Decide now or wait for something better? Our standards drop over time


Date:
June 18, 2020
Source:
University of Zurich
Summary:
When we make decisions, we don't always have all options available
to choose from at the same time. Instead they often come one after
another, as for example when we search for an apartment or a flight
ticket. So we have to decide on something without knowing if a
better option might have come along later. A study has shown that
our standards drop more and more in the course of decision-making.



FULL STORY ==========================================================================
Be it booking flight tickets, buying a car or finding a new apartment,
we always come up against the same question: Should I strike while the
iron's hot, or wait until a better offer comes along? People often
find it difficult to make decisions when options are presented not simultaneously but one after another. This becomes even more difficult
when time is limited and an offer that you turn down now may no longer
be available later.


==========================================================================
"We have to make decisions like this countless times every day, from
the small ones like looking for a parking space to the big ones like
buying a house or even choosing a partner," says Christiane Baumann,
a doctoral candidate in the Department of Psychology of the University
of Zurich. "However, until now, the way we behave in such situations
has never been thoroughly examined." Under the leadership of cognitive psychologist Bettina von Helversen (previously UZH, now University
of Bremen) and in collaboration with Professor Sam Gershman (Harvard University), Baumann carried out numerous experiments to investigate
this issue. Using the results, she then developed a simple mathematical
model for the strategy that people use when they make decisions.

Is there an optimal process? It is easy, using a computer, to find the best-possible process for making decisions of this type. "But the human
brain is not capable of carrying out the complex calculations that are required, so humans use a rather simplified strategy," says Baumann.

Baumann simulated purchasing situations with up to 200 participants in
each test in order to find out what strategies people use. In one test,
the participants were told to try to get a flight ticket as cheaply as
possible - - they were given 10 offers one after the other in which the
price fluctuated; meanwhile the fictional departure date was getting
nearer and nearer. In another test, people had to get the best possible
deal on products such as groceries or kitchen appliances, with the
fluctuating prices taken from an online shop.

Expectations driven down The evaluation of the experiments confirmed
that the test participants did not use the optimal, yet complex, strategy calculated by the computer. Instead, Baumann discovered that they use a
"linear threshold model": "The price that I am prepared to pay increases
every day by the same amount. That is, the further along I am in the
process, the higher the price I will accept," explains Baumann.

This principle can be applied not only to purchasing decisions,
but also situations such as choice of an employer or a life partner:
"At the beginning perhaps my standards are high. But over time they may
lower so that in the end I may settle for someone I would have rejected in
the beginning." A model to stimulate the human strategy Baumann analyzed
the experimental data and developed a mathematical model that describes
human behavior in various scenarios. "That helps us to better understand decision-making," says Baumann. The model also allows us to predict the circumstances in which we tend to buy a product too early -- or when we
delay too long and then have to take whatever is left in the end.

Baumann thinks these findings could help people make difficult decisions
in future: "In the current digital world the amount of information
available for decision-making can be overwhelming. Our work provides
a starting point for a better understanding of when people succeed or
fail in such tasks. That could enable us to structure decision-making
problems, for example in online shopping, in such a way that people are supported in navigating the flood of data."

========================================================================== Story Source: Materials provided by University_of_Zurich. Note: Content
may be edited for style and length.


========================================================================== Journal Reference:
1. Christiane Baumann, Henrik Singmann, Samuel J. Gershman, Bettina von
Helversen. A linear threshold model for optimal stopping behavior.

Proceedings of the National Academy of Sciences, 2020; 117 (23):
12750 DOI: 10.1073/pnas.2002312117 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2020/06/200618111007.htm

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