Content uploaded by Ines Kawgan-Kagan
Author content
All content in this area was uploaded by Ines Kawgan-Kagan on Mar 11, 2016
Content may be subject to copyright.
Available via license: CC BY 4.0
Content may be subject to copyright.
ORIGINAL PAPER
Early adopters of carsharing with and without BEVs
with respect to gender preferences
Ines Kawgan-Kagan
1
Received: 2 January 2015 /Accepted: 22 September 2015 /Published online: 1 October 2015
#The Author(s) 2015. This article is published with open access at SpringerLink.com
Abstract
Purpose The majority of current e-carsharing users are
middle-aged men with a high education and high income; they
are most likely to have a full-time employment. Women are
consistently underrepresented in previous studies and there-
fore this paper focusses on characterization of female early
adopters. It builds a basis to identify current female early
adopters and understand their preferences in e-carsharing in
order to address women as target groups for e-carsharing.
Methods A sample of 492 carsharing subscribers from Berlin
is analysed according to socio-demographic backgrounds,
mode choice, use and evaluation of (e-) carsharing services.
Additionally, attitudinal indices and clusters based on mobility
related attitudes are analysed to reveal significant differences
between male and female users.
Results Generally, the results confirm socio-demographic
findings from previous literature about early adopters. Com-
paring females and males revealed differences in income, em-
ployment status and age. Female early adopters used battery
electric vehicles (BEVs) more often than vehicles with an
internal combustion engine and evaluate handling BEVs more
positive. They show a higher bike affinity and lower affinities
towards technology and innovation than male respondents.
They combine public transportation and bicycling with the
useof(e-)carsharingservicesasanadditionalpartofurban
mobility. Children do not seem to have an impact of the re-
spective topics, although the findings suggest that services are
not used with children.
Conclusions The analysis of carsharing schemes needs to fo-
cus on specific requirements of each trip (e.g. transporting or
accompanying children) in order to make sustainable mobility
an option for others than one ‘typical early adopter’.
Keywords Female early adopters .Carsharing .BEV .
Gender differences .E-mobility .Women .Mobility related
attitudes .Sustainable urban mobility
1 Introduction
Carsharing with battery electric vehicles (BEVs) can help re-
ducing urban space scarcity, local and global emissions and
noise exposure. However, operating a carsharing scheme with
electric vehicles is more expensive and offers users less au-
tonomy than carsharing powered by internal combustion en-
gines (ICEVs). Thus, carsharing operators need to identify
and address target groups for these mobility services. The
majority of electrical vehicles owners are urban or suburban
middle-aged men with high education and high income; they
usually live in a household that owns more than one car and
are most likely to have a full-time employment [1,2]. Socio-
demographic characteristics of early adopters of carsharing
are congruent with the identified characterisations of early
adopters of electrical vehicles. Carsharing subscribers are
mainly between the age of 35 and 45 years, with a higher
education and income [3–5]. International studies showed a
higher environmental awareness of both groups of early
This article is part of the Topical Collection on Driving Societal Changes
towards an Electro-mobility Future
Description:
This Paper is part of a multimethodological study to answer the question
on how women can be addressed as target groups for e-carsharing. It
builds a basis to identify current female early adopters and understand
their preferences in e-carsharing.
*Ines Kawgan-Kagan
ines.kawgan-kagan@tu-berlin.de
1
Institute of Land and Sea Transport, Technical University Berlin,
Berlin, Germany
Eur. Transp. Res. Rev. (2015) 7: 33
DOI 10.1007/s12544-015-0183-3
adopters. It becomes salient that women are consistently un-
derrepresented in previous studies and therefore special anal-
yses should give insights beyond the typical ‘early adopter’.
In general, adult women are more likely to head for multi-
ple destinations and their mobility includes more complex trip
chains due to their traditional social role, which involves re-
sponsibility for shopping and family errands [6–8]. These trips
usually are of shorter distances and, therefore, could be easily
covered by using e-carsharing services in urban areas. Women
show greater awareness of environmental issues [9] and have
a more positive attitude towards ecological measures like re-
ducing car use and using public transportation (PT) [10].
While taking greater household and family responsibilities,
women can be role models for the future generation and cre-
ating a shift towards sustainable mobility services since par-
ents have an impact on the travel behaviour of their children
[11]. However, exact requirements and preferences of women
have to be identified.
For the first time a sample collected within the BeMobility
2.0 project by the Innovation Center for Mobility and Societal
Change (InnoZ) containing carsharing and e-carsharing sub-
scribers from Berlin is analysed to get insights about female
early adopters presented in this paper. After presenting rele-
vant literature including findings about early adopters in gen-
eral and differences between women and men, a sample of
early adopters of carsharing with and without BEVs of Berlin
is analysed and set into a relation to the Berlin and were
possible the German population.
The findings are the first step in a multimethodological
study to answer the question on how women can be addressed
as target groups for e-carsharing. It builds a basis to identify
current female early adopters and understand their preferences
in carsharing with and without BEVs.
2 Characterisation of early adopters of carsharing
and BEVs
Analysing the characteristics of female early adopters of
carsharing with and without BEVs, as a first step, early
adopters in general have to be considered according to previ-
ous literature. Therefore, this section focusses on an overview
of the characterisations of early adopters of BEVs and of
carsharing according to previous studies. Important aspects
for the characterisation of female early adopters are drawn.
In order to characterise early adopters of carsharing with
and without BEVs, following previous findings of analyses of
carsharing subscribers and BEVowners is presented. Previous
international literature shows a high consistency of socio-
demographic characteristics for early adopters of BEVs. The
majority of BEV owners are middle-aged men with a high
education and high income [12]; they usually live in a house-
hold that owns more than one car [13] and are most likely to
have a full-time employment [1]. Additionally, BEV owners
and users are wealthy and keep multiple cars, whereas they
use the BEV as an addition to their private car. Most of the
BEV owners live in households with more children than the
average [2,14]. In terms of socio-demographics, international
surveys showed that potential owners of BEVs bear resem-
blance to actual owner characterisation: The majority are
middle-aged males with a high income and education, a high
eco-sensitivity and living in larger cities [15,16]. An analysis
of driving profiles from the large scale study ‘Mobilitaet in
Deutschland 2008’[17] in Germany shows, that for respon-
dents from larger cities owning an BEV would not be an
economic option due to the high initial costs [1]. The authors
conclude that people living in cities with less than 20,000
inhabitants could have the highest economic benefits of
BEVownership: Usually, urban profiles include too low driv-
ing frequencies and too short distances for the lower price of
propulsion to balance the total costs of ownership. Neverthe-
less, most of the BEVowners live in or near larger cities [18,
19]. This leads to the assumption that economic consider-
ations cannot be the only factor for purchasing a BEV. Thus,
other factors have to affect the purchase decision. The BEV
market segment shows a higher environmentally awareness
and technological affinity [20,27]. Most of the studies reveal
lifestyle [13] as well as technological and economic reasons as
important motivating factors owning a BEV [21]. Other stud-
ies contradict, naming interest in cutting-edge technologies as
the crucial factor and not environmental issues [19].
The socio-demographic background for early adopters of
carsharing is congruent with the identified characterisations of
early adopters of BEVs. Carsharing subscribers are mainly
male and between the age of 35 and 45 years, with a higher
education and income [4,5,22]. Referring to merely free
floating carsharing services, which presents a new mobility
service, more than half of the users are male and younger than
35 with a high share of full-time employment [5,23]. Addi-
tionally, in general carsharing subscribers have a higher in-
come [5,23], although Petersen found a lower income in his
sample from the early nineties [24]. Carsharing subscribers
mainly live in larger cities [3]. Most of the studies attest
carsharing subscribers a high affinity towards environmental
issues and a high affinity towards public transportation
[24–26].
Less consistent is the characterisation regarding attitudes
even for the respective early adopters: several studies identi-
fied lifestyle [13], technological affinity and economical
awareness as crucial factors influencing buying decisions
and the usage of carsharing services [20,21,27]. Neverthe-
less, there are contradicting results naming higher affinity to-
wards new technologies and not environmental awareness for
owners of BEVs [19]. Carsharing users show a higher affinity
towards public transportation [24–26]. In contrast, BEV
owners usually have more than one car in the household
33 Page 2 of 11 Eur.Transp.Res.Rev.(2015)7:33
[13]. The findings about differing attitudes indicate that there
is not only one type of early adopter of carsharing with BEVs
regarding attitudes. In 2015 Hinkeldein et al. [28] present an
attitude-based typology to cluster a representative sample into
six groups with different attitudinal profiles. There are mainly
two clusters with a high potential for using e-carsharing
schemes: ‘innovative technology-loving multioptionals’and
‘ecological PT- and bike-lovers’. Both clusters show a high
level of mobility related environment awareness, high affini-
ties regarding mobility services, public transportation (PT)
and long-distance train and regarding innovations. Differences
can be found concerning the joy of car driving, the general car
affinity and the affinity towards new technologies.
According to previous identified aspects, for a characteri-
sation of female early adopters the following aspects need to
be covered in the analysis:
&Socio-demographics (specifically place of resident, in-
come, education, age, number of children)
&Preferences regarding other modes of transport, usage and
evaluation of (e-) carsharing
&Attitudes relevant to mobility issues (especially environ-
mental awareness, affinity towards technology and
innovation)
Therefore, the following sections provide a solid back-
ground of the differences between women and men referring
to the recurrently identified characteristics of early adopters of
carsharing and BEVs.
3 Differences between women and men
Numerous studies have proved that differences in mobility
and transport behaviour between men and women are evident
for metropolitan areas [6], aggregated for Germany [7], the
USA [8,29] or Dutch Monocentric and Policentric Urban
Systems [30]. Mostly these differences result due to different
social roles –to different gender. Even in developed western
civilisations significant differences can be found comparing
characteristics and social roles of women and men. The fol-
lowing part gives an overview of differences according to
gender and sex of related topics (socio-demographic back-
grounds, traffic behaviour and mobility related attitudes). Be-
sides a general overview, a closer look at the Berlin Population
as a reference group for the used sample is presented where
possible.
3.1 Socio-demographic differences between women
and men
Although women in western societies prevalently participate
in the labour market as statistics show, additionally, they are
more likely to take over household responsibilities and take
care of children and relatives in need of care [31,32]. There-
fore, parenthood has a crucial impact on gender: although the
share of women without children working is almost as high as
for men, it significantly changes as soon as a child, especially
between 0 and 14 years, lives in the household [33]. Whereas
childrened women are more likely to have a part time position
when participating in labour market, men are more likely to
increase their workload when a child is present in the house-
hold. Generally, women show lower incomes. One of the rea-
sons is working part time; another is that women more often
working in lower paid fields and positions. Even when con-
sidering work time, respective positon and qualifications,
women earned 15 % less than men in 2011 in Berlin [33].
When it comes to education, in recent years the share of
female students in Germany increased to 49.5 % [33]. With
further academic education women are less represented to
the point of 8.6 % being female professors in Germany in
2003/04 [34]. Nevertheless, for the age category of under
30 years old Germans more women than men earned a
university degree including universities of applied sciences
[34]. For the group of people above this age men still have
a greater share.
3.2 Differences in mobility behaviour and preferences
Due to the additional responsibilities of taking care, more
women than men accompany children [35]. This leads to dif-
ferent traffic patterns. As mentioned before, a traffic gap has
been identified between men and women: whereas men are
more likely to travel further and have less destinations to cov-
er, women on an aggregation have more complex trip chains
with lower distances [7,8,36]. Especially in developed urban
areas, patterns of women’s traffic behaviour are similar across
international studies [6–8].Womentakecareofchildrenby
accompanying them when they have to go somewhere. In
addition, when living in a multiperson household, women
show a higher number of trips to run errands than the average
[7]. Related places are usually not far from home, therefore,
women show a complex radial net of trip chains over the day,
whereas for most of the male travellers the way to work and
back is an uninterrupted trip without (many) intermediate
stops [37].
In addition, there are differences between female and male
travellers already showing in early years in schools. Studies
revealed that already for the time being in school boys tend to
rather use individual traffic modes such as biking and driving
[38]. Female adults from Berlin use bikes and cars less and
public transportation more often than male adults [39]. Berlin,
with a well-established public transportation infrastructure,
takes on a leading position within Germany for the use of local
public transportation: more than a third uses busses and local
trains (almost) on a daily basis and only 13 % responded
Eur. Transp. Res. Rev. (2015) 7: 33 Page 3 of 11 33
(almost) never using those [39]. For the aggregated German
population biking and using local public transportation sys-
tems show hardly any differences according to sex, solely
women above 65 use local public transport system clearly
more often than men in Germany [17]. When being grown
up, women drive cars themselves less often than men [7]:
for 43 % of their trips women use the car compared to 58 %
of the trips of men, which is mainly due to a lower accessibil-
ity [40]. With an average of 11.5 km per trip, e-carsharing
services could provide a sustainable tool for urban mobility.
In 2008 the share of driver’s licenses in Germany falls in line
for both sexes with 29.2 % women and 30.3 % men. The
almost balanced ratio is due to women between 40 and 60
having a higher share of driver’s licenses and women between
18 and 39 and above 60 showing a smaller share than men
[40]. A huge gap is revealed when looking at the kilometres
travelled: German men cover with 1.103.7 million km trav-
elled by car a day almost twice of the distance of the total
kilometres travelled compared to German women with only
512.6 million km travelled by car per day. The mean distance
covered has been equal for women and men below the age of
29 and almost equal above 65 in 2008. In between, women
cover only 10 km each way on average and men 16 to 17 km
[40]. Parenthood and household responsibilities lead to wom-
en covering shorter distances since trips with a professional
purpose including the way to work are morethan twice as long
as journeys to escort others [40].
3.3 Differences in attitudes related to mobility issues
Studies covering attitudes according to sex showed differ-
ences for the adaption of technology and environmental is-
sues. Latter are not consistent though: In General, German
and European women are slightly more aware of environmen-
tal concerns then men [9,41,42]. Environmental awareness
expresses mostly on a local scale since women are more often
concerned about household related aspects, such as waste sep-
aration and healthy food [9,41]. Regarding rather global is-
sues, such as climate change, results vary for study to study.
Contradicting findings have been presented for the USA and
Europe: whereas women from the USA show slightly higher
concerns about climate change than men, in Europe it was
found to be vice versa [10,43]. Stern, Dietz [44]foundno
difference in the strengths of value orientation and therefore
respective actions, but women show stronger believes about
the consequences of environmental issues expressed in infor-
mation about particular consequences of environmental prob-
lems. They argue that there is no innate, biological difference
in value orientation but rather due to shared experiences.
These experiences differ between men and women and have
different cultural influences. Differences in the attitude to-
wards and use of technology are consistently showing a higher
technological affinity for men than women due to stereotypi-
cal and most important homemade experiences [45,46].
All these studies covering topics according to the identified
characteristics of early adopters show the importance of sex
expressing gender differences. Therefore, gender is central
theme for mobility behaviour research. To address these find-
ings, female early adopters will be analysed in contrast to male
early adopters and in contrast to the respective Berlin popula-
tion and the German average. Due to significant differences
for most of the important characteristics of early adopters (see
Section 2), female early adopters are expected to show signif-
icant differences for these characteristics as well.
4 Research design
In order to identify female early adopters and gain insights of
their socio-demographic backgrounds, the behavioural impact
of their attitudes and their evaluation of different aspects of
carsharing, customers of two main carsharing operators
(‘Flinkster’and ‘Multicity’)inBerlinwereaskedabouttheir
mode choices, experiences and preferences. ‘Flinkster’offers
round-trip carsharing services with vehicles with ICEVs and
BEVs; ‘Multicity’offers the more flexible free-floating ser-
vice with exclusively BEVs. The sample contains of 418 men
and 74 women, 492 in total. At the point of conduction, cus-
tomers can be considered as early adopters considering the
market diffusion of carsharing with and without BEVs. In
addition, it shows the same characteristics of early adopters,
whichhavebeenidentifiedinpreviousliterature.
Respondents were asked to fill out an online survey be-
tween July and September 2013. Besides socio-demographic
backgrounds, participants were asked about their behaviour
and preferences of their mode choice as well as of integrated
mobility services. Additionally, reasons for their choice of
using carsharing services, experiences with several aspects
of BEVs in carsharing, and their intention of using BEVs in
the near future were included in the questionnaire. 27 ques-
tions were asked to generate mobility related attitudes and
reconstruct the attitude-based typology [28]. Respondents
were asked to state their agreement on a 6-point Likert scale
(0 = I completely disagree, 5 = I completely agree) to specific
items such as ‘Environmental protection is crucial for me in
my choice of transportation.’The questionnaire contained
questions about the occupational status and number of chil-
dren in the household as well. Nevertheless, it was only pos-
sible to find out about the respondents’gender by concluding
from socio-demographic characterisations. Therefore, this
analysis focusses on the respondents’sex since the gap be-
tween female and male users is strongly visible. Where appli-
cable, differences for female and male respondents with and
without children are presented.
33 Page 4 of 11 Eur.Transp.Res.Rev.(2015)7:33
Since this paper aims for the effect of gender on e-
carsharing, the influence of this one variable is analysed on
all other variables and tested for significance. Therefore, all
results that are presented in this paper show significant differ-
ences between female and male early adopters of carsharing
with and without BEVs unless stated otherwise in the text. In a
first step, the differences in socio-demographic backgrounds
and characteristics of female early adopters to the Berlin pop-
ulation are being presented. Second, mode choice is being
compared in addition to the frequency of usage per month
and the usage within the past 12 month of different carsharing
operators. These findings are set in relation to the characteris-
tics of female Berliners and to the male early adopters and
male Berliners. Differences between early adopters of differ-
ent types of carsharing schemes can be seen in the presented
studies. Carsharing might be operated with BEVs, ICEVs or
offered as free-floating or as round-trip services. The question-
naire contained questions about various different operators.
Table 1lists the different carsharing operators and determines
their aspects.
In order to see differences in usage of different types of
carsharing, the stated usage was recoded into variables accord-
ing to the different service types. This way, differences be-
tween the usage of BEVs and ICEVs in carsharing schemes
and free-floating and round-trip services for women and men
can be analysed.
Furthermore, mobility related attitudinal variables were
analysed to identify differences between women and men. In
addition, the distribution of the clusters of mobility related
attitudes according to Hinkeldein et al. [28]ispresented.
The inconsistencies in previous studies about the attitudes
regarding sex differences indicate either that there is not a
specific sex more environmentally concerned than the other
or that there are significant cultural differences that need to be
taken into account. Additionally, different findings from data
about early adopters about their attitudes suggest that there is
not just one typical (e-) carsharing user. In order to compare
the distribution of the clusters, first a confirmatory factor anal-
ysis recreated the reduction of the dimensionality of the data
set to nine mobility related attitudes including reliability test-
ing. The attitudinal indices were generated by computing the
means of the variables loading on the respective factor. The
following Table 2gives an overview of the indices used in this
analysis. Second, the respondents were allocated to the gener-
ated clusters according to mobility related attitudes [28].
5Results
In order to identify female early adopters of carsharing and e-
carsharing, a German sample of 492 carsharing subscribers
from Berlin is analysed of which 74 are female early adopters.
This sample generally confirms socio-demographic findings
about early adopters as described before. The presentation of
the results is structured according to the identified character-
istics in Section 2. Although there is a relatively small share
covering 15 % of the sample –as usual for sample of early
adopters of carsharing and BEVs, insights about female early
adopters of carsharing with and without BEVs can be provid-
ed. First, the results of analysing socio-demographic back-
grounds are being presented. Second, preferences in mode
choice including a section about the use and evaluation of
the e-carsharing service are described. Finally, mobility relat-
ed attitudes and the clusters according to them are analysed.
5.1 Socio-demographic characteristics of female early
adopters
As a first step to understand female early adopters, their char-
acteristics are compared to those of males and the reference
group of the Berlin population and Germany as shown in the
following Table 3. In General, besides being male, the major-
ity of the sample is well-educated and full-time employed with
a high income. Differentiating between women and men, the
socio-demographic backgrounds remain homogenous except
for the average age, the employment status and the net house-
hold income per month. 50 % of the women are between 27
and 35 and accordingly 3.3 years younger on the aggregated
level than men.
Although the sample shows a higher share of full-time em-
ployment than found in Berlin, which is nearly equal for men
and women if no child lives in the household, the typical gap
occurs assoon as a child lives in the household, nearly aligning
with the share of the Berlin population. Childrened female
early adopters show, therefore, the same effects of parenthood
on the employment status as elsewhere in Berlin, Germany or
Europe. The levels of education are equal on the aggregated
level and are much higher than the German and Berlin average.
Tab l e 1 (E-) carsharing operators regarding types of services –
(included in questionnaire)
Operator Using BEVs Using
ICEVs
Free-floating
service
Round-trip
service
Cambio x x
Car2go x x
Citeecar x x
DriveNow x x
Flinkster x x
E-Flinkster x x
Greenwheels x x
Hertz on
demand
xx
Multicity x x
Stadtmobil x x
Eur. Transp. Res. Rev. (2015) 7: 33 Page 5 of 11 33
Interesting is the income gap, which is bigger than usual: a
third of the women have a net household income below 2000
Euro a month; whereas, only every fifth men receive less than
2000 Euro a month. This gap is bigger than the regular gap
found for the Berlin population. This can be explained with
carsharing offering a cheaper access to using a car when need-
ed instead of having to own a car. More than three quarter of
the women (77 %) in the sample do not have a car in the
household compared to less than a third of the men (64 %).
The number of children is different but not on a significant
level: the male share of the sample has 0.68 children on aver-
age, while the female share has 0.48. Splitting the data accord-
ing to two age categories of the children, it shows that the
difference lies within the group for children younger than
14 years: more than half of the women stated not having
children below 14 compared to a third of the men (Fig. 1).
Concluding from the employment status (men with children
are usually more often full-time employed than without chil-
dren and women are usually a lot more often part-time
employed with children than without), women reduce their
work time in order to take care of their child or children. This
effect leads to the assumption that using carsharing with and
without BEVs schemes is not as attractive to people taking
care of children –and this means usually women.
To sum it up, regarding socio-demographic backgrounds
there are significant differences regarding age, employment
Tabl e 2 Mobility related attitudes, indices generated from –(n= 492, Berlin)
Factor Item example (item loading most highly on the factor) No. of items
loading on
the factor
Cronbach’sα
Car affinity I find driving an easy way for getting around. 3 0.808
Bike affinity I find cycling an easy way for getting around. 3 0.923
PT affinity I reach my destination without stress when using public transport. 4 0.825
Long-distance train affinity I find using the train an easy way for getting around. 3 0.872
Mobility service affinity The use of mobility services allows me to reach all my important destinations. 3 0.869
Owning a car affinity I am dependent on my car in my daily life. 4 0.857
Mobility related environment affinity Environmental protection is crucial for me in my choice of transportation. 2 0.881
Technology affinity I am quickly able to figure out unknown electronic devices. 2 0.825
Innovator scale Other people often discover new travel ideas thanks to me. 3 0.870
Tabl e 3 Comparison of socio-demographic characteristics –(n= 492, Berlin)
Female Early
Adopters
Berlin
Male
Early Adopters
Berlin
Berlin N=492,
July/August 2013
Average
Berlin
(women/men)
Average
Germany
Sex Female 100 % −15.4 % 51.0 %
a
51.0 %
b
Age 17–24 8.9 % 4.3 % 4.3 % 8.7 %
a
9.8 %
b
25–39 58.9 % 51.9 % 50.8 % 22.4 %
a
21.3 %
b
40–49 17.9 % 25.5 % 26.9 % 16.2 %
a
19.9 %
b
50–64 14.3 % 14.7 % 14.6 % 19.2 %
a
24.3 %
b
65+ −3.5 % 3.4 % 19.9 %
a
24.6 %
b
Graduated from university
or technical college
66.7 % 66.7 % 66.7 % 19.5 %
a
(17.8 %/21.3 %)
15.1 %
b
Full-time employed Total 62.3 % 79.2 % 76.6 % 64.8 %
a
(57.6 %/71.1 %)
62.3 %
c
Without children 76.9 % 78.3 % 78.0 % 66.7 %
a
(62.6 %/70.1 %)
−
With children 53.8 % 84.2 % 80.7 % 61.4 %
a
(49.8 %/73.0 %)
−
Net household income
per month
<2000€36.2 % 20.3 % 22.6 % 48.1 %
a
(49.7 %/46.4 %)
50.1 %
a
a
Average Germany/Berlin data from [47]
b
Average Germany data from [48]
c
Average Germany data from [17]
33 Page 6 of 11 Eur.Transp.Res.Rev.(2015)7:33
status and income between female and male early adopters of
carsharing with and without BEVs: female early adopters are
younger, less often full-time employed when children live in
the household and show a lower income than male early
adopters, although latter is still higher than the average of
female Berliners. Women of this sample are more often full-
time employed than on an average, especially when they do
not have children in the household. As expected, having a
child shows a big effect on the status of employment: female
early adopters with children work less often full-time. The
number of children is smaller for women than for men, where-
as no comparable data for Germany or Berlin is available. This
aspect and the effect of having children in the household on
the employment status suggest that carsharing is rather attrac-
tive to people not being in charge of taking care of their
children.
5.2 Differences in mode choice and use of carsharing
with and without BEVs
This part provides insights about different aspects regarding
mode choice and the use and evaluation of e-carsharing ser-
vices. Female early adopters show different preferences in
mode choice compared to men: they are using bikes with
80 % at least once a week compared to men with 62 %. Cars
including BEVs and rented cars are not used as often by wom-
en as by men. Women do not show a higher usage of public
transportation as it has been identified in other international
studies before and described in Section 3.2. Regarding the use
of free floating carsharing with BEVs, 10 % of the women use
this service for professional reasons compared to 24 % of the
men. When cleaning according to employment status, the dif-
ference remains. This could be explained with different work
tasks for women and men, which were not asked for in the
survey. Additionally, more than half of the women almost
never or less than once a month use a car driving themselves
(53 %) compared to a third of the men (37 %).
Comparing the use of different carsharing service opera-
tors, differences between women and men occur mostly
checking for the average frequency of use per month generat-
ed out of the past 12 months. As Table 4shows, for most of the
service operators, men have used carsharing services more
often. Only regarding the use of ‘Multicity’the average num-
ber of uses is almost equal for both groups of early adopters.
For one of the main service operators ‘Flinkster’, there is a
much higher share of men using this service: almost half of the
men used ‘Flinkster’at least once within the past 12 months
compared to a quarter of the women. ‘Flinkster’is a station
based carsharing service operator with vehicles with an inter-
nal combustion engine. Other operators namely ‘Citeecar’,
‘Greenwheels’,‘Hertz on demand’,‘Cambio’,‘Stadtmobil’
and others do not play a role for the female users of this
sample. 14.5 % of the male respondents used others though.
On average, respondents had 2.2 memberships. Women show
a significantly smaller number of memberships with 1.8 com-
pared to men with 2.4.
Additionally, women showshorter membership periods for
all operators than men. Nevertheless, a slightly higher share of
the women who used ‘Multicity’within the past 12 months
can be found. ‘Multicity’offers only one model of BEV
(Citroen C-Zero). The higher share of female early adopters
using the service of ‘Multicity’can be explained by the fact
that women prefer using one type of car when using
carsharing: 73 % of the women agreed, whereas 52 % of the
35.3%
56.5%
90.2%
86.7%
36.0%
26.1%
8.6%
10.0%
23.7%
17.4%
1.2%
3.3%
5.0%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
male
female
male
female
Children <14 Children 14-18
none 1 2 3 and more
Fig. 1 Respondents with and without children –(n=492,Berlin)
Tab l e 4 Use of different (e-) carsharing operators of members of
‘Flinkster’and ‘Multicity’– (n= 492, Berlin)
Carsharing
service
operator
Mean
frequency
used per
month
Female
Mean
frequency
used per
month
Male
Used
within past
12 month
Female
Used
within past
12 month
Male
Total 4.5 5.8 95.2 % 91.3 %
Multicity 2.2 2.1 65.2 % 65.0 %
DriveNow 2.5 2.8 40.6 % 50.6 %
Car2go 1.9 2.1 33.3 % 50.4 %
Flinkster 0.4 0.9 24.6 % 46.3 %
E-Flinkster 0.4 0.4 23.2 % 29.1 %
Other
Operators
0.0 0.7 2.9 % 14.5 %
Eur. Transp. Res. Rev. (2015) 7: 33 Page 7 of 11 33
men prefer always using the same type of car. Therefore, it can
be argued that female early adopters do not use carsharing
services because of trying different models as much as men
do, but rather because of having to run errands that are difficult
to realize by other modes of transport, especially by bike.
Always using the same car model provides a higher potential
of routinizing the use of carsharing. After ‘Multicity’,
‘DriveNow’shows the highest rates of usage although a gap
for both the frequency of use and share of users can be iden-
tified comparing women and men. At this point, the reader
needs to bear in mind that the sample consists of members of
‘Flinkster’and ‘Multicity’and, therefore, the order of the
operators is not representing early adopters in general. Never-
theless, the ratio of women and men using the servicesreveals
that women show a higher affinity towards BEVs. Since ‘Mul-
ticity’is the only operator using only one model of BEV, it
achieves the highest share of female users and frequency of
use per month. Women in the sample agreed significantly less
with statements like ‘a car in the household is part of their life’
and that ‘their car is needed for staying in contact with friends’
compared to men. This leads to the conclusion that owning a
car is even less important to female early adopters than for
males. Another difference can be found in the evaluation of
handling of charging the battery and handling the charging
station: more than half of the women experienced the battery
charging as very positive compared to a third of the men.
Using the charging station, 40 % of the women stated a very
positive handling experience, whereas not even 20 % of the
men stated the same.
Splitting the different operators according to their specific
characteristics as determined in Table 1, almost 80 % of the
females have used BEVs compared to 65 % having used
ICEVs within the past 12 month (Fig. 2). For the male respon-
dents the share having used ICEVs is slightly bigger than the
one for BEVs. The difference of the use of ICEVs is highly
significant. This clearly states that women using carsharing
show a higher tendency to use BEVs instead of ICEVs. Com-
paring free-floating to round-trip (e-) carsharing schemes, lat-
ter shows another significant gap between women and men:
whereas a bit more than a third of the females used round-trip
services, almost 60 % used them.
Since the usage rates are generally smaller for women, the
fact that operators with BEVs (free-floating and round-trip
services) show a higher share of women using the services
than the services with ICEVs, it can be argued that female
carsharing subscribers show a higher potential for the use of
BEVs instead of ICEVs. Significantly more women than men
(76/63 % agreed) reporting that they have found a vehicle
whenever they needed one and describing the business area
as big enough for their daily trips (64/50 %), supports the
argument of women’s traffic patterns being optimal for urban
e-carsharing schemes. Men and women report almost equally
about the intention of using e-carsharing services in the near
future: 88 % of the men intend to use electric vehicles through
sharing schemes on a regular basis compared to 85 % of the
women.
Having children in the household does not lead to signifi-
cant differences between women and men regarding the pre-
sented variables of usage. This suggests that using these ser-
vices takes place mainly without children. Therefore, no effect
of the variables can be seen.
5.3 Differences in mobility related attitudes
At this point attitudinal variables are used to compare men and
women in order to get insights about female early adopters.
Nine indices were computed using 27 attitudinal variables as
described in Section 4. The sample shows a high affinity for
new mobility services and bike affinity. Although there is a
high car affinity across the sample, male and female early
adopters show a very low preference for owning a car.
Comparing the indices regarding attitudinal parameters,
three main differences can be identified between women and
men: as seen before, female early adopters use bikes more
often compared to men. This characteristic is confirmed by a
higher affinity towards riding bikes. Additionally, differences
regarding affinity towards technologies and the attitude
57.9%
34.8%
79.8%
75.4%
82.9%
65.2%
79.0%
79.7%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90%
male
female
BEV ICEV Free-floang Round-trip
Fig. 2 Differences in (e-) carsharing usage between women and men –(n= 492, Berlin)
33 Page 8 of 11 Eur.Transp.Res.Rev.(2015)7:33
towards innovations can be seen. Table 5shows the means of
the indices comparing women and men.
Grouping the sample according to the clusters usedaccord-
ingtoHinkeldeinetal.[28], the overall sample is dominated
by ‘innovative technology-loving multioptionals’and ‘eco-
logical PT-and –bike lovers’as shown in Fig. 3. The two
groups can be characterised with a high mobility related envi-
ronment awareness, mobility service affinity, PT affinity,
long-distance train affinity and innovator scale. Differences
can be found regarding the joy of car driving and general car
affinity and the affinity towards new technologies. This sup-
ports the assumption that female carsharing subscribers use
the services not to test different car models, but rather as an
additional multimodal part of urban mobility.
Although there is neither an identified significant differ-
ence in the attitude regarding affinity towards local public
transportation, nor a difference in the usage of it between
men and women, the distribution of mobility types across
the sample shows a greater share of female ‘ecological PT-
and –bike lovers’comparedto male early adopters. More than
half of the male sample can be allocated to the group of ‘in-
novative technology-loving multioptionals’and a third to
‘ecological PT-and –bike lovers’. The shares of the two groups
for women are nearly equal with 44 % each. This allocation is
consistent with the findings of Hinkeldein et al. [28], where
two thirds of the cluster ‘innovative technology-loving
multioptionals’and a bit than half of the cluster ‘ecological
PT-and –bike lovers’are male. The cluster of ‘flexible car-
lovers’shows a high affinity towards driving and testing cars.
Nevertheless, they do not generally reject other modes of
transport. Although for both sexes the share of ‘flexible car-
lovers’is about 9 to 10 %, the previously identified differences
have to lie within the two remaining clusters (‘innovative
technology-loving multioptionals’and ‘urban oriented PT-
lovers’).
The differences in the attitudes and distribution of the clus-
ters according to mobility related attitudes indicate that early
adopters show a high ecological awareness and have a high
affinity towards public and individual traffic. Nevertheless,
clusters that clearly prefer PT and show a high environmental
awareness (‘urban oriented PT-lovers’)aswellasclustersthat
show a higher affinity towards cars (‘traditional car-lovers’)o
r
bikes (‘conventional bike-lovers’) are hardly represented in
the sample of early adopter. For the biggest clusters of the
sample driving oneself either by car or by bike in combination
with public transport is an important criterion. For the women
of the sample the individualtraffic is mostly by bicycle; for the
men it stands for car usage. Clearly, the more sustainable way
of transport is by bicycle. Therefore, female early adopters
show higher environmental friendly traffic behaviour than
male, although the attitude towards ecological issues does
not show differences between these two groups. If women
used carsharing, they rather used locally environmental
friendly battery electric vehicles in carsharing than men.
Tabl e 5 Mobility related attitudes –(n=492,Berlin)
Factor Female early
adopters
Male early
adopters
Car affinity 3.2 3.2
Bike affinity** 4.0 3.6
PT affinity 3.5 3.5
Long-distance train affinity 3.1 3.2
Mobility service affinity 3.9 3.9
Owning a car affinity 0.9 1.3
Mobility related environment affinity 3.3 3.2
Technology affinity** 2.7 3.7
Innovator scale* 2.9 3.2
**p<0.005;*p<0.05
Women Men
Fig. 3 Distribution of clusters according to mobility related attitudes –(n= 492, Berlin)
Eur. Transp. Res. Rev. (2015) 7: 33 Page 9 of 11 33
Although the sample does not show great differences in the
attitude towards mobility related environmental issues, 60 %
of the women agreed completely on the statement of BEVs
being environmentally friendly, compared to men with 43 %.
This indicates that’s women are not as sceptical about the
environmentally effects of BEVs.
6 Conclusion
In order to generate a shift towards sustainable mobility, the
needs of potential customers have to be identified. The focus
on male early adopters has to be overcome and other groups of
potential customers need to be addressed. For the first time a
sample of early adopters was analysed with a special focus on
female early adopters. Besides socio-demographic character-
istics, mode choice including the evaluation of e-carsharing
and mobility related attitudes were included in the analysis.
Although the sample does not contain a high share of women,
it was possible to gain insights out of the subsample size of 74
female early adopters.
Comparing female and male carsharers revealed significant
differences in socio-demographics, especially in age, income
and full-time employment status when children live in the
household. The accessibility to driving a car when needed,
which carsharing services offer, helps overcoming the income
gap. The business areas of carsharing operators fit women’s
urban traffic patterns since they usually cover shorter dis-
tances compared to men. As shown, female early adopters
show a high potential for using BEVs in carsharing services.
If women use free-floating carsharing services, they are more
likely to choose operators offering BEVs. This hypothesis is
supported by the fact that women prefer one type of car in-
stead of trying different models. Female early adopters use
bikes more often and ICEVs and BEVs less often compared
to men. The analyses of mode choice, the use and evaluation
of e-carsharing as well as the attitudinal variables suggests that
female early adopters tend to use carsharing services in the
original meaning as an additional part for urban mobility and
not for testing car models as much as men do. In addition, it
was possible to show that it is important to address different
types of carsharing services to respective potential customers.
In general, children significantly change the traffic patterns
of women. At this point the influence of children remains un-
clear since no differences can be found between men and wom-
en with and without children in this sample. It is suspected that
the services do not offer an adequate solution to accompany
children. In order to address more women as potential cus-
tomers, this effect needs to be addressed in further research.
Qualitative interviews will provide a deeper understanding of
the obstacles of using round-trip and free-floating carsharing
services that other potential customer groups than the known
early adopters might face when covering complex trip chains.
All these findings are preliminary. Nevertheless, they show
that carsharing operators need to discover the potential of
women as customers to provide a more sustainable urban mo-
bility culture. These findings need to be confirmed by
analysing more samples according to sex or gender. It is nec-
essary to analyse not merely a single group of potential cus-
tomers or simply one market segment. It is of crucial impor-
tance for understanding transportation, since gender continues
to play an important role explaining traffic behaviour [3]. In
addition, the differentiation of carsharing with and without
BEVs schemes showed that the services cover different as-
pects that need further attention. Comparing the findings of
this study to a representative sample will shed light on the
difference of the behavioural impact of mobility related atti-
tudes and can help understanding the requirements of women
in order to support the use of carsharing.
Acknowledgments The analysis presented in this paper is kindly sup-
ported by InnoZ –Innovation Centre for Mobility and Societal Change,
Germany by providing the data of the research project ‘BeMobility 2.0’
funded by German Federal Ministry of Transport, Building and Urban
Development (BMVBS).
Open Access This article is distributed under the terms of the Creative
Commons Attribution 4.0 International License (http://
creativecommons.org/licenses/by/4.0/), which permits unrestricted use,
distribution, and reproduction in any medium, provided you give appro-
priate credit to the original author(s) and the source, provide a link to the
Creative Commons license, and indicate if changes were made.
References
1. Globisch J et al. (2013) Early adopter unter der Lupe. Elektroautos -
wer ist jetzt schon e-mobil und wer kann sich vorstellen, eines zu
kaufen? Int Verkehrswesen 65(2):46–49
2. Hjorthol R (2013) Attitudes, ownership and use of electric vehi-
cles–a review of literature.National Academy of Sciences
3. Burkhardt JE, Millard-Ball A (2006) Who is attracted to carsharing?
Transp Res Rec: J Transp Res Board 1986:98–105
4. Lane C (2005) PhillyCarShare: first-year social and mobility im-
pacts of carsharing in Philadelphia, Pennsylvania. Transp Res Rec:
J Transp Res Board 1927:158–166
5. Stillwater T, Mokhtarian P, Shaheen S (2009) Carsharing and the
built environment. Transp Res Rec: J Transp Res Board 2110:27–34
6. Gordon P, Kumar A, Richardson HW (1989) Gender differences in
metropolitan travel behaviour. Reg Stud 23(6):499–510
7. Nobis C, B. Lenz (2005) Gender differences in travel patterns.
Research on Women’s Issues in Transportation, p. 114.
8. Rosenbloom S (2000) Trends in women’s travel patterns.in
Women’s Travel Issues Second National Conference
9. Umweltbewusstsein in Deutschland,Ergebnisse einer repräsentativen
Bevölerungsumfrage. 2012, Umweltbundesamt: Berlin, Marburg.
10. Special Eurobarometer 313:Europeans’attitudes towards climate
change. 2009, European Commission, European Parliament
11. Halden D (2003) Children’s attitudes to sustainable transport
12. Trommer S, J Jarass, V Kolarova (2015) EarlyadoptersofEVsin
Germany unveiled - Results of a study among private users of EVs
in Germany.in28th International Electric Vehicle Symposium and
33 Page 10 of 11 Eur.Transp.Res.Rev.(2015)7:33
Exhibition. Deutsches Zentrum für Luft- und Raumfahrt (DLR),
Kintex
13. Peters A, J Hoffmann (2011) Nutzerakzeptanz von Elektromobilität.
Eine empirische Studie zu attraktiven Nutzungsvarianten,
Fahrzeugkonzepten und Geschäftsmodellen aus Sicht potenzieller
Nutzer.Karlsruhep34.
14. Saarenpää J, Kolehmainen M, Niska H (2013) Geodemographic
analysis and estimation of early plug-in hybrid electric vehicle
adoption. Appl Energy 107:456–464
15. Erdem C, Şentürk İ,Şimşek T (2010) Identifying the factors affect-
ing the willingness to pay for fuel-efficient vehicles in Turkey: a
case of hybrids. Energ Policy 38(6):3038–3043
16. Hanappi T et al. (2012) Elektromobilität in Österreich.
Determinanten für die Kaufentscheidung von alternativ
betriebenen Fahrzeugen:Ein diskretes Entscheidungsexperiment.
Umweltbundesamt: Wien.
17. Mobilitaet in Deutschland 2008 - Ergebnisbericht. Struktur -
Aufkommen - Emissionen - Trends. 2010, Bundesministerium für
Verkehr Bau und Stadtentwicklung, Institut für angewandte
Sozialwissenschaft (infas), Deutsches Zentrum für Luft- und
Raumfahrt (DLR) Bonn, Berlin.
18. Hackbarth A, Madlener R (2013) Consumer preferences for alter-
native fuel vehicles: a discrete choice analysis. Transp Res Part D:
Transp Environ 25:5–17
19. Pierre M, Jemelin C, Louvet N (2011) Driving an electric vehicle. A
sociological analysis on pioneer users. Energ Effic 4(4):511–522
20. Jensen AF, Cherchi E, Mabit SL (2013) On the stability of prefer-
ences and attitudes before and after experiencing an electric vehicle.
Transp Res Part D: Transp Environ 25:24–32
21. Tran M et al. (2013) Simulating early adoption of alternative fuel
vehicles for sustainability. Technol Forecast Soc Chang 80(5):865–
875
22. Firnkorn J (2012) Triangulation of two methods measuring the
impacts of a free-floating carsharing system in Germany. Transp
Res A Policy Pract 46(10):1654–1672
23. Firnkorn J, Müller M (2011) What will be the environmental effects
of new free-floating car-sharing systems? The case of car2go in
Ulm. Ecol Econ 70(8):1519–1528
24. Petersen M (1995) Ökonomische Analyse des Car-Sharing.
Wiesbaden.
25. Costain C, Ardron C, Habib KN (2012) Synopsis of users’behav-
iour of a carsharing program: A case study in Toronto. Transp Res
A Policy Pract 46(3):421–434
26. Efthymiou D, Antoniou C, Waddell P (2013) Factors affecting the
adoption of vehicle sharing systems by young drivers. Transp
Policy 29:64–73
27. Schuitema G et al. (2013) The role of instrumental, hedonic and
symbolic attributes in the intention to adopt electric vehicles.
Transp Res A Policy Pract 48:39–49
28. Hinkeldein D et al. Who Would Use Integrated Sustainable Mobility
Services –And Why?, in Sustainable Urban Transport.p.177–203.
29. Crane R (2007) Is there a quiet revolution in women's travel?
Revisiting the gender gap in commuting. J Am Plan Assoc 73(3):
298–316
30. Schwanen T, Dieleman FM, Dijst M (2001) Travel behaviour in
Dutch monocentric and policentric urban systems. J Transp Geogr
9(3):173–186
31. Dribe M, Stanfors M (2009) Does parenthood strengthen a tradi-
tional household division of labor? Evidence from Sweden, national
council on family relations. J Marriage Fam 71(1):33–45
32. Schneebaum A, K Mader (2013) The gendered nature of intra-
household decision making in and across Europe, in Department
of Economics Working Paper Series, W.V.U.o.E.a. Business,
Editor: Vienna
33. Gender Datenreport Berlin 2012,inBerlin Senate Department for
Integration,Labour and Social Issues (BSDILS). 2012, Amt für
Statistik Berlin-Brandenburg.
34. Datenreport zur Gleichstellung von Frauen und Männern in der
Bundesrepublik Deutschland,inGender-Datenreport. 2005,
Deutsches Jugendinstitut, Statistisches Bundesamt: München.
35. Turner T, Niemeier D (1997) Travel to work and household respon-
sibility: new evidence. Transportation 24(4):397–419
36. Bauhardt C (1999) Bürgersteige und Straßenbahnen für die Frauen –
den Männern ICE und Transrapid? In: Collmer S, Döge P, Fenner B
(eds) Technik, Politik, Geschlecht. Kleine Verlag, Bielefeld
37. VCÖ, Gender Gap im Verkehrs- und Mobilitätsbereich,
Hintergrundbericht. 2009, VCÖ –Verkehrsclub Österreich Wien.
38. Richter B (2009) Das Verkehrsverhalten von deutschen und
schweizerischen Jugendlichen im Vergleich. mobilogisch.
Zeitschrift für Ökologie, Politik & Bewegung, 3/10: p. 40–43.
39. Mobilität in Städten –SrV 2008: Sample Berlin. Analysis by TU
Dresden/VIP. 2008, Senate department for urban development and
the environment Berlin, Department Traffic: Berlin.
40. Stiewe M, L. Krause (2012) Geschlechterverhältnisse und
Mobilität–Welchen Beitrag leisten Mobilitätserhebungen?
Schwechat
41. Mohai P (1992) Men, women, and the environment: an examina-
tion of the gender gap in environmental concern and activism. Soc
Nat Resour 5(1):1–19
42. Schahn J, Holzer E (1990) Studies of individual environmental
concern: the role of knowledge, gender, and background variables.
Environ Behav 22(6):767–786
43. McCright AM (2010) The effects of gender on climate change
knowledge and concern in the American public. Popul Environ
32(1):66–87
44. Stern PC, Dietz T, Kalof L (1993) Value orientations, gender, and
environmental concern. Environ Behav 25(5):322–348
45. Harris TA, Gale MT, Colley AM (1994) Effects of gender role
identity and experience on computer attitude components. J Educ
Comput Res 10(2):129–137
46. Venkatesh V, Morris MG, Ackerman PL (2000) A longitudinal field
investigation of gender differences in individual technology adop-
tion decision-making processes. Organ Behav Hum Decis Process
83(1):33–60
47. Mikrozensus 2012. 2012, Amt für Statistik Berlin-Brandenburg:
Berlin.
48. Zensus 2011. 2014, Statistische Ämter des Bundes und der Länder,
Wiesbaden
Eur. Transp. Res. Rev. (2015) 7: 33 Page 11 of 11 33