POTENTIAL ELECTRIC VEHICLE DRIVERS IN AUSTRIA By Alfons Priener; - PowerPoint PPT Presentation

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 04 September 2017, IAEE 2017 - Vienna

49% of Austrian population are interested in purchase an electric vehicle Can you imagine to purchase an Last Modified 04.09.2017 08:03 W. Europe Standard Time If I buy a car , I would chose the following... electric vehicle ... Diesel 37% Petrol Benzin 25% Hybrid 17% 11% 25% Electric (Battery Electric Elektrisch (Batterie- Ja Yes 16% Elektrofahrzeuge (BEV)… Vehicle (BEV) Rather Yes Eher ja 28% Anderes Others 2% Rather No Eher nein 36% Used oil/plant oil 1% No Altöl/Pflanzenöl Nein Natural Gas Erdgas 1% Printed Bioethanol/Biodiesel 1% 0% 10% 20% 30% 40% (1.000 respondents – Oct 2016) Who are these early and potential adopters? SOURCE : WU Wien, Deloitte, Wien Energie: „Erneuerbare Energien in Österreich 2016“ | 2

Problem statement and research objective: Early-Electric Vehicle (EV) Adopters Predictors & Characteristics Last Modified 04.09.2017 08:03 W. Europe Standard Time Early-Adopters Predictors & Characteristics Early-Adoption Predictors  Research on predictors for early EV adoption North America (e.g., Axsen et al., 2016), Norway (e.g., Nayum et al., 2016), Germany (e.g., Plötz et al., 2014) Austria (Bahamonde-Birke & Hanappi, 2016).  Certain socio-demographic and socio-psychological predictors identified  The influence of cultural worldviews on the propensity to purchase an EV not research yet Problem Characteristics Sub-Segments: Statement  A more granular understanding of potential-adopter sub-segments needed (Cherubini et al., 2015).  E.g., McKinsey (2017) sees three sub-segments of near-term potential adopters based on demographics and car preferences  Most market segmentations are not focusing on socio-psychological factors despite their need in Printed creating incentives that are more effectively accelerating EV diffusion Nayum et al. (2016) 1. Test the influence of cultural worldviews of car drivers on the propensity to purchase an EV (Cherry et al., 2014 already tested their influence on adoption of other clean technologies) Research Objectives 2. Identify and characterize potential-adopter sub-segments via demographics, EV preferences and socio-psychological characteristics | SOURCE: Prießner, Sposato & Hampl 2017 3

Based on existing literature hypothesis on the effect of socio- demographic, -psychological, worldviews and EV incentives were derived Hypothese effect on Last Modified 04.09.2017 08:03 W. Europe Standard Time Category Variable EV-adoption Reference Gender (to be male) 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 H1: Socio- al., 2016; Plötz et al., 2014 demo- Education Nayum et al., 2016; Plötz et al., 2014; Tal & Nicolas, 2013 graphic 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 Carley et al., 2013; Hidrue et al., 2011; Wolf & Seebauer, Printed H2: Socio- (a=.90) 2014; Axsen et al., 2016 psycho- Pro-Technological Axsen et al., 2016, Wolf & Seebauer, 2014). Egbue and logical (a=.80) Long (2012 Individualism (a=.55) Cherry et al. (2014); Kahan et al., 2012 H3: Worldviews Hierarchical (a=.50) Cherry et al. (2014); Kahan et al., 2012 H4: EV incentive sub-region e.g., Langbroek, Franklin, & Susilo, 2016; Mannberg, Context: EV Jansson, Pettersson, Brännlund, & Lindgren, 2014; incentives Sierzchula et al., 2014 | SOURCE: Prießner, Sposato & Hampl 2017 4

We conducted a nationally representative online survey and used a multi-nominal logistic regression and non-hierarchical cluster analysis Last Modified 04.09.2017 08:03 W. Europe Standard Time  A nationally representative online survey in Austria was conducted in Survey autumn 2016 (n=1.000). Details  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% Survey Participants  Income (EUR) 2,711 vs. 2,769 Descriptive  Federal Distribution & Age    Education  Printed We applied a multinomial logistic regression to examine whether  Methodology the socio-demographic, socio-psychological (including cultural worldviews) and contextual characteristics (i.e. policy incentives) have an influence on the willingness to purchase EVs By applying a non-hierarchical cluster analysis, we aim to shed  some light on characteristics of potential adopter segments; their preferences for policy incentives were compared with ANOVAs | SOURCE: Prießner, Sposato & Hampl 2017 5

Socio-psychological variables are stronger predictors for an early- and potential EV-adoption than socio-demographic ones Last Modified 04.09.2017 08:03 W. Europe Standard Time Adopter-segments e-cars Austria (%) Predictors for für early-/potential EV-adoption N=1.000 status Q4 2016  Socio-demographic characteristics  weak predictors: 100  Men are more willing to buy an EV  People without a car have a preference for EVs in case of a car-purchase  51 No significant effect : age, income, education, etc.  Socio-psychological characteristics  strong predictors:  Early adopters : strong pro-environment and pro- 32 technological attitude Printed  Non-adopters: strong individualistic and 17 hierarchical worldviews  EV policy incentives: mixed predictors, i.e.,  Potential Early adopters : significant effect Early Non- Total  adopters 2 adopters 1 adopters 3 Non-adopters: non-significant effect 1: Already own an e-car or want to buy an e-car as next car 2: Can imagine to buy a car in the near future, but not as their next car 3: No intention to replace his/her car against an e-car in the near future | SOURCE: Prießner, Sposato & Hampl 2017 6

EV-purchase motives are evaluated significantly higher Non-adopters from early- and potential adopters Potential adopters Early Adopters Last Modified 04.09.2017 08:03 W. Europe Standard Time Evaluation purchase motives PRO EV per adopter segment : 1=non-relevant – 5=very relevant Emission-free Protection of the environment and climate Main Take-aways ▪ No big difference in Lower operation cost valuation between early- and potential Ideal for short distance and city traffic adopters ▪ Non-adopters see High efficiency of electric engines buying reasons for an electric car less relevant More independence from energy suppliers ▪ Electric cars are not Printed seen as a static Low driving noise by low speed symbol, but as a green alternative The battery of the car can be also used as a buffer with lower operating storage for the in-house photovoltaic system costs, well suited for Charm of modern technologies city traffic Good experiences of friends or relatives Status symbol 0 1 2 3 4 5 SEITE 7 | 7 SOURCE: WU Wien, Deloitte, Wien Energie: „Erneuerbare Energien in Österreich 2016“

EV non-purchase motives are evaluated similar across all Non-adopters adopter segments Potential adopters Early Adopters General Non- Last Modified 04.09.2017 08:03 W. Europe Standard Time Purchase Motives Evaluation EV Non-Purchase Motives / customer segment : 1=non-relevant – 5=very relevant Range of EVs too low Too expensive Main Take-aways ▪ Range, price, e- Low availability of EV-charging stations (in Austria/abroad) charging infrastructure EV batteries are rather short-lived are still the most perceived e-car Long charging duration barriers ▪ The gap in structural No charging possibility near apartment/house E-car barriers between The technology for electric cars is not yet fully developed non-adopters and EV are also a burden on the environment (e.g., battery early adopters is not production and disposal, electricity production) statistically significant, Printed EVs are rather small and therefore e.g., not suitable as a family i.e., uncertainties as car well as ignorance in Too small selections of models every future adopter segment EV is only a transition technology ▪ Attitude barriers Not safe enough stronger for non- adopters High complexity A petrol- or diesel car is clean enough I do not need a car SEITE 8 0 1 2 3 4 5 | 8 SOURCE: WU Wien, Deloitte, Wien Energie: „Erneuerbare Energien in Österreich 2016“