compromise effect
an option is chosen more often when it’s attributes are not the extremes
preferences are influenced by context
attraction/decoy effect
option A is more strongly preferred over option B, when A obviously dominates the other option.
Kahneman & Tversky
studied how people actually make decisions with integrating psychological principles
biases and heuristics
biases
labels for behavior, not theories for explaining them
- endownment effect
- framing effect
- sunk-cost fallacy
endownment effect
people value something more when they feel a sense of ownership.
for example test-driving, free return trials etc.
framing effect
preferences can shift depending on how information is presented.
sunk-cost fallacy
people will keep investing when they’ve already invested in something. because otherwise they will feel as if they wasted money.
heuristics
availability heuristics
people judge the likelihood of events by the ease with which they can generate an instance of that event.
from memory, imagine, generate examples, ability to visualise it.
cognitive ease
people rely on things that come to mind easily
anchoring and adjustment
people start from an initial value and then adjust up- or downwards. the adjustment is often insufficient and by manipulating the anchor final judgements can be manipulated.
mental accounting
people put money in different accounts for different things, while it all has the same monetary value.
prospect theory
theory about how people value losses and gains and think about probability
3 aspects of the value function
loss function
effects/biases in prospect theory
disposition effect
traders tend to sell winning stocks too early and hold on to losing stocks too long.
due to the reference point and tendency to seek risk under loss
status quo bias
people tend to stick with the default/status quo, even if this was randomly determined
end-of-the-day effect
as gamblers lose more money, they are more likely to bet on long-shots.
mixed evidence on taking more or less risk after loss.
- realized/money exchanged loss = more risk averse
- paper/not yet cashed out loss = more risk seeking
probability weighting function
how we weight probability
- we overweight low probabilities
- underweight high probabilities
for example people play the lottery, but also take out insurance for rare events.
certainty effect
p weighting
the (sometimes small) step from a high probability to certainty has a large psychological effect.
nudging
changing the choice architecture that alters people’s behavior in a predictable way without forbidding options or significantly changing their economic incentives.
problems with nudging
solutions for limited acces to relevant information
nudging limitations
decision information
- increase visibility
- make easier to interpret
- provide reference points
for example the nutri score instead of just the macro’s