Philippa Noble conducts an experiment into the relative strengths of altruism bias and the bandwagon
effect with a donation framing.
Our results were as follows:
After taking on a behavioural economics
project, Amy Mitchell and I chose to test the relative strengths of the
bandwagon effect and altruism bias within PGS in a donation scenario. The
bandwagon effect, sometimes known as herd behaviour, is where our behaviour
copies what the majority has done before. For example, buying a new product as
it is popular with consumers. Altruism bias, however, is where our behaviour
gravitates towards the fairer or more just option.
Our main hypothesis was that the bandwagon
effect would override the altruism bias and be the main dictator of test
subjects’ behaviour. The bandwagon effect is a powerful cognitive bias, which
drives much of our behaviour based on strong egos or social norms - effectively
our entire understanding of what is appropriate behaviour. However, with
donation framing, altruism bias could be emphasised to the extent that it would
override this bias.
Before school on a Thursday morning, we
followed a scientific method, using both a control and test group to check that
our results would be valid. Taking a control group of 12 (from different year
groups and genders), we offered each subject a choice of two jars, one labeled
“John” and the other labeled “Jeremy”. We framed each trial with the following
scenario:
“We have been raising money for the homeless
in Portsmouth and would like your help to decide who we should give it to. John
and Jeremy are both from Portsmouth and are equally in need. Please cast your
vote.”
The subjects then took a counter to place their
vote in either jar, removing it afterwards to reset each trial. We repeated
this method with a test group of 10 (from different year groups and genders),
now with the jar labeled “John” ⅓ full with extra counters. We asked each test
subject to cast their vote. When subjects were in groups, we gave the briefing
together, but kept each vote anonymous by asking those not immediately taking
part to turn around. Through this, we ensured each vote was genuine,
independent, and not affected by peer-pressure or additional bandwagon effect.
|
“John”
|
“Jeremy”
|
Control Group
|
5
|
7
|
Test Group
|
0
|
10
|
These results show that altruism bias is much
stronger than the bandwagon effect in this scenario, likely due to the heavy
altruistic framing. 100% of test subjects chose the jar with no counters in it,
showing a negative nudge from the ⅓ full jar. This was caused by a greater
perceived unfairness compared to when both jars were equal, as each vote
represented greater wellbeing from the same initial welfare.
Of course, no experiment is without its
limitations. These results are only relevant for PGS as there was no variance
in this aspect - meaning that the data are unlikely to be replicated exactly in
other scenarios. However, within our samples we incorporated a variety of ages,
genders, and cliques. Furthermore, there could be biases based on the names used
in the test. “John” or “Jeremy” could have emotional value for some subjects
(for instance, being the name of a family member) that would affect their
choices. However, I believe the increased humanity gained by using names within
the experiment led to a more realistic representation of the scenario, and the
data does not appear to have been skewed to a large extent. The main limitation
of this experiment was the small sample tested. Altruism bias is likely to
affect a smaller percentage of subjects’ behaviour if a larger sample is taken,
due to the fact it is unlikely that the bias would consistently change 100% of
behaviour. This calls for increased testing beyond our means as students (with
a lack of time and ability to travel) in order to find a more representative
result for both sample groups. Finally, it is true that the probability of
choosing “John” in the control group was not 0.5, however this is likely due to
the small sample size. Nevertheless, through statistical analysis, it can be
seen that the raw data is not significantly different from the expected result
and so it cannot be said that the true probability is not 0.5.
P = probability of
choosing “John”
H0:
p=0.5 H1: p≠0.5 α = 0.1 / 2 = 0.05 Actual Critical Range = x<2, x>9
X~B(12, 0.5)
Therefore, 5/12 is
not significant, thus the null hypothesis cannot be rejected. The result 5/12
is not within the critical range, meaning that it cannot be asserted to a
reasonable degree of certainty that the probability of choosing “John” over
“Jeremy” was not 0.5.
Overall, this project has shown that, within
the PGS community, altruism bias overrides the bandwagon effect when a
situation has an altruistic framing. Due to the limitations of our sample
groups, this may not be the case for other samples from different areas and
suggests that further testing should be undertaken. Furthermore, it is
important to compare this to real-life examples of similar situations to
evaluate this finding’s relevance. For example, we should look at how this
altruistic leaning affects supermarket counter voting systems when there are
varied causes and very personal attachments to different causes. A point to
consider in this is that: when the time taken to make the decision isn’t the
same, different skews may occur. For instance, as these supermarket charity
voting boxes are placed on the way out of the shop, consumers are moving faster
and will likely not stop to read the brief descriptions of each option.
Therefore, it is probable that the bandwagon effect is stronger there as public
opinion is the easiest information to comprehend. Following the proximity bias,
if perfect information is difficult to attain, consumers will revert to the
most obvious or prominent piece of information (which in this case is the
visually displayed public opinion). Nevertheless, the findings of this
experiment show that altruism bias is far stronger than the bandwagon effect
when a scenario is framed altruistically. So, our ingrained instincts to follow
the herd really can be overridden by perceived unfairness.
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