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ordinary bike were less interested in buying an e-bike.
Contrary to this, we found that those who were willing
to pay more for an ordinary bike were also willing to
pay more if they were to buy an e-bike, despite being
reluctant to purchase one in the first place. These slightly
con icting relationships have to be understood in light
of a particular Norwegian cycling culture, which is typical
for many other countries with low cycling levels as
well. Compared to countries with higher cycling shares,
Norway has a much larger proportion of training-oriented
and highly equipped cyclists (i.e. they tend to have a high
willingness to pay for sports equipment), who also tend
to be men, often denoted as lycra-cyclists due to their
outfits. or this large subgroup of the cycling population,
an e-bike is counter to their motivation for cycling, since
it does not provide such high intensity exercise. This
interpretation is supported by the fact that improved
fitness was the benefit from cycling that to the largest
extent divided the participants in these surveys. People
tended to either think of this as important or unimportant
for their decision about travel mode, and quite rarely
as of middle importance. Related to this, there were no
differences according to existing travel mode to work in
people s willingness to pay for an e-bike.
To learn about the e-bikes effect on mode share and
physical activity levels, a series of more controlled
interventions were carried out. The first was a trial where
61 participants were randomly selected from our larger
survey sample pool to try an e-bike for two or four weeks.
In the second intervention study, a sample of 45 people
responded to a questionnaire prior to buying an e-bike
and follow-up four weeks later. A further
people
(mainly physically inactive) were recruited through a
Norwegian N O. n both studies, we relied on self-report
measures to capture travel and physical activity levels.
The final intervention study was carried out as a multi-
method study with two main data collection procedures:
a survey and a measurement program with a mobile
app. The participants were ,
people in Oslo who had
received a subsidy to buy an e-bike. n all of these studies,
results from the intervention having access to an e-bike
were compared with a comparison group who did not
gain access to e-bikes.
In the surveys, a series of questions that captured bike
use and daily travel were asked. Based on these, we
could see if bicycle use had increased as a result of the
experiment and what transport modes it had replaced.
Since we had a control group without an e-bike, we could
also say with great certainty that the changes we found
were due to the e-bike.
Percentage who used the bike, %
Distance/ week, kilometers
Cycling as a share of all travelled kilometres, %
80
70
60
50
40
68
30
52
20
10
0
24
48
40.1
33.9
30
29.8
20
20
Before
20
After
Control group
28
Before
After
Test group
Figure 2 Bicycle use – as percentage who used the bike, distance per week and cycling
as a share of all travelled kilometres in the control group and the test group, before and
after the trial.
igure shows the results from our first trial. n the test
group, 30 percent of the participants had cycled on the
day before the experiment at the first data collection.
This percentage increased to
percent during the
trial when they had access to an e-bike . We also saw
that the number of kilometres covered on bicycle, as a
proportion of all kilometres travelled per day, increased
in the test group. In the comparison group, there were no
such changes in the same period.