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1 Understanding current and future potential PEV buyers: Implications for policy Jonn Axsen Sustainable Transportation Action Research Team (START) Simon Fraser University Vancouver, Canada May 11, 2016 International Energy Agency Transport, Energy Efficiency and Behaviour Workshop
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potential PEV buyers: Implications for policy · 2019-11-27 · 11% 0% 10% 20% 30% 40% PEV Owners Mainstream Graduate Degree 33% 0% 20% 40% 60% 80% 100% PEV Owners Mainstream Household

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Page 1: potential PEV buyers: Implications for policy · 2019-11-27 · 11% 0% 10% 20% 30% 40% PEV Owners Mainstream Graduate Degree 33% 0% 20% 40% 60% 80% 100% PEV Owners Mainstream Household

1 Understanding current and future

potential PEV buyers:

Implications for policy Jonn Axsen

Sustainable Transportation Action Research Team

(START) Simon Fraser University

Vancouver, Canada

May 11, 2016

International Energy

Agency

Transport, Energy Efficiency

and Behaviour Workshop

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Sustainable Transportation Action Research Team

(START)

Canadian PEV Study

Report now available http://www.rem.sfu.ca/people/faculty/jaxsen/cpevs/

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Following media attention for different

alternative fuels (New York Times 1980-2013)

Source: Melton, Axsen & Sperling (2016), Nature Energy

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4 4

Focusing on the Canadian market…

• Compare PEV “Pioneers” with the potential mainstream market.

• Forecast PEV sales (among potential future buyers) under different policies.

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5

1) Data collection:

The Canadian Plug-in Electric

Vehicle Study (CPEVS)

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6

Passenger Vehicle Owners

A perspective on the PEV market:

Now and future

6

New vehicle buyers

Potential

“Early Mainstream”

PEV buyers

(NVOS, 2013

n = 1754)

PEV “Pioneers”

(PEVOS, 2014/15

n = 126)

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7 Canadian “Mainstream” Survey (n = 1754),

representative of new vehicle buying households

Source: Axsen et al. (2015), Electrifying Vehicles

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8

Participants (BEV+PHEV)

across BC

8

PEV owners survey (“Pioneers”)

British Columbia, 2014-15, n = 126

0% 10% 20% 30% 40% 50%

Toyota Plug in Prius

Conversions

BMW i3

Ford Focus Electric

Fisker Karma

Ford C-Max Energi

Mitsubishi i-MiEV

Smart Fortwo

Tesla Model S

Chevrolet Volt

Nissan Leaf

Participation by Vehicle Type

26%

10%

45%

Page 9: potential PEV buyers: Implications for policy · 2019-11-27 · 11% 0% 10% 20% 30% 40% PEV Owners Mainstream Graduate Degree 33% 0% 20% 40% 60% 80% 100% PEV Owners Mainstream Household

9 CPEVS: Reflexive, multi-method design

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10 PEV interest determined through discrete choice

experiment and “design space” exercise

Source: Axsen et al. (2015), Electrifying Vehicles

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11

2) The PEV “Pioneers”

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12 “Images” that PEV owners associate with their PEV

0%

20%

40%

60%

80%

100% Leaf Volt Tesla

n= 59(Leaf); 32 (Volt); 12(Tesla)

Individual Pro-Societal

Source: Axsen et al. (2015), Electrifying Vehicles

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13 Preferences: PEV Pioneers love their

PEV, tend to prefer BEV (over PHEV)

Source: Axsen et al. (2015), Electrifying Vehicles

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14

Low-tech Green

- Preserving Enviro

- Prefer BEV

- Moderate UCC interest

High-tech Green

- Supporting innovation and

enviro. progress

- Prefer BEV

- Support UCC

“Other”

- Being different

- Economical (cost)

- Practicality

- Appearance

- Prefer PHEV

- Low UCC interest

Tech Enthusiast

- Supporting innovation

- Prefer BEV

- Support UCC (grid optimization)

Not tech-oriented Very tech-oriented

Not pro-environmental

Very pro-environmental

Motivations: 4 lifestyle segments of Pioneers

Source:

Axsen et al. (2015), Electrifying Vehicles

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15

3) Comparing Pioneers to

the potential “Mainstream”

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16 PEV “Pioneers” are more highly educated,

higher income, “greener” and more “techie”

30%

11% 0%

10%

20%

30%

40%

PEVOwners

Mainstream

Graduate Degree

33% 0%

20%

40%

60%

80%

100%

PEV Owners Mainstream

Household Income = +$90k

Pioneers

Mainstream

0

5

10

15

20

TechnologyOrientation (0-25)

EnvironmentalOrientation (0-25)

67%

Source: Axsen et al. (2015), Electrifying Vehicles

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17 17 Mainstream awareness is low

“How is each of the following vehicle fueled?

Source: Axsen, Bailey and Kamiya (2013), CPEVS 2013 Preliminary Report

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18

Mainstream buyers are more attracted to

PHEVs, not so much BEVs

Source: Axsen and Goldberg (Under Review), Transportation Research Part D

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19

4: PEV forecasts….

the Respondent-based Preference

and Constraint (REPAC) model

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20 Comparing PEV policies

Purchase incentives Rebates, tax breaks, fee reductions

Energy incentives Preferential electricity rates, TOU rates

Non-monetary benefits Carpool lane access, free parking

Chargers Home: incentives, building codes, streamlined permitting

Work: workplace incentives

Public: deployment, incentives

Information provision Websites, promotional material, outreach/education

Demand-focused policies

ZEV program Direct PEV deployment requirements

Efficiency standards MPG credits for PEVs

Low-carbon fuel standard Carbon reduction credits for electricity sold

R&D support Funds for various research activities

Supply-focused policies

Adapted from: Lutsey et al. (2015), ICCT White Paper

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21

Al-Alawi and Bradley’s (2013) recommendations for a “useful” model:

1. Better represent consumer behaviour:

– Use consumer data (survey, e.g. choice model)

– Represent financial and non-financial motivators

2. Model vehicle supply and actions of automakers

– Availability of PEV models (in dealerships)

– Variety of PEV models

– Vehicle class

3. Model national and subnational policy

– Demand-focused policies (incentives, charging access)

– Supply-focused policies (production requirements)

Source: Al-Alawi and Bradley (2013), Renewable & Sustainable Energy Reviews

Responding to critiques of alternative fuel

vehicle forecast studies

Page 22: potential PEV buyers: Implications for policy · 2019-11-27 · 11% 0% 10% 20% 30% 40% PEV Owners Mainstream Graduate Degree 33% 0% 20% 40% 60% 80% 100% PEV Owners Mainstream Household

The respondent-based preference and

constraint model (REPAC)

Source: Wolinetz & Axsen (Under Review), Technological Forecasting & Social Change

Discrete choice model

Constraints model

Latent or unconstrained demand (UD)

Stated choice experiment

Vehicle attribute

model Survey data: driving patterns, vehicle class

Tech assumptions: battery costs, fuel prices

Survey data: awareness, home charging access

Dealership access, model availability

Constrained demand (CD)

Thanks Amy Miele

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The respondent-based preference and

constraint model (REPAC)

Source: Wolinetz & Axsen (Under Review), Technological Forecasting & Social Change

CDi,j= UDi,j * HCi* PFi,j * PAi,j Unconstrained

Demand Home

charging

PEV familiarity

Constrained Demand

PEV availability

Class availability

Dealership availability Model variety

Thanks Amy Miele

Page 24: potential PEV buyers: Implications for policy · 2019-11-27 · 11% 0% 10% 20% 30% 40% PEV Owners Mainstream Graduate Degree 33% 0% 20% 40% 60% 80% 100% PEV Owners Mainstream Household

The respondent-based preference and

constraint model (REPAC)

Source: Wolinetz & Axsen (Under Review), Technological Forecasting & Social Change

CDi,j= UDi,j * HCi* PFi,j * PAi,j Unconstrained

Demand Home

charging

PEV familiarity

Constrained Demand

PEV availability

One feedback: As sales increase, consumer awareness increases

Thanks Amy Miele

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The respondent-based preference and

constraint model (REPAC)

Source: Wolinetz & Axsen (Under Review), Technological Forecasting & Social Change

CDi,j= UDi,j * HCi* PFi,j * PAi,j Unconstrained

Demand Home

charging

PEV familiarity

Constrained Demand

PEV availability

In the future, we’d like to add this feedback:

consumer preference dynamics

Thanks Amy Miele

Page 26: potential PEV buyers: Implications for policy · 2019-11-27 · 11% 0% 10% 20% 30% 40% PEV Owners Mainstream Graduate Degree 33% 0% 20% 40% 60% 80% 100% PEV Owners Mainstream Household

Adding various constraints to

understand present and short-term sales

Source: Wolinetz & Axsen (Under Review), Technological Forecasting & Social Change

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0%

5%

10%

15%

20%

25%

30%

35%

40%

2015 2020 2025 2030

Subsidy to 2020 "Weaker " demand policy

PEV

new

market

share

(BC)

Demand-focused policies can get

PEVs only so far…

Source: Wolinetz & Axsen (Under Review), Technological Forecasting & Social Change

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0%

5%

10%

15%

20%

25%

30%

35%

40%

2015 2020 2025 2030

Subsidy to 2020

Subsidy to 2030, 90% home charge access

"Stronger" demand-focused policy

"Weaker " demand policy

PEV

new

market

share

(BC)

Demand-focused policies can get

PEVs only so far…

Source: Wolinetz & Axsen (Under Review), Technological Forecasting & Social Change

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0%

5%

10%

15%

20%

25%

30%

35%

40%

2015 2020 2025 2030

Subsidy to 2020

Subsidy to 2030, 9-90% home charge access

Subsidy to 2030, 90% home charge access, “full” PEV supply

+ Strong supply policy

"Stronger" demand-focused policy

"Weaker " demand policy

PEV

new

market

share

(BC)

Supply-focused policies may be essential

for PEV “success” (e.g. with 50+ models available)

Source: Wolinetz & Axsen (Under Review), Technological Forecasting & Social Change

Page 30: potential PEV buyers: Implications for policy · 2019-11-27 · 11% 0% 10% 20% 30% 40% PEV Owners Mainstream Graduate Degree 33% 0% 20% 40% 60% 80% 100% PEV Owners Mainstream Household

PEV

new

market

share

(BC)

0%

2%

4%

6%

8%

10%

12%

14%

16%

2015 2020 2025 2030

BC baseline (no policy)

“Norway-like”

Demand policy

(Norway class share)

Comparing “Norway-like” and “California-like”

policies in Canada via REPAC

Source: Wolinetz & Axsen (Under Review), Technological Forecasting & Social Change

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PEV

new

market

share

(BC)

Comparing “Norway-like” and “California-like”

policies in Canada via REPAC

0%

2%

4%

6%

8%

10%

12%

14%

16%

2015 2020 2025 2030

BC baseline (no policy)

“Norway-like”

Demand policy

(Norway class share)

“Norway-like”

Demand policy

(BC class share)

Source: Wolinetz & Axsen (Under Review), Technological Forecasting & Social Change

Page 32: potential PEV buyers: Implications for policy · 2019-11-27 · 11% 0% 10% 20% 30% 40% PEV Owners Mainstream Graduate Degree 33% 0% 20% 40% 60% 80% 100% PEV Owners Mainstream Household

PEV

new

market

share

(BC)

0%

2%

4%

6%

8%

10%

12%

14%

16%

2015 2020 2025 2030

BC baseline (no policy)

“Norway-like”

Demand policy

(Norway class share)

“Norway-like”

Demand policy

(BC class share)

“California-like” Supply policy

Comparing “Norway-like” and “California-like”

policies in Canada via REPAC

Source: Wolinetz & Axsen (Under Review), Technological Forecasting & Social Change

Page 33: potential PEV buyers: Implications for policy · 2019-11-27 · 11% 0% 10% 20% 30% 40% PEV Owners Mainstream Graduate Degree 33% 0% 20% 40% 60% 80% 100% PEV Owners Mainstream Household

Summary PEV Pioneers

General

• Higher income, education

• Green and/or techie lifestyle

• Variety of motives

(green, techie)

PEVs

• Highly aware and engaged with

technology

• Tend to prefer BEV

• Public chargers not essential

Early Mainstream

• Lower income/education

• Variety of lifestyles

• Even wider variety of motives

• Low awareness, higher

confusion (e.g. PHEVs, UCC)

• Greatly prefer PHEVs

• Public chargers not essential

REPAC relative to most PEV forecasting literature:

1. More pessimistic no-policy scenarios (e.g. 1-2% share)

2. More pessimistic about demand-focused policies (e.g. 2-12%)

3. Suggests that supply needs to increase, perhaps through supply-focused policy

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34

Extra

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35 California’s ZEV Mandate

Sales requirement: “the most direct policy change any state can take to ensure increased PEV deployment”

– California: ~15% PEV new market share by 2025

– Credits differ by vehicle (PHEV, EV, Fuel Cell)

– Credits can be traded among automakers (noncompliance = $5k per ZEV credit)

– US Regions: 8 other states have ZEV programs (Section 117 ZEV States)

Policy details from: Lutsey et al. (2015), ICCT White Paper

Page 36: potential PEV buyers: Implications for policy · 2019-11-27 · 11% 0% 10% 20% 30% 40% PEV Owners Mainstream Graduate Degree 33% 0% 20% 40% 60% 80% 100% PEV Owners Mainstream Household

36 Critiques of alternative fuel vehicle forecast studies

Al-Alawi and Bradley (2013) summarize several studies that forecasts market share of electric drive vehicles. Four modeling approaches:

1. Time-based diffusion models: e.g. fitting an s-curve

2. Constraints models: e.g. % of population with garage, or with a

particular commute distance

3. Discrete choice models: quantify consumer preferences, stated or

revealed preference (or data-less)

4. Agent-based models: flexible, represents decision makers

(consumers, even automakers), can be empirically-based or not

Source: Al-Alawi and Bradley (2013), Renewable & Sustainable Energy Reviews

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37 Stated preference choice experiment…

Source: Axsen et al. (2015), Energy Economics

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38 Identifying five consumer segments (or classes)

via a latent-class choice model

Source: Axsen et al. (2015), Energy Economics

Page 39: potential PEV buyers: Implications for policy · 2019-11-27 · 11% 0% 10% 20% 30% 40% PEV Owners Mainstream Graduate Degree 33% 0% 20% 40% 60% 80% 100% PEV Owners Mainstream Household

Modeling PEV policy: The respondent-based

preference and constraint model (REPAC)

Source: Wolinetz & Axsen (Under Review), Technological Forecasting & Social Change

Page 40: potential PEV buyers: Implications for policy · 2019-11-27 · 11% 0% 10% 20% 30% 40% PEV Owners Mainstream Graduate Degree 33% 0% 20% 40% 60% 80% 100% PEV Owners Mainstream Household

A ZEV mandate may be essential to

achieve 2050 GHG targets

0

2000

4000

6000

8000

10000

12000

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

2050 GHG Target

80% below 2005 GHGs

Current Policies

“Ambitious” Policies

(no ZEV)

+ZEV mandate

LCFS: 15% less GHG intensive w/ biofuels

CAFE: 60% less fuel intensive by 2050

“Ambitious”

Policies Carbon Tax: $30/t 2015 to $120/t 2050

ZEV Subsidies: $5000 in 2015 and 2020

Passenger

vehicle

GHGs

(well-to-

wheel)

Source: Sykes and Axsen (In Progress), Master’s Thesis