how to trigger mass-market adoption for electric - EEG, TU-Wien

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how to trigger mass-market adoption for electric - EEG, TU-Wien
HOW TO TRIGGER MASS-MARKET ADOPTION
FOR ELECTRIC VEHICLES? - AN ANALYSIS OF
POTENTIAL ELECTRIC VEHICLE DRIVERS IN
AUSTRIA
By Alfons Prießner; Robert Sposato; Nina Hampl
Department for Sustainable Energy Management
Institute for Operations, Energy, and Environmental Management (OEE)
Alpen-Adria University Klagenfurt
15 February 2017, IEWT 2017 - Vienna
Who owns an Electric Vehicle (EV) or plans to purchase one as his/her
next car?
Last Modified 15.02.2017 14:36 W. Europe Standard Time
17% of the car
owners plan to purchase
an EV as their next car
(Early Adopters)
second
Printed
Every
car driver can imagine to
purchase an EV (Early &
Potential Adopters)
But who are these early and potential adopters?
SOURCE: Website Tesla & Toyota; Umfrage WU Wien, Deloitte & Wien Energie Nov 2016 Österreich (n=1000)
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Current literature and research questions
Current
Literature
 Prior work has shown that certain socio-demographic, socio-psychological
as well as contextual differences (Axsen et al., 2016; Peters & Dütschke,
2014; Tal & Nicolas, 2013; Nayum & Klöckner, 2014; Nayum et al., 2016)
distinguish between actual EV owners and potential EV adopters currently
using ICE vehicles
Research
Question
SOURCE: Prießner, Sposato & Hampl 2017
Printed
 Our study, in addition, hypothesizes that respondents with certain cultural
worldviews, i.e., “a general perspective from which a person sees and
interprets the world” (Cherry, García, Kallbekken, & Torvanger, 2014: 563),
will be more likely to adopt clean technology vehicles such as EVs.
.
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 Despite the high need of stakeholders, such as car manufacturers or utility
companies, to learn more about potential adopters in order to make EVs
suitable for the mass market (Wesche et al., 2016) up to now, only a
narrow stream in literature has studied potential EV adopter segments
(Axsen et al., 2016; Nayum & Klöckner, 2014 Peters & Dütschke, 2014;
Wesche, Plötz, & Dütschke, 2016).
1) What are predictors for EV-adoption?
2) How do potential adopter segments differ?
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Based on existing literature hypothesis on the effect of socio-demographic,
socio-psychological, worldviews and EV incentives were derived
Variable
Hypothese effect on
Reference
EV-adoption
Plötz et al., 2014
Income
Axsen et al., 2016; Nayum et al., 2016; Plötz et al., 2014;
Tal & Nicolas, 2013; Carley, Krause, Lane, & Graham,
2013)
Age
(Hidrue, Parsons, Kempton, & Gardner, 2011; Nayum et
al., 2016; Plötz et al., 2014
Education
Nayum et al., 2016; Plötz et al., 2014; Tal & Nicolas, 2013
Dwelling density
Plötz et al., 2014)
# of people per household
Nayum et al., 2016
# of cars per household
Klöckner, Nayum, & Mehmetoglu, 2013; Nayum et al.,
2016; Peters & Dütschke, 2014; Tal & Nicholas, 2013
Pro-Environmental
(a=.90)
Carley et al., 2013; Hidrue et al., 2011; Wolf & Seebauer,
2014; Axsen et al., 2016)
Pro-Technological
(a=.80)
(Axsen et al., 2016, Wolf & Seebauer, 2014). Egbue and
Long (2012)
H3:
Worldviews
Individualism (a=.55)
Cherry et al. (2014); Kahan et al., 2012
Hierarchical (a=.50)
Cherry et al. (2014); Kahan et al., 2012
H4:
Context: EV
incentives
EV incentive sub-region
(e.g., Langbroek, Franklin, & Susilo, 2016; Mannberg,
Jansson, Pettersson, Brännlund, & Lindgren, 2014;
Sierzchula et al., 2014
H1: Sociodemographic
H2: Sociopsychological
SOURCE: Prießner, Sposato & Hampl 2017
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Gender (to be male)
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Category
Methods: We conducted a nationally representative online survey and used
a multi-nominal logistic regression and non-hierarchical cluster analysis
Survey
Participants
Descriptive
 A nationally representative online survey in Austria was conducted in
autumn 2016 (n=1.000).
 The data was collected by an external market research company
 A subsection of the questionnaire focused on participants’ attitudes
towards EVs, their willingness to invest and related policy incentives
Sample
Population
 Gender (share women):
51%
vs.
51%
 Income (EUR)
2,711
vs.
2,769
 Federal Distribution & Age
Methodology


 We applied a multinomial logistic regression to examine whether
the socio-demographic, socio-psychological (including cultural
worldviews) and contextual characteristics (i.e. policy incentives)
have an influence on the willingness to purchase EVs based
 By applying a non-hierarchical cluster analysis, we aim to shed
some light on characteristics of potential adopter segments and
their preferences for policy incentives
SOURCE: Prießner, Sposato & Hampl 2017
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 Education

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Survey
Details
Early Adopters and Potential Adopters of EVs make already up to almost
50% (i.e. every second car driver can imagine purchasing an EV)
100
51
32
Early
Potential NonTotal
Adotpers Adopters Adopters
Early Adopters (17%):
 Already purchased an EV1 or intend to buy an EV
as their next car.
 Considering an average holding period of a car in
central Europe of 5-6 years they are likely to be
EV drivers within the next 5-10 years.
Potential Adopters (32%)
 Stated an interest in purchasing an EV, but not as
their next car
 most likely to buy an EV in the next 10-15 years.
Non-adopters (51%):
 A little more than 50% of the respondents prefer a
car with an internal combustion engine to an
electric car and, at least at the time of our survey,
have no intention to purchase an EV
 In order to inspire interest in EVs among these
buyers, substantial developments with regard to
policy, technology, costs or cultural norms would
need to take place (Axsen et al., 2016).
1: Sample identified ten people as current EV and hybrid electric vehicle drivers out of a 1,000, which is equivalent to the Austria current EV market
share of approx. 0.1% ( Austria Tech (2015)). This in line with other countries e.g., Germany or Italy but lacking behind the leaders such as Norway
(23%) or Netherlands (10%) (IEA, 2016a).
SOURCE: Prießner, Sposato & Hampl 2017
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17
Last Modified 15.02.2017 14:36 W. Europe Standard Time
Adopter Segments EV AUT Autumn 2016
(%)
Rejected
H1: Sociodemographic
H3: Worldviews
H4: Context:
EV incentives
Constant
5.645 (0.936)
1.770 (0.968)
Age
1.004 (0.007)
1.000 (0.008)
Education
0.904 (0.113)
0.981 (0.116)
Household-size
1.041 (0.098)
1.272† (0.099)
Income
1.040 (0.032)
1.050 (0.023)
Gender (male)
0.644 (0.202)
0.684 (0.208)
Exp(B) Potential- Hypothese effect on Hypothese:
early EV-adoption
Evaluation
adopters 1,2
Gender (female)
Dwelling density: Municipal=1
Dwelling density: town=2
Dwelling density: City=3
# of cars per household=0
# of cars per household=1
1.505 (0.304)
1.113 (0.231)
1.132 (0.311)
0.839 (0.240)
0.376** (0.328)
1.039 (0.241)
0.524† (0.332)
0.740 (0.248)
# of cars per household =2
Pro-technological attitude
0.700* (0.175)
0.898 (0.182)
Pro-environment attitude
0.352*** (0.186)
0.742 (0.192)
Individualistic Worldview
1.506*** (0.096)
1.313** (0.097)
Egalitarian Worldview
EV incentives = No
EV incentives = Yes
0.735** (0.104)
1.220 (0.235)
0.845† (0.108)
1.628* (0.242)
1 Standard errors in parentheses
2 EV adopters as reference. Note: † p < 0.10; * p < 0.05; ** p < 0.01; *** p < 0.001.
SOURCE: Prießner, Sposato & Hampl 2017
Partially accpeted
Printed
H2: Sociopsychological
Dependent variable = WTI
Exp(B) Nonadopters 1,2
Accepted
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Findings indicate that socio-psychological (incl. worldviews) in contrary to
socio-demographic factors play a significant role in explaining differences
between segments of potential adopters and non-adopters
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4 Potential Adopter segments were identified for the next wave of adoption
NonPurchase
Motives2
3 Undiscerning
Urbanites
(16%)
2 The Undecided
(28%)
4 EV Supporters
(32%)
Low
High
Purchase Motives1
3
Tend to be younger and more
educated and live in an urban area,
high pro-environmental attitude
 No real preference for incentives
at all
4 Tend to be a male, older and
environmentally conscious car driver,
who shows high pro-environmental
attitude
 Decent high preference for
purchase- and user-based
incentives, similar to early
adopters
1 Factors General EV Motives ((Low TOC, Less Co2 emissions, etc.) & Technological Motives (Charm of new technology, no noise, etc.)
2 Factors Structural Barriers (High Price, Little range, few charging stations, etc.) & Attitudinal Barriers (too complex, too small, etc)
SOURCE: Prießner, Sposato & Hampl 2017
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Printed
Low
2 Less educated, earn below average
income, inhabit more likely the
countryside and has a more
individualistic worldview
 High preference for any kind of
policy incentive
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High 1 Conservative
Non-Techs
(34%)
1 more likely to be female, better
educated, living on the countryside
and has a higher income
 Preference for purchase-based
incentives
Conclusion: how to trigger a mass-market-adoption of Evs in Austria?
First, potential future adopters are getting more heterogeneous. To achieve a
transition towards electric mobility in our society, policy makers, marketers and
research scholars need to get an even more granular understanding of
preferences and characteristics (focus on socio-psychological) of the future
EV adopters compared to early ones.
2
Second, EV-related industries can increase acceptance of EVs with alternative
tailored products and business models e.g., first ideas (to be researched):
EV-Supporters: Smaller EV city cars, E-car-sharing
Undiscerning Urbanites: E-Hailing, E-car-sharing, E-busses
The Undecided: E-car-pooling, types of hybrid-models
Conservative Non-Techs: Awareness campaigns
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1
Printed
3 Third, policy incentives alone will not trigger enough EV sales to sufficiently
contribute to GHG emissions reduction. Our findings underline the need to
tailor policy incentives to meet the specific needs of different types of potential
EV adopters
SOURCE: Prießner, Sposato & Hampl 2017
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Thanks for your attention! Questions?
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Printed
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Backup
Last Modified 15.02.2017 14:36 W. Europe Standard Time
Printed
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Descriptives: Part 1
Early
adopters
Potential
adopters
Nonadopters
1,000
163
325
512
1.56
3
2
1
1=male,
49%
56%
48%
47%
2=female
51%
44%
52%
53%
Age
Years
45.03
45.06
43.78
45.82
Education
1=compulsory school,
5.8%
5.6%
6.8%
5.1%
2=vocational training,
44.1%
40.5%
39.7%
48.0%
2=high school
25.1%
24.5%
27.7%
26.8%
4=college
24.2%
29.4%
25.8%
20.1%
Variable code
No. of respondents
Willingness-toinvest
3=Early Adopters
2=Potential Adopter
1=Potential Non-Adopter
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Sample
mean
Variables
Socio-demographic variables
Gender
People range from 1-6
2.39
2.23
2.60
2.31
Income
EUR per month
2,785
2,681
2,873
2,673
# of cars per
household
0=No car, 1= One car, 2=
More than one cars
1.19
1.04
1.22
1.22
Dwelling density
1=Municipal <10k,
30.2%
28.8%
30.5%
30.5%
2=Town 10-100k
32.9%
33.1%
30.1%
34.5%
3=City >100k
36.9%
38.0%
39.4%
35.0%
Printed
Household size
Context variable
SOURCE: Source
| 13
Descriptives: Part 2
Variables
Sample
mean
Early
adopters
Potential
adopters
Nonadopters
0=No financial incentive
48.0%
42.9%
52.0%
47.1%
1=Financial incentive
52.0%
57.1%
48.0%
52.9%
3.14
3.28
3.21
3.04
3.02
3.25
3.15
2.87
2.84
2.66
2.85
2.91
3.11
3.30
3.17
3.01
Variable code
EV incentives
(provided in
federal state)
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Context variable
Socio-psychological variables
Pro-technological
attitude
“I see the digitization as an
opportunity for better
networking.”
1=disagree, 2=rather
disagree, 3=rather agree,
4=agree
Pro-environmental
attitude
“I would say of myself that I
am environmentally
conscious.”
Individualism “The government interferes
Communitarianism far too much in our everyday
lives.”
Printed
1=disagree, 2=rather
disagree, 3=rather agree,
4=agree
1=disagree, 2=rather
disagree, 3=rather agree,
4=agree
HierarchismEgalitarianism
“In pursuit of equal rights in
this country, we have gone
too far.”
1=disagree, 2=rather
disagree, 3=rather agree,
4=agree
SOURCE: Source
| 14
Faktorenanalyse
Factor Analysis: Non-Purchase Motives
Factor-Analysis: Purchase Motives
Components
General EV Motives
Structural -Barriers
Technological Motives
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Components
Attitudinal Barriers
Low availability of electrical
,876
Free of emissions
Protection of the environment
and the climate
stations
Germany
and ,848
abroad)
,859
Range of the electric cars too
low
,768
Low operating costs
Ideal for short journeys and city
traffic
High efficiency of the electric
motor
Too expensive
,772
Batteries are rather short-lived
,689
No lounging possible near the
,612
apartment / house
Lower driving noise at low
,790
Long Charge-duration
,701
A petrol or diesel vehicle is
clean enough
The battery of the car can also
be used as a buffer storage for
,688
photovoltaic
High complexity
,707
component.
main
Electric cars are rather small
Rotation method: Oblimin with Kaiser
and therefore, e.g. not suitable
method:
analysis
of
the
normalization.a A. Rotation converged in 4 iterations.
SOURCE: Source
,817
,746
transition technology
Extraction
,631
EV is not save enough
The electric car is only a
system
,654
Printed
speed
in-house
,779
,710
Charm of modern technologies
the
(in
,637
,543
for a family car
| 15
Skalen: Worldviews
English version
(Kahan’s IDs)
Individualism-communitarianism
Kahan et al., 2011,
2007; Cherry et al.,
2014
IINTRSTS
(IINTRFER)
The government interferes far too much in our everyday lives.
Der Staat greift viel zu stark in unser tägliches Leben ein.
Kahan et al., 2007
IMKT
Free markets – not government programs – are the best way to supply
people with the things they need.
Freie Märkte, und nicht staatliche Programme, sind der beste Weg, um
die Bevölkerung mit den Dingen zu versorgen, die sie braucht.
Kahan et al., 2011,
2007; Cherry et al.,
2014
CPROTECT2
The government should do more to advance society’s goals, even if that
means limiting the freedom and choices of individuals.
Der Staat sollte mehr tun, um gesellschaftliche Ziele zu verfolgen, auch
wenn dies eine Einschränkung der Freiheit und der Wahlmöglichkeiten
des Einzelnen bedeutet.
(Kahan’s IDs)
Hierarchy-egalitarianism
Kahan et al., 2011,
2007; Cherry et al.,
2014
HEQUAL
We have gone too far in pushing equal rights in this country.
Im Streben nach gleichen Rechten in diesem Land sind wir zu weit
gegangen.
Kahan et al., 2011,
2007; Cherry et al.,
2014
EWEALTH2
Our society would be better off if the distribution of wealth was more
equal.
Unserer Gesellschaft würde es besser gehen, wenn der Wohlstand
gleichmäßiger verteilt wäre.
Kahan et al., 2011,
2007; Cherry et al.,
2014
EDISCRIM2
Discrimination against minorities is still a very serious problem in our
society.
Die Diskriminierung von Minderheiten ist immer noch ein sehr
ernsthaftes Problem in unserer Gesellschaft.
SOURCE: Source
German version (own translation)
Printed
Item ID
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Source(s)1
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