Barriers to widespread adoption of electric vehicles: An analysis of consumer attitudes and perceptions

doi:10.1016/J.ENPOL.2012.06.009

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Barriers to widespread adoption of electric vehicles: An analysis of consumer attitudes and perceptions

Journal Article•DOI•

Barriers to widespread adoption of electric vehicles: An analysis of consumer attitudes and perceptions

Ona Egbue¹, Suzanna Long¹•Institutions (1)

Missouri University of Science and Technology¹

01 Sep 2012-Energy Policy (Elsevier)-Vol. 48, pp 717-729

TL;DR: In this paper, the authors identify potential socio-technical barriers to consumer adoption of EVs and determine if sustainability issues influence consumer decision to purchase an EV, and provide valuable insights into preferences and perceptions of technology enthusiasts; individuals highly connected to technology development and better equipped to sort out the many differences between EVs and CVs.

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About: This article is published in Energy Policy.The article was published on 2012-09-01. It has received 1207 citations till now.

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Journal Article•DOI•

A review of consumer preferences of and interactions with electric vehicle charging infrastructure

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Scott Hardman¹, Alan Jenn¹, Gil Tal¹, Jonn Axsen², George Beard, Nicolò Daina³, Erik Figenbaum, Niklas Jakobsson⁴, Patrick Jochem⁵, Neale Kinnear, Patrick Plötz, Jose Pontes, Nazir Refa, Frances Sprei⁴, Tom Turrentine¹, Bert Witkamp - Show less +12 more•Institutions (5)

University of California, Davis¹, Simon Fraser University², Imperial College London³, Chalmers University of Technology⁴, Karlsruhe Institute of Technology⁵

01 Jul 2018-Transportation Research Part D-transport and Environment

TL;DR: In this paper, the authors present a literature review of studies that investigate infrastructure needs to support the market introduction of plug-in electric vehicles (PEVs), focusing on literature relating to consumer preferences for charging infrastructure, and how consumers interact with and use this infrastructure.

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Abstract: This paper presents a literature review of studies that investigate infrastructure needs to support the market introduction of plug-in electric vehicles (PEVs). It focuses on literature relating to consumer preferences for charging infrastructure, and how consumers interact with and use this infrastructure. This includes studies that use questionnaire surveys, interviews, modelling, GPS data from vehicles, and data from electric vehicle charging equipment. These studies indicate that the most important location for PEV charging is at home, followed by work, and then public locations. Studies have found that more effort is needed to ensure consumers have easy access to PEV charging and that charging at home, work, or public locations should not be free of cost. Research indicates that PEV charging will not impact electricity grids on the short term, however charging may need to be managed when the vehicles are deployed in greater numbers. In some areas of study the literature is not sufficiently mature to draw any conclusions from. More research is especially needed to determine how much infrastructure is needed to support the roll out of PEVs. This paper ends with policy implications and suggests avenues of future research.

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358 citations

Journal Article•DOI•

Electric vehicles revisited: a review of factors that affect adoption

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Makena Coffman, Paul Bernstein, Sherilyn Wee

02 Jan 2017-Transport Reviews

TL;DR: In this article, a growing body of peer-reviewed literature assessing factors affecting EV adoption is reviewed and several important gaps in knowledge are identified, particularly in regards to issues of timing and magnitude.

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339 citations

Cites background or result from "Barriers to widespread adoption of ..."

...Egbue and Long (2012) found in their study among technology enthusiasts that 17% of the respondents identified lack of charging infrastructure as their biggest concern with EVs. Sierzchula et al. (2014) found that charging infrastructure (relative to population) is significantly positively related to EV market share across countries. In a regional and municipal level analysis of incentives in Norway, Mersky, Sprei, Samaras, and Qian (2016) found that EV charging infrastructure is the greatest predictor of EV uptake. Tran et al. (2013) draw similar conclusions through a Monte Carlo simulation model. The literature also looks at the question of what determines adequate charging infrastructure. Xi, Sioshansi, and Marano (2013) developed an optimisation model that locates Level 1 and Level 2 charging infrastructure within the central-Ohio region. By maximising service levels (amount of battery energy recharged and number of EVs recharged), they found that universities have the highest service level since multiple EVs are able to fully recharge throughout the day. Workplace charging is less effective because vehicles are normally parked all day long. Shopping locations only serve vehicles in the morning and afternoon and are restricted to a small group of vehicles. Through a discrete choice model done in Japan, Ito, Takeuchi, and Managi (2013) found that an EV user will have a lower willingness to pay for “quick charging” at a retail location (like outside a supermarket) if the user has “quick charge” capability at home. Moreover, the authors found that a robust battery-exchange network could be economical if new EV sales exceed 5%. Similarly, Schroeder and Traber (2012), Flores, Shaffer, and Brouwer (2016), and Madina, Zamora, and Zabala (2016) found that fast chargers are not profitable at low EV adoption and trip rates, particularly when people favour home charging....
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...Egbue and Long (2012) found in their study among technology enthusiasts that 17% of the respondents identified lack of charging infrastructure as their biggest concern with EVs. Sierzchula et al. (2014) found that charging infrastructure (relative to population) is significantly positively related to EV market share across countries. In a regional and municipal level analysis of incentives in Norway, Mersky, Sprei, Samaras, and Qian (2016) found that EV charging infrastructure is the greatest predictor of EV uptake. Tran et al. (2013) draw similar conclusions through a Monte Carlo simulation model. The literature also looks at the question of what determines adequate charging infrastructure. Xi, Sioshansi, and Marano (2013) developed an optimisation model that locates Level 1 and Level 2 charging infrastructure within the central-Ohio region. By maximising service levels (amount of battery energy recharged and number of EVs recharged), they found that universities have the highest service level since multiple EVs are able to fully recharge throughout the day. Workplace charging is less effective because vehicles are normally parked all day long. Shopping locations only serve vehicles in the morning and afternoon and are restricted to a small group of vehicles. Through a discrete choice model done in Japan, Ito, Takeuchi, and Managi (2013) found that an EV user will have a lower willingness to pay for “quick charging” at a retail location (like outside a supermarket) if the user has “quick charge” capability at home. Moreover, the authors found that a robust battery-exchange network could be economical if new EV sales exceed 5%. Similarly, Schroeder and Traber (2012), Flores, Shaffer, and Brouwer (2016), and Madina, Zamora, and Zabala (2016) found that fast chargers are not profitable at low EV adoption and trip rates, particularly when people favour home charging. Using data from a small BEV usage trial in Japan, with 24 private and 8 commercial vehicles, Sun, Yamamoto, and Morikawa (2016) found that private EV users are willing to detour up to...
[...]
...Egbue and Long (2012) found in their study among technology enthusiasts that 17% of the respondents identified lack of charging infrastructure as their biggest concern with EVs. Sierzchula et al. (2014) found that charging infrastructure (relative to population) is significantly positively related to EV market share across countries. In a regional and municipal level analysis of incentives in Norway, Mersky, Sprei, Samaras, and Qian (2016) found that EV charging infrastructure is the greatest predictor of EV uptake. Tran et al. (2013) draw similar conclusions through a Monte Carlo simulation model. The literature also looks at the question of what determines adequate charging infrastructure. Xi, Sioshansi, and Marano (2013) developed an optimisation model that locates Level 1 and Level 2 charging infrastructure within the central-Ohio region. By maximising service levels (amount of battery energy recharged and number of EVs recharged), they found that universities have the highest service level since multiple EVs are able to fully recharge throughout the day. Workplace charging is less effective because vehicles are normally parked all day long. Shopping locations only serve vehicles in the morning and afternoon and are restricted to a small group of vehicles. Through a discrete choice model done in Japan, Ito, Takeuchi, and Managi (2013) found that an EV user will have a lower willingness to pay for “quick charging” at a retail location (like outside a supermarket) if the user has “quick charge” capability at home....
[...]
...Egbue and Long (2012) found in their study among technology enthusiasts that 17% of the respondents identified lack of charging infrastructure as their biggest concern with EVs. Sierzchula et al. (2014) found that charging infrastructure (relative to population) is significantly positively related to EV market share across countries. In a regional and municipal level analysis of incentives in Norway, Mersky, Sprei, Samaras, and Qian (2016) found that EV charging infrastructure is the greatest predictor of EV uptake. Tran et al. (2013) draw similar conclusions through a Monte Carlo simulation model. The literature also looks at the question of what determines adequate charging infrastructure. Xi, Sioshansi, and Marano (2013) developed an optimisation model that locates Level 1 and Level 2 charging infrastructure within the central-Ohio region....
[...]
...In a web-based survey administered at a technological university, 33% of the respondents identified battery range as their biggest concern with EVs (Egbue & Long, 2012)....
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Journal Article•DOI•

Effectiveness of incentives on electric vehicle adoption in Norway

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Avi Chaim Mersky¹, Frances Sprei², Constantine Samaras¹, Zhen (Sean) Qian¹•Institutions (2)

Carnegie Mellon University¹, Chalmers University of Technology²

01 Jul 2016-Transportation Research Part D-transport and Environment

TL;DR: In this paper, the authors analyzed the sales of electric vehicles on a regional and municipal basis in Norway and then cross analyzed these with the corresponding local demographic data and incentive measures to attempt to ascertain which factors lead to higher BEV adoption.

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Abstract: © 2016 Elsevier Ltd. Battery Electric vehicles (BEVs) shift pollution off the road and to potentially less damaging and more varied sources than petroleum. Depending on the source of electricity, a transition to electrified personal transportation can dramatically reduce greenhouse gas emissions and air pollutants. However current EVs tend to be more expensive and have shorter range, which can hinder public adoption. Government incentives can be used to alleviate these factors and encourage adoption. Norway has a long history incentivizing BEV adoption including measures such as exemption from roadway tolls, access to charging infrastructure, point of sale tax incentives, and usage of public bus use limited lanes. This paper analyzed the sales of electric vehicles on a regional and municipal basis in Norway and then cross analyzed these with the corresponding local demographic data and incentive measures to attempt to ascertain which factors lead to higher BEV adoption. It was concluded that access to BEV charging infrastructure, being adjacent to major cities, and regional incomes had the greatest predictive power for the growth of BEV sales. It was also concluded that short-range vehicles showed somewhat more income and unemployment sensitivity than long-range vehicles. Toll exemptions and the right to use bus designated lanes do not seem to have statistically significant predictive power for BEV sales in our linear municipal-level models, but this could be due to neighboring major cities containing those incentive features.

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322 citations

Cites background from "Barriers to widespread adoption of ..."

...State preference and survey studies also find refueling possibilities an important factor for the adoption of a range of alternative fueled vehicles including EVs (Achtnicht et al., 2012; Egbue and Long, 2012; Tran et al., 2012)....
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Journal Article•DOI•

The effect of policy incentives on electric vehicle adoption

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Joram H.M. Langbroek¹, Joel P. Franklin¹, Yusak O. Susilo¹•Institutions (1)

Royal Institute of Technology¹

01 Jul 2016-Energy Policy

TL;DR: In order to increase the attractiveness of electric vehicles (EVs), packages of policy incentives are provided in many countries as discussed by the authors, however, it is still unclear how effective different policy incenti...

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312 citations

Journal Article•DOI•

A review of battery fires in electric vehicles

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Peiyi Sun¹, Roeland Bisschop², Niu Huichang³, Xinyan Huang¹•Institutions (3)

Hong Kong Polytechnic University¹, Research Institutes of Sweden², Industrial Technology Research Institute³

01 Jan 2020-Fire Technology

TL;DR: In this article, the authors focus on the latest fire-safety issues of EVs related to thermal runaway and fire in Li-ion batteries and provide a qualitative understanding of the fire risk and hazards associated with battery powered EVs.

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Abstract: Over the last decade, the electric vehicle (EV) has significantly changed the car industry globally, driven by the fast development of Li-ion battery technology. However, the fire risk and hazard associated with this type of high-energy battery has become a major safety concern for EVs. This review focuses on the latest fire-safety issues of EVs related to thermal runaway and fire in Li-ion batteries. Thermal runaway or fire can occur as a result of extreme abuse conditions that may be the result of the faulty operation or traffic accidents. Failure of the battery may then be accompanied by the release of toxic gas, fire, jet flames, and explosion. This paper is devoted to reviewing the battery fire in battery EVs, hybrid EVs, and electric buses to provide a qualitative understanding of the fire risk and hazards associated with battery powered EVs. In addition, important battery fire characteristics involved in various EV fire scenarios, obtained through testing, are analysed. The tested peak heat release rate (PHHR in MW) varies with the energy capacity of LIBs ($$E_{B}$$ in Wh) crossing different scales as $$PHRR = 2E_{B}^{0.6}$$. For the full-scale EV fire test, limited data have revealed that the heat release and hazard of an EV fire are comparable to that of a fossil-fuelled vehicle fire. Once the onboard battery involved in fire, there is a greater difficulty in suppressing EV fires, because the burning battery pack inside is inaccessible to externally applied suppressant and can re-ignite without sufficient cooling. As a result, an excessive amount of suppression agent is needed to cool the battery, extinguish the fire, and prevent reignition. By addressing these concerns, this review aims to aid researchers and industries working with batteries, EVs and fire safety engineering, to encourage active research collaborations, and attract future research and development on improving the overall safety of future EVs. Only then will society achieve the same comfort level for EVs as they have for conventional vehicles.

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303 citations

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References

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Open Access

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Journal Article•DOI•

The theory of planned behavior

[...]

Icek Ajzen¹•Institutions (1)

University of Massachusetts Amherst¹

01 Dec 1991-Organizational Behavior and Human Decision Processes

TL;DR: Ajzen, 1985, 1987, this article reviewed the theory of planned behavior and some unresolved issues and concluded that the theory is well supported by empirical evidence and that intention to perform behaviors of different kinds can be predicted with high accuracy from attitudes toward the behavior, subjective norms, and perceived behavioral control; and these intentions, together with perceptions of behavioral control, account for considerable variance in actual behavior.

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65,095 citations

Journal Article•DOI•

Car use: lust and must. Instrumental, symbolic and affective motives for car use

[...]

Linda Steg¹•Institutions (1)

University of Groningen¹

01 Feb 2005-Transportation Research Part A-policy and Practice

TL;DR: In this paper, the authors report results of two questionnaire studies aimed at examining various motives for car use, and investigate individual differences in the relative importance of the three categories of motives were investigated.

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Abstract: This paper reports results of two questionnaire studies aimed at examining various motives for car use. In the first study, a random selection of 185 respondents who possess a driving licence were interviewed. Respondents were recruited from the cities of Groningen and Rotterdam, The Netherlands. The sample of the second study comprised a random selection of 113 commuters who regularly travelled during rush hours in and around Rotterdam, a region in the west of the Netherlands. First, it was examined which categories of car use motives may be distinguished. As proposed by Dittmar’s (1992) [The social psychology of material possessions: to have is to be. Havester Wheatsheaf, Hemel Hempstead, UK; St. Martin’s Press, New York] model on the meaning of material possessions, results from both studies revealed that car use not only fulfils instrumental functions, but also important symbolic and affective functions. Second, it was studied to what extent these different motives are related to the level of car use. From the results of study 2, it appeared that commuter car use was most strongly related to symbolic and affective motives, and not to instrumental motives. Third, individual differences in the relative importance of the three categories of motives were investigated. In both studies, most group differences were found in the evaluation of the symbolic and affective motives (and not the instrumental ones). Especially frequent drivers, respondents with a positive car attitude, male and younger respondents valued these non-instrumental motives for car use. These results suggest that policy makers should not exclusively focus on instrumental motives for car use, but they should consider the many social and affective motives as well.

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1,064 citations

Journal Article•DOI•

Giving Green to Get Green: Incentives and Consumer Adoption of Hybrid Vehicle Technology

[...]

Kelly Sims Gallagher¹, Erich Muehlegger¹•Institutions (1)

Harvard University¹

01 Feb 2008-Social Science Research Network

TL;DR: In this paper, the relative efficacy of state sales tax waivers, income tax credits and non-tax incentives for hybrid-electric vehicle adoption in the United States has been studied and shown that the type of tax incentive offered is as important as the value of the tax incentive.

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Abstract: Federal, state and local governments use a variety of incentives to induce consumer adoption of hybrid-electric vehicles. We study the relative efficacy of state sales tax waivers, income tax credits and non-tax incentives and find that the type of tax incentive offered is as important as the value of the tax incentive. Conditional on value, we find that sales tax waivers are associated a seven-fold greater increase in hybrid sales than income tax credits. In addition, we estimate the extent to which consumer adoption of hybrid-electric vehicles (HEV) in the United States from 2000-2006 can be attributed to government incentives, changing gasoline prices, or consumer preferences for environmental quality or energy security. After controlling for model specific state and time trends, we find that rising gasoline prices are associated with higher hybrid sales, although the effect operates entirely through sales of the hybrid models with the highest fuel economy. In total, we find that tax incentives, rising gasoline prices and social preferences are associated with 6, 27 and 36 percent of high economy hybrid sales from 2000-2006.

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595 citations

Journal Article•DOI•

Beyond batteries: an examination of the benefits and barriers to plug-in hybrid electric vehicles (PHEVs) and a vehicle-to-grid (V2G) transition

[...]

Benjamin K. Sovacool¹, Richard F. Hirsh²•Institutions (2)

National University of Singapore¹, Virginia Tech²

01 Mar 2009-Energy Policy

TL;DR: In this article, the authors explore both the promise and the possible pitfalls of the plug-in hybrid electric vehicles (PHEV) and vehicle-to-grid (V2G) concept, focusing first on its definition and then on its technical state-of-the-art.

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551 citations

Journal Article•DOI•

Electric vehicles: How much range is required for a day’s driving?

[...]

Nathaniel S. Pearre¹, Willett Kempton¹, Randall Guensler², Vetri Elango²•Institutions (2)

University of Delaware¹, Georgia Institute of Technology²

01 Dec 2011-Transportation Research Part C-emerging Technologies

TL;DR: In this article, a full year of high-resolution driving data from 484 instrumented gasoline vehicles in the US is used to analyze daily driving patterns, and from those infer the range requirements of electric vehicles (EVs).

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Abstract: One full year of high-resolution driving data from 484 instrumented gasoline vehicles in the US is used to analyze daily driving patterns, and from those infer the range requirements of electric vehicles (EVs). We conservatively assume that EV drivers would not change their current gasoline-fueled driving patterns and that they would charge only once daily, typically at home overnight. Next, the market is segmented into those drivers for whom a limited-range vehicle would meet every day’s range need, and those who could meet their daily range need only if they make adaptations on some days. Adaptations, for example, could mean they have to either recharge during the day, borrow a liquid-fueled vehicle, or save some errands for the subsequent day. From this analysis, with the stated assumptions, we infer the potential market share for limited-range vehicles. For example, we find that 9% of the vehicles in the sample never exceeded 100 miles in one day, and 21% never exceeded 150 miles in one day. These drivers presumably could substitute a limited-range vehicle, like electric vehicles now on the market, for their current gasoline vehicle without any adaptation in their driving at all. For drivers who are willing to make adaptations on 2 days a year, the same 100 mile range EV would meet the needs of 17% of drivers, and if they are willing to adapt every other month (six times a year), it would work for 32% of drivers. Thus, it appears that even modest electric vehicles with today’s limited battery range, if marketed correctly to segments with appropriate driving behavior, comprise a large enough market for substantial vehicle sales. An additional analysis examines driving versus parking by time of day. On the average weekday at 5 pm, only 15% of the vehicles in the sample are on the road; at no time during the year are fewer than 75% of vehicles parked. Also, because the return trip home is widely spread in time, even if all cars plug in and begin charging immediately when they arrive home and park, the increased demand on the electric system is less problematic than prior analyses have suggested.

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541 citations