something. If you violate this expectation then the decisions might be very different. What we need to keep
in mind for the representative heuristic is that base rates are not taken into account for decisions and therefore decisions are
sometimes fawed.
A more easy to understand second step or heuristic comes from this type of situation which is a situation where 2 people want to
take the plane. Both of them miss the plane. But one of them basically misses the plane by 5 minutes, the other one by about 30
minutes. So the situation for both of them is the same, that the plain is gone. But one of them just missed it, the other one
missed it by half an hour. The question in that situation is: Who would be more upset? Most people assume that Robert (missed
plane by 5 minutes) is more upset than Sarah (missed plane by half an hour). The question is why that is. The actual situation is
the same. People are at the airport, plane is gone, you can’t do anything about it. But still you fnd that people indeed tend to be
more upset in the frst situation (missed plane by 5 minutes) than in the second situation (missed plane by half an hour). This has
quite a lot of consequences. Therefore it led to the formulation of something that is called the simulation heuristic.
In the simulation heuristic the idea is that people tend to simulate the event that should/could have happened. The easier it is for
them to imagine or simulate that the outcome that they wanted to have happened, the more angry they should be. The easier
time I have to imagine that I had managed to get my plane, the more upset I should be. You could also do that with the bus. If
you run to the bus stop and see the bust leaving when you arrive, it’s very easy for you to imagine that you could have been on
that bus while if you come to the bus stop and there is no bus in sight you are probably less likely to be concerned about this.
People tend to simulate these alternative outcomes and if it’s relatively easy to imagine that the alternative outcome would have
happened people are more upset. That has led to a lot of research. I am saying that people are more upset now, but you can
replace upset with a whole set of emotions that might be connected to the outcome (angry, sad, frustrated). If I intended to buy
something but I was just not on time to buy something I might be upset, but I might also be angry, I might regret me being too
slow, so there’s a whole set of emotions that might be connected to that event and that kind of mental simulation of an
alternative outcome. A related concept is counterfactual thoughts, so this is the thought “If I had been earlier, I would have
managed to get my fight.” You can do the same thing in the future and imagine alternative outcomes: prefactual thoughts.
These thoughts tend to have strong infuence on future behavior and affect and also in the moment. Again with the idea, the
easier you can imagine the alternative, the stronger the response (behavior + affect) by the individual.
One potential outcome of such a situation (simulating an event) is that people regret the event. Therefore, regret is indeed the
most typical or prototypical emotion that has been studied in relation to these events where something didn’t go according to
plan, that you have a clear idea of how the event could have been. In the consumer context, this has been studied quite
frequently. Not only actual regret, when something happened and you regret it, but also so-called anticipated regret, which is
that you can imagine if you don’t make a certain decision, you will regret it and therefore you buy something. This has been
studied quite frequently and is used actively in advertising as we see in a second.
If you study regret outside of consumer context you can of course start very broadly, just asking people what in general in life do
you regret. That’s quite interesting topic. What you fnd in studies (on the slide 2 studies are combined in one graph) is that in
general, people regret things like decisions concering romance, family, career, education and fnance. These are the most
important ones. Of course, that depends on the age group you ask these questions which domains are the most important. If I
would ask you (students) what kind of things you regret in life and you would say education, you shouldn’t be here actually if that
would be the case (haha). Younger people, in general, tend to be more concerned with romantic things and with family things.
The older you get, the other things, like career and education, gain bigger importance. That’s why for this type of topic it’s
interesting to have a sample that is not only students because the topic differ.
If you look at consumer regret in the same way, where you just ask people what kind of purchases do you regret, you get things
like this. This is an American sample. People regret their decisions on consumer electronics, household furnishings and
equipment, apparel (clothing), personal care products and services, househould operations and supplies and so on. So there’s a
whole set of things. But you can see that the frst 3 stick out: consumer electronics, household furnishings and equipment,
apparel. In this study it has been controlled for the amount of money that a certain category would usually cost. That didn’t
really put it to the intensity of regret, but you can see that there is different categories that people can regret.
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