Renewable and Sustainable Energy Reviews 78 (2017) 318–328
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Renewable and Sustainable Energy Reviews journal homepage: www.elsevier.com/locate/rser
A review of factors inﬂuencing consumer intentions to adopt battery electric vehicles ⁎
Wenbo Li, Ruyin Long , Hong Chen , Jichao Geng School of Management, China University of Mining and Technology, Da Xue Road 1, Xuzhou 221116, China
A R T I C L E I N F O
A BS T RAC T
Keywords: Intention to adopt Battery electric vehicles Inﬂuencing factors Literature review
Despite reducing environmental pollution and the excessive consumption of fossil fuels, the number of battery electric vehicles (BEVs) on the road is still low. Why is this so? Why is the mass adoption of BEVs so diﬃcult to realize? One important reason is that the adoption of BEVs is, to a large extent, dependent on the acceptance of private consumers, and their willingness to adopt this mode of transport is insuﬃcient. This study is a systematic overview of peer-reviewed journal articles to identify the reasons for and against consumer intentions to adopt BEVs. A total of 1846 papers were retrieved and after a two-step identiﬁcation, 40 papers were ﬁnally identiﬁed and analyzed in detail. The inﬂuencing factors were categorized into three main types, namely demographic, situational and psychological, and they were reviewed separately. In addition, the shortcomings and deﬁciencies in the current studies were also noted.
1. Introduction Transportation industries are fundamental in contemporary society and play an important role in world economic growth. With socioeconomic development and improvements in living standards, the problems caused by transportation, such as excessive oil consumption, air pollution and greenhouse gas emissions, will become more serious in the future . To mitigate these problems, the development of fuel-eﬃcient and alternative-fuel vehicles, in particular, battery electric vehicles (BEVs), has become one of the main aims in the automobile industry in many countries . BEVs are powered by electricity and have no internal-combustion engine, and as a result do not produce gas emissions. This is of great signiﬁcance for protecting the environment and reducing climate change. In addition, the energy transition eﬃciency of BEVs is higher than traditional automobiles and the electricity to charge them can be obtained from wind, the sun, water and other clean sources of energy. Therefore, the promotion of BEV adoption can reduce our consumption of and reliance on fossil fuels. Furthermore, BEVs are more suitable for the low speed states and stop-go patterns that are common in city driving . However, all the above advantages oﬀered by BEVs have not been enough to persuade consumers. Even in Norway, a global forerunner in the ﬁeld of electro mobility, the share of BEVs only accounts for about 2% of all passenger vehicles . Since the number of private vehicles accounts for a large proportion of car ownership and will continue to increase
in the near future, it is clear that the mass adoption of BEVs relies, to a large extent, on private consumers . Therefore, exploring what factors inﬂuence consumers to adopt BEVs is essential for stakeholders and government policy making. BEVs are still new automobile products for consumers in many countries and regions, and the number of consumers who already possess or drive BEVs is comparatively low. Since it is diﬃcult to investigate and analyze actual consumer behavior , present researches related to adopting BEVs focus more on consumer intentions. Researchers have utilized various methods and drawn many useful conclusions, but there is currently a lack of a summary to help readers understand the research status and development trends in this ﬁeld. Therefore, this paper presents a comprehensive overview to facilitate, and to provide a reference point for, future research. The research objectives of the review were (1) to collect and identify papers related to the consumers’ reasons to adopt BEVs; (2) to explore and review the important factors that inﬂuence the intentions to adopt BEVs; and (3) to analyze critically the limitations of current studies and to suggest future lines of work. The study is arranged as follows. In the next section, the materials and methods used for this review are presented. The factors inﬂuencing consumer intentions to adopt BEVs are reviewed in Section 3. Finally, in the conclusions and recommendations section, opportunities for and beneﬁts from further studies are elaborated in detail.
Corresponding authors. E-mail addresses: [email protected]
(W. Li), [email protected]
(R. Long), [email protected]
(H. Chen), [email protected]
http://dx.doi.org/10.1016/j.rser.2017.04.076 Received 28 May 2016; Received in revised form 29 December 2016; Accepted 27 April 2017 1364-0321/ © 2017 Elsevier Ltd. All rights reserved.
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Although a number of studies modeled market demand, market share and their inﬂuences on future BEV markets , they cannot reﬂect the actual intentions of consumers. As a result, these studies were also removed. Thus, after ﬁltering the 88 studies, 24 studies were left. However, 16 more studies retrieved not through searches but chosen from the references cited by the 88 papers were supplemented with our selection, leaving us with a ﬁnal list of 40 papers. From Fig. 2, it can be seen that the 40 studies were all published after 2011 and the number of studies shows an increasing trend over time. This indicates that with the background of an acute global energy crisis and progressive depravation of the environment, researchers have become more concerned with this topic in the past ﬁve years. On a per country basis (Fig. 3), studies focusing on the US and Germany account for more than half of the 40 studies, the rest primarily involve other European countries, Australia, China and Korea.
2. Materials and methods 2.1. Deﬁnition of BEVs In order to clarify what BEVs are and why they are selected as objects for research, diﬀerent types of electric vehicles (EVs) are introduced in the following discussion. Presently, the EVs on the market not only include BEVs, but also hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs) and extended-range electric vehicles (E-REVs). HEVs are each powered by a gasoline internal-combustion engine and a supplementary electric motor. With its limited battery capacity, the electric motor can only supply power for starting the vehicle and acceleration. HEVs cannot be charged by outlets, instead the batteries are charged by recovering the energy through deceleration or braking. A PHEV, which is a new type of HEV, has better battery capacity and can be charged from electricity mains. The major diﬀerence between PHEVs and HEVs is that the former have a short pure-electric range, usually about 50– 100 km, and can be driven by an ICE after battery depletion. E-REVs, similar to PHEVs, also have better battery capacity and a plug-in charger. When an E-REV depletes its energy in pure-electric mode, a fuel tank is used for extending its driving range by charging the batteries and providing electricity that directly drives the electric motor. A BEV is completely powered by an electric motor and the batteries are the only powerful energy source. The batteries can mainly be charged with a plug-in charger. Compared to HEVs, PHEVs and EREVs, BEVs have the highest battery capacity and longest pure-electric driving range. Energy generation in HEVs primarily comes from gasoline or diesel. As HEVs cannot be charged by an outlet, using a HEV is no diﬀerent from a conventional fuel vehicle (CFV). Although PHEVs and E-REVs need to be recharged from an external electric power source after battery depletion, their total driving range is similar to a CFV with a fuel tank. However, in spite of the longer pure-electric driving range, the total driving range of a BEV is far less than the other three EVs. In addition, due to the longer charging time for BEVs, compared to PHEVs or E-REVs, more care must be given to timely charging in order to avoid a lack of power during the next use. Compared with CFVs or other EVs, consumers who use a BEV need to signiﬁcantly change their usage behavior and habits. This means that the factors inﬂuencing whether or not consumers will adopt a BEV are also quite diﬀerent. Therefore, this review is mostly conﬁned to the factors that inﬂuence the decision to adopt BEVs and not those related to HEVs, PHEVs and E-REVs.
3. Results and discussion 3.1. Overview Rezvani et al.  reported that the adoption of EVs can be seen as behavioral responses incorporating purchase and use. Therefore, the intentions to adopt in this review include purchasing intentions, using intentions, consumer readiness, willingness to pay, willingness to accept and other similar proxy variables. Many studies have established models to analyze the factors inﬂuencing consumer intentions to adopt BEVs. Lane and Potter  utilized two categories to illustrate these factors, situational and psychological factors. The former include objective factors, such as economics, environmental regulations, performance attributes and fuel/road infrastructure readiness. The latter are subjective factors that include attitudes, symbols, experience, societal inﬂuences and emotions. However, demographic factors, which are also a major inﬂuence on consumer EV adopting intentions and can reﬂect the characteristics of diﬀerent individuals and families, are not included in this study. Therefore, in this review, the factors inﬂuencing consumer intentions to adopt BEVs are categorized into three categories, namely demographic, situational, and psychological. Using the identiﬁed studies, a list of the factors in these three categories is produced in Table 1. 3.2. Demographic factors The inﬂuence of demographic factors on environmental protection and low-carbon purchasing behavior has gained extensive attention in recent years. Similarly, many studies have discussed the impact of demographic factors on consumer intentions to adopt BEVs, focusing on two main aspects, individual and family factors.
2.2. Identiﬁcation strategy and results Two steps were used to identify the relevant studies (see Fig. 1). The ﬁrst step was to search for research papers published in peerreviewed journals in the following databases and search engines; Science Direct, Springer, Wiley, Emerald, Web of Science, and Google Scholar. The search focused mainly on studies from 2006 onwards with the following keywords: electric vehicle, pure electric vehicle, full electric vehicle, battery electric vehicle, new energy vehicle, green vehicle, energy saving vehicle, alternative fuel vehicle, cleaner vehicle, eco-car, adoption, use, usage, purchase, buy, pay, preference, accept, acceptance, willingness, intention and behavior. From these, 1846 studies were identiﬁed. After eliminating 1561 studies with irrelevant titles, 285 studies remained. The abstracts of these studies were then checked for relevance. Only 88 of the studies were related to the topic of this review. The second step was to ﬁlter the 88 studies using full-text reviews with three primary inclusion criteria. To begin with, studies featuring the reasons for and against consumer intentions to adopt BEVs were focused on. Furthermore, the studies had to use empirical consumer data, rather than mathematical induction or computer simulations.
3.2.1. Individual factors To date, the individual factors that have been discussed mainly include gender, age, education level, income and occupation. Based on the available studies, young and middle-aged, well-educated male consumers are believed to have stronger intentions to adopt [9–13]. In terms of occupation, Plötz et al.  found that consumers engaged in technical professions are more likely than others to prefer BEVs. This point may be relevant to the results of Egbue and Long  and Hackbarth et al. , who reported that BEVs are diﬀerent from ordinary green products. As assemblages of advanced technology, BEVs are more easily acceptable to technophiles. In terms of income, generally speaking, the purchasing cost for BEVs is higher than for CFVs, meaning that purchasers must have suﬃcient wealth. Although many studies believed that this is an important predictor for the adopting intentions of ﬂexible-fuel and hybrid-electric vehicles [16,17], the results of BEV-related studies suggested the opposite. Zhang et al.  used a questionnaire to survey 299 trainees in Nanjing driving schools, the results showed that whether a consumer chooses an EV is 319
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Fig. 1. Identiﬁcation process for relevant studies.
Fig. 2. Number of relevant studies per year.
not inﬂuenced by income. Similarly, a larger survey (n=3092) was conducted by Hidrue et al.  in the US, the authors again found that income is not an important factor. Bjerkan et al.  suggested that income is a less prominent indicator when compared with gender, age and education. They believed that this was because of the reasonable prices of BEVs in Norway, which is likely a result of the signiﬁcant market competition.
Fig. 3. Rate of relevant studies in diﬀerent countries.
Peters and Dütschke  reported that consumer intentions to adopt BEVs increase with the number of family vehicles. The results of Hackbarth et al.  are somewhere in between the above two studies, and stated that the number of vehicles is indeed an inﬂuence, but only families with HEVs have a positive impact on consumer intentions. Although the results of these three studies are diﬀerent, they all acknowledge that there is an impact of vehicle numbers on consumer adopting intentions. However, Hidrue et al.  did not accept this view and they suggested that there is no impact from vehicle numbers. With regards to charging vehicles at home, the results of Bühler et al.  suggested that if there are enough family charging piles, present BEVs can, to a large extent, meet consumer daily traveling demands. In addition, Hidrue et al.  and Hackbarth et al.  believed that the realization of charging BEVs at home or nearby can improve consumer
3.2.2. Family factors Diﬀerent from a daily commodity, BEVs are classed as big-ticket purchases. Deciding whether or not to purchase a BEV not only depends on consumers themselves, but often their family members also. In the joint decision-making process, family factors usually have a great inﬂuence on consumer adopting intentions. Presently, the number of vehicles and the accessibility to plug-in vehicles at home are the main concerns. As Zhang et al.  asserted, the number of vehicles is an important factor; consumers in families with more vehicles always have less intention to adopt BEVs. On the contrary, 320
Barth et al. (2016) Beck et al. (2016)
Bühler et al. (2014) Burgess et al. (2013)
Bjerkan et al. (2016) Carley et al. (2013)
Dumortier et al. (2015) Egbue and Long (2012)
Franke and Krems (2013)
    
   
Jensen et al. (2014) Ko and Hahn (2013) Lai et al. (2015) Lieven et al. (2011) Moons and De Pelsmacker (2012) Noppers et al. (2014) Peters and Dütschke (2014) Pierre et al. (2011) Plötz et al. (2014)
Green et al. (2014) Hackbarth and Madlener (2013) Hackbarth and Madlener (2016) Helveston et al. (2015) Hoen and Koetse (2014) Hidrue et al. (2011) Jensen et al. (2013)
Axsen et al. (2013)
Axsen and Kurani (2013)
Graham-Rowe et al. (2012)
Aasness and Odeck (2015) Adepetu and Keshav (2015) Axsen et al. (2012)
Gender, age, education, occupation,
Gender, age, number of family vehicles
Age, education, accessibility to plug-in vehicles at home Age, education
Gender, age, education
Age, gender, education Education, gender, age
Table 1 Overview of factors influencing consumers’ intention to adopt battery electric vehicles.
Charging time, domestic charging infrastructure, charging price, driving range Fuel economy, driving range
Environmental attributes, functional attributes Cost reducing policy, carbon emission, energy efficiency
Purchasing cost, driving range, charging infrastructure, charging time, environmental effect Driving range, government incentives, vehicle emissions, energy crisis, air quality, climate change Driving interest, driving cost, low noise, purchasing cost, driving range Performance, speed, noise, look and style, environmental attributes, car of the future, Purchase cost, running cost Purchasing cost, policy incentives Charging time, driving range, charging infrastructure, charging time, fuel economy, purchasing cost Battery cost, driving range Technological level, driving range, environment effect, safety, charging infrastructure, purchasing cost, sustainability Driving range, charging time, charging infrastructure, exemption of road tax, financial incentives Purchasing cost, operation cost, maintenance cost, subsidy policy, environment effect, performance, safety, driving range, battery material, electricity source, charging infrastructure Government incentives Fuel economy, emission reduction, driving range, charging infrastructure, exemptions of vehicle tax, free parking, bus lane access Charging time, driving range, charging infrastructure, environmental effect, fuel cost, policy incentives Subsidy policy, driving range Purchasing cost, fuel cost, total cost, financial benefit Driving range, purchasing cost, fuel cost, charging time Driving range, top speed, fuel cost, purchasing cost, battery life, charging stations, carbon emission Charging infrastructure, charging time, vehicle type Policy incentives, charging infrastructure, swappable battery Economic benefits, policy, high energy efficiency, cheap electricity Purchase price, range, type, performance Driving range, performance, purchasing price
Green electricity, financial savings
Economic incentives Battery capacity, purchasing cost, driving range
Pioneering-ecological spirit Attitudes, experience, environmental beliefs (continued on next page)
Environmental concerns Social influence Attitudes, emotions, subjective social norms, perceived behavioral control Symbols, social status Value, experience, subjective social norm
Attitudes, experiences, preference
Environmental concerns Experience, attitudes, environmental awareness
Symbol, environment concerns
Attitudes, perception awareness, technology awareness, experience, interest
Experience, environmental beliefs
Experience Symbolic meaning of driving EV, personal resistance, first-hand experience
Pro-environmental lifestyle, technology oriented lifestyle and openness to change Concerns about air pollution and the environment, interest in new technology Attitudes, subjective social norms, perceived behavioral control, individual preferences Subjective social norm, collective efficacy, experience Environmental concerns, driving habits
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Hedonic attributes, symbolic attributes, proenvironmental identity Experience Environmental concerns Openness, conscientiousness, agreeableness, symbolic value, environmental concern
As detailed in the materials and methods section, some BEV performance aspects, such as driving range and refueling time, are diﬀerent from CFVs and other EVs. In addition, they are also diﬀerent in terms of energy consumption, greenhouse gas reduction and government policy. Therefore, this section mainly reviews the impact of these objective factors.
Schuitema et al. (2013)
Schneidereit et al. (2015) Sierzchula et al. (2014) Skippon and Garwood (2011) Tamor et al. (2013) Tamor et al. (2015) Zhang et al. (2011)
  
Number of driver's licenses, number of vehicles
3.3.1. Technical features The driving range of BEVs was found to be one of the major barriers for limiting consumer adoption [14,15]. In the study of Jensen et al. , they hypothesized that the negative inﬂuence of driving range on consumer adopting intentions is due to their inaccurate perception. However, this hypothesis was not veriﬁed by comparing empirical data collected before and after respondents experienced BEVs. They stated that this is indeed caused by the mismatch between the facts and consumer expectations of BEV driving ranges. Accordingly, unless the driving range is greatly improved, it is diﬃcult to promote BEVs to private consumers. However, in fact, the driving range of BEVs has already met the demand for short trips . The reasons why consumers have become so sensitive to driving range are as follows. The ﬁrst reason is the demand for long trips. By comparing BEVs with E-REVs, Schneidereit et al.  found that the reason why consumers have higher adopting intentions for E-REVs is because E-REVs can meet their demand for several long trips per mouth. This reﬂects the fact that consumers signiﬁcantly care about the total driving range of BEVs. Graham-Rowe et al.  also believed the limited-range mobility of BEVs is not competent enough for long trips. The second reason is the high range preferences. Presently, consumer range preferences for BEVs are always found to be higher than their real demand. The reason is consumers are more familiar with the high driving range of CFVs, which makes consumers produce a similar preference . Researchers have investigated how to mitigate the negative eﬀect of the BEV limited driving range. Franke and Krems  employed an experimental method to analyze data from 79 participants who had driven a BEV for 3 months; the results showed that their range preferences decreased in this period, which indicated that practical experience can play an important role in increasing adopting intention. In addition, if consumers’ travel times and distances can be reasonably planned, their range anxiety can also be decreased . As well as the driving range, the charging problem, including long charging time and insuﬃcient charging infrastructures, is regarded as another technical barrier . Pierre et al.  stated that unless the charging time can be obviously shortened and charging infrastructures can be easily obtained, their negative impact cannot be ignored. Considering the charging time is diﬃcult to be shortened radically in a short period of time, Ko and Hahn  suggested that swappable batteries could be used to enhance the consumer intention. In terms of charging infrastructures, Jensen et al.  asserted the impact of likelihood to charge at the working place, and the number and location of charging stations in the public domain are very important. On the contrary, consumer demands for charging stations in the public
  
Sang and Bekhet (2015) 
Gender, age, education, income Income, education
Driving range Charging infrastructure, Economic incentive policies Environmental effect, driving range, purchasing cost, charging infrastructure, charging time, acceleration, responsiveness, smoothness, low noise Battery cost, driving range Driving range, charging infrastructure Government policies
Performance, driving range, purchasing cost
Social influence, environmental concerns, experience Gender, age, education, marital status, income, living place
Fuel economy, environmental effect, safety, vehicle power, reliability and early availability of vehicle in the market Performance attributes, financial benefits, charging infrastructure Prakash et al. (2014) 
living place, size of family Gender, age
Psychological factors Situational factors
3.3. Situational factors
adopting intentions. Furthermore, the results of Plötz et al.  appear to conﬁrm this also. They showed that Germans in rural and suburban areas are more likely to own garages, since they tend to recharge at home. As for other family factors, family members and the number of driving licenses are found to signiﬁcantly inﬂuence consumer intentions. According to Zhang et al. , the more family members that can drive, the more likely consumers are to adopt a BEV. The results of Plötz et al.  showed that consumers in rural or suburban multimember families are more likely to be adopters, since they can save money using BEVs due to their long mileage and city driving advantages.
Table 1 (continued)
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3.3.4. Government policy In the market promotion stage, the mass adoption of BEVs heavily relies on government support. Current government policies mainly include ﬁnancial subsidies, preferential tax, free parking and driving privileges . All these policies were demonstrated as positively inﬂuencing consumer adoption intentions in many previous studies [5,10,18,45]. And these eﬀects were found to increase when more powerful policies were issued . From an economic perspective, Aasness and Odeck  believed that adopting of BEVs by consumers is the consequence of the economic incentives of current policies, which can help consumers save a lot of money. Diﬀerent policies also diﬀered in their impact. The results of Ko and Hahn  showed that consumers who have high willingness to adopt a BEV favor lumpsum subsidies instead of installments. Similarly, Bjerkan et al.  suggested that up-front cost decreasing measures, such as exemption or reduction of purchase tax and value-added tax, are the most powerful incentives in encouraging adoption. However, exemption from tolls and bus lane driving privileges are the only inﬂuencing factors for some consumers . Nevertheless, some studies found that the impact of policies was not as powerful as expected. In the study of Hoen and Koetse , policies including road tax exemption and ﬁscal incentives were found to contribute to adoption intentions, but were far less eﬀective in eliminating consumers’ doubts about performance attributes of BEVs. Furthermore, Green et al.  suggested that the objective of current policies, which aim at realizing the large-scale application of BEVs, is targeted at mainstream consumers. Considering that these policies are proven to be ineﬃcient and costly, policies focusing on niche markets would be more eﬀective.
domain, such as supermarkets, parks and restaurants, are demonstrated to be small by Skippon and Garwood  and Plötz et al. . They found that consumers are more willing to charge BEVs at home, so domestic charging infrastructures are more important to them. Presently, charging infrastructures in both public and domestic domains are insuﬃcient, but more focus should be placed on domestic domains by governments. As Skippon and Garwood  noted, consumers who use a BEV are willing to pay a modest investment for upgrading their domestic charging supplies and future policies could supply some subsidies to encourage them. Creative designs for charging infrastructures, which have less of an impact on consumer habits, should also be discussed in the future. As a new automobile product, BEVs are quite diﬀerent from CFVs in terms of technicality. All these diﬀerences could be potential inﬂuences. Most researchers accept that the three main barriers to BEV adoption are driving range, charging time and charging infrastructures; however, the impact of others technical factors, such as top speed, battery life, after sales maintenance, trunk space, acceleration, responsiveness, smoothness and low noise, have also been veriﬁed [21,30–34].
3.3.2. Cost Compared with CFVs of a similar conﬁguration, the high front purchasing cost of BEVs is discussed as a barrier to adopt BEVs in the majority of studies, whereas the lower operational cost is asserted in favor of BEV adoption [34–37]. Dumortier et al.  believed the ﬁnancial beneﬁts from reduced energy consumption and low price of electricity can oﬀset much or all of the front premium cost in the long term. Educating consumers of the real savings of BEVs by describing how to calculate the savings and the cost of the fuel and other costs over the ownership period are very eﬀective in inducing adoption. However, Carley et al.  asserted that, despite the savings, consumers will not be inclined to adopt BEVs because of the disadvantages of BEV attributes. In addition, although signiﬁcant money can be saved by the energy conservation of BEVs , only consumers with long driving ranges can completely beneﬁt from it . Furthermore, the study of Dumortier et al.  indicated that consumers value the current expense more rather than the long term savings of BEV. Although the beneﬁts of BEV in terms of cost may attract some consumers, these beneﬁts are not apparent in the short term. Therefore, other short-term measures, such as larger economic incentives, should encourage consumers more .
3.4. Psychological factors Deciding whether or not to adopt a BEV not only depends on situational factors, but also on psychological factors. In previous studies, the eﬀect of psychological factors was proven to be signiﬁcant [36,48]. Psychological factors are important because they can aﬀect adoption intentions directly, as well as mediate the objective factors . For instance, it is usually how consumers feel that aﬀects their vehicle adopting decisions instead of purchasing costs. Therefore, to more comprehensively understand the factors aﬀecting adoption intention, it is instructive to summarize the psychological factors, some of which are discussed below. 3.4.1. Experience Experience generally, and that of owning an automobile in particular, is the major determinant of the intention to adopt a BEV. As suggested by Schulte et al. , experience encompasses general life experience, knowledge of related topics, education, and practical experience with a speciﬁc product. In research on consumer adoption of BEVs, this construct mostly includes knowledge of and practical experience with BEVs. Some studies used empirical investigation to collect data from consumers directly, and measured practical experience by asking who drove BEVs or had driven them in the past. Burgess et al.  found that practical experience was an important factor in converting the attitude of consumers from one of skepticism to that of support and acceptance. First-hand experience enhances consumers’ understanding and can change their stereotype of BEVs. By driving BEVs, consumers begin to perceive them more positively, especially in terms of speed, acceleration, and low noise. Besides, practical experience can help in demonstrating that BEVs are practical vehicles and oﬀer a usable and viable option. Barth et al.  introduced respondents to two scenarios, namely buying and car sharing. In the second option, consumers use BEVs only when needed. The respondents were assigned to one of the two scenarios at random and were asked the same questions. The results showed a positive relationship between the intention to adopt a BEV and (1) practical experience and (2) BEV-
3.3.3. Environmental attributes One important reason why BEVs are promoted worldwide is their oil independence and emission pollution control. These environmental advantages have been reported by a number of studies and have been tested as driving factors for consumer adoption intentions [12,39]. Beck et al.  found that environmental protection, which overcomes the impact of energy saving, has become one important factor for attracting consumers. Therefore, the promotion of BEVs should not only emphasize the characteristics of energy conservation; environmental protection may also help improve the adoption rate to a large extent . However, opposing opinions have also been proposed. Graham-Rowe et al.  found that environmental protection is not the main concern for some consumers when considering purchasing a BEV. Axsen et al.  further suggested that some consumers suspect the ability of BEVs to provide environmental protection. The reason for this is that much pollution is created in the process of producing batteries and electricity, as well as the pollution caused by the discarded batteries. Therefore, the implementation of carbon labels could satisfy the consumers, and the reduction of battery pollution, such as recycled batteries and green electricity, could eﬀectively enhance consumer adoption intentions [42,43]. 323
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behavior is the result of careful consideration, and behavioral change is a complex mental process. Attitudes cannot inﬂuence human behavior directly, but do so indirectly by aﬀecting individual intention. Besides, intention is also inﬂuenced by subjective social norm and perceived behavioral control, and these two factors are reviewed in depth in Sections 3.4.4 and 3.4.5. Moons and De Pelsmacker  and Afroz et al.  both analyzed the impact of attitudes under the framework of the TPB. In the former study, attitudes towards BEVs were measured as the sum of the number of positive choices among the following dichotomous items: good/bad, like/dislike, clever/stupid, nice/not nice, useful/useless, suitable/unsuitable. In the latter study, dimensions of attitudes included the consumers’ beliefs about BEV being fuel eﬃcient as well as their perceptions of BEVs as being able to decrease the consumption of oil and reduce the emissions of greenhouse gases. Both studies asserted that the intention to adopt BEVs can be well explained by the TPB, with the direct impact of attitudes being the highest among that of all the variables.
related knowledge. Practical experience with BEVs counts much more than mere knowledge. Many scholars have used experiments instead, in which participants are given short-time access (usually 3–6 months) to BEVs. By collecting data before and after such ﬁrst-hand experience of BEVs, the eﬀect of practical experience can be observed. However, the results of this method diﬀered from those of direct empirical investigations. Jensen et al.  showed that consumers learn much more about BEVs through practical experience, which changes their preference signiﬁcantly. In particular, such experience changed their preferences related to driving range, top speed, cost, battery life, and charging the vehicles at city centers and train stations. However, consumer attitude did not change after experiencing BEVs. Jensen et al.  further indicated that with more practical experience, respondents had a more positive attitude towards the driving performance of BEVs than before and did not consider charging a serious problem. However, they were concerned more about the ability of BEVs to meet their travel demands. The results also showed that BEVs were chosen much less often after the consumers’ ﬁrst-hand experience of the vehicles. Besides, both of these studies pointed out that future analysis should not be based on respondents without practical experience. The results obtained by Bühler et al.  are similar to those obtained by Jensen et al. [21,51] and showed that experience enhances consumer perceptions of BEVs signiﬁcantly: many of the advantages, such as driving enjoyment and low operational costs, become more obvious whereas several disadvantages, such as low noise, seem to matter less. Practical experience did have positive impacts on consumer perception of BEVs and on the intention to recommend BEVs to others, but not on attitudes and adoption intentions. Conversely, Franke and Krems  believed that after experiencing BEVs, consumers would have fewer doubts because ﬁrst-hand experience can help consumers to appreciate the actual driving distance of BEVs and to convince them that their travel demands would be meet, thereby improving the consumers’ adoption intention. From the above ﬁndings, it is clear that although experience did not inﬂuence consumers’ attitude and intention in some studies, it was generally seen as a positive factor. To enhance consumer adoption intentions, activities such as test drives and car sharing are suggested as ways to appeal to potential consumers.
3.4.3. Emotions The above studies suggest that attitude is generally seen as a kind of cognitive valuation, which helps in deciding whether it is economical or meaningful to perform a certain action from the viewpoints of costs, beneﬁts, and other non-monetary considerations such as impact on the environment. However, some scholars maintain that attitudes do not refer to cognition alone, but also include aﬀective components [54–56]. These aﬀective components, also called emotions, are a type of attitude or experience to help in judging whether some objects or actions meet someone else's needs and reﬂect not only positive attitudes such as love, approval, and pride but also negative attitudes such as worry, shame, and disgust. Given their importance in predicting various behaviors, some studies are now beginning to analyze the eﬀect of emotions on consumers' adoption of BEVs. Moons and De Pelsmacker  added emotions to the TPB. In their study, emotions include three aspects: visceral, behavioral, and reﬂective. The ﬁrst, visceral, emotion is the consumers’ responses toward such attributes of BEVs as the throb of the engine, acceleration, information on the dashboard, aesthetics of the interior, appearance, and the possibility to attain high speeds. The second, behavioral, emotion is the consumers’ expectations of enjoying the overall ambience and being relaxed while driving. The third, reﬂective, emotion is the consumers’ perception in terms of low cost, environmental protection, and economy in fuel consumption. All these emotions are measured by asking respondents for the extent to which the three aspects contribute to their positive emotions while driving a BEV. Results showed that the eﬀects of emotions are similar to those of attitudes: consumers who have positive emotions are usually more willing to adopt BEVs and vice versa. Besides, Graham-Rowe et al.  reported that consumers express diﬀerent emotions while trying out BEVs. For instance, some consumers felt awkward or negative when comparing BEVs with CFVs and others felt ashamed to be driving a BEV because they could not drive as fast or as conﬁdently as those driving a CFV. Schuitema et al.  researched the impact of hedonic attributes, which are deﬁned as emotional experiences such as joy or pleasure stemming from the use of new technologies, on consumers adoption intentions. The results showed that the intention to adopt BEVs was stronger if the consumers had positive perceptions of their hedonic attributes.
3.4.2. Attitudes When individuals have some experience, they cannot convert that experience into an adoption intention directly: positive or negative attitudes are formed after thinking carefully about these experiences. If individuals hold positive attitudes (e.g. “I believe driving CFVs violates the environment.”), this may encourage their adoption intention of BEVs. Conversely, negative attitudes (e.g. “I believe there is no diﬀerence between using BEVs and CFVs as far as the environment is concerned.”) are likely to discourage people from adopting BEVs. Therefore, attitudes are always regarded as key psychological factors that inﬂuence the adoption intention. In general, attitudes are deﬁned as individual mental experiences that reﬂect entrenched likes or dislikes as well as individual positive or negative evaluations of particular behaviors. Plötz et al.  analyzed attitudes related to many aspects: technology aﬃnity, the environment, comfort, and image and found that attitudes were the most eﬀective predictors – better than demographic and situational factors – of a consumer's intentions to adopt a BEV. Beck et al.  examined the relevant attributes in a new way, referred to as best–worst scaling. In this method, respondents need to choose attitudes from a set of attitudinal statements. It is found that without considering the role of attitudes properly, consumer intentions cannot be evaluated and predicted accurately: only an in-depth analysis focusing on the relationship between attitudes and intentions can provide a more accurate reference point for future policymaking. In addition, some studies analyzed the impact of attitudes based on the theory of planned behavior (TPB), which holds that human
3.4.4. Perceived behavioral control Individual behaviors are not only powered by the processes of evaluation and expectations that follow cognition and emotion but also rely on the supporting role of control belief. In the TPB, Ajzen proposed the variable of Perceived behavioral control (PBC) and suggested that this control belief stems from two sources: the inner force, such as selfsuﬃciency, and the outer force that controls external conditions . For example, after a speciﬁc attitude is formed, people need to evaluate 324
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technology spread. Rogers  argued that diﬀusion is inﬂuenced by communication (e.g. mass media and oral communication) over time among individuals in a social system. Therefore, in the process of studying DOI, subjective social norms are usually considered. Except for this variable, Barth et al.  incorporated three other norms, namely descriptive, injunctive, and provincial. If a norm refers to what other people commonly do, it is a descriptive norm. If a norm refers to what is generally agreed or disagreed within the group, it is an injunctive norm. If a norm refers to the impact that behavior of other people can have on our judgments or predictions when those others encounter a similar conditions, it is a provincial norm. Besides, collective eﬃcacy, which refers to the belief that an in-group is able to inﬂuence crucial aspects of its environment, was also included in the study. After controlling for the impact of economic and demographic variables, Barth et al.  found that the impact of the above four norms and collective eﬃcacy was higher than that of economicrelated factors. (3) Technology acceptance model. The technology acceptance model (TAM) is a theory used for analyzing how users come to accept and use a technology. Due to its widespread use in research on the acceptance of technology, the TAM has been continually studied and expanded. Venkatesh and Davis  proposed an expanded TAM by adding variables including subjective social norms. Because BEV is an emerging technology, Peters and Dütschke  used this expanded TAM to explain its adoption intentions. Consequently, subjective social norms have also been conﬁrmed as a signiﬁcant inﬂuence.
their conﬁdence and abilities to purchase or use a BEV by overcoming the perceived disadvantages. The stronger the PBC, the greater the likelihood of consumers buying and using a BEV. From the current literature, most scholars discuss the PBC under the framework of TPB. In the study by Moons and De Pelsmacker , dimensions of PBC included such considerations as whether consumers could aﬀord BEVs, whether they could use BEVs in their daily life (given such issues as charging problems, limited driving range, and the cost of driving), and the likelihood of CFVs being banned in the near future. That study found positive relationships between PBC and adoption intention, although the impact of PBC was smaller than that of attitudes and emotions. Afroz et al.  arrived at similar results, although they measured PBC diﬀerently, asking the respondents whether the following four aspects were important to them: politeness and respectfulness, self-control (such as being restrained and self-disciplined), a clean and tidy environment, and hard work and aspirations. The results indicated that in deciding whether to adopt BEVs, consumers try to assess their ability to adapt to the changes that the switch to BEVs entails, and that PBC positively inﬂuences adoption intention but is less important than attitudes. 3.4.5. Societal inﬂuence Since the 1990s, many scholars began discussing human behaviors from the sociological perspective and maintained that a given behavior is not only a personal but also a societal activity. Whether individuals adopt a speciﬁc behavior is inﬂuenced by what others do. A behavior is generally believed to be reasonable if others around us also behave similarly, because most people will constantly modify their behavior in light of public opinion . For example, if most people adopt CFVs, it is diﬃcult to blame these adopters, and adopting BEVs instead may be seen as weird or unsociable. At this point, societal inﬂuence plays an important role in a consumer's intentions to adopt a BEV . Societal inﬂuence is the degree of importance an individual attaches to the approval of his or her actions by others (such as family members and friends). Such actions include adopting a speciﬁc innovation or technology. Utilizing the framework of reﬂexive layers of inﬂuence, Axsen et al.  categorized societal inﬂuences into three processes: diﬀusion, translation, and reﬂexivity. Diﬀusion describes interpersonal inﬂuence as delivered through the ﬂow of functional information about a new product among individuals. The second, translation, represents the negotiation of a new product's perceived advantages and signiﬁcance in a social environment. The third, reﬂexivity, refers to individuals connecting their awareness and evaluation of the product to their lifestyle and self-image. Empirical results showed that respondents are aﬀected by at least one of these processes. Societal inﬂuence is an umbrella concept and encompasses peer pressure, subjective social norms, neighbor eﬀects, collective eﬃcacy, and social culture. Many of the studies of BEV adoption pay attention to the subjective social norms, which refer to individual perception of exception or pressure from speciﬁc external references. These references can be intangible or stipulated by rules. The eﬀect of subjective social norms from diﬀerent theories is summarized below.
3.4.6. Symbols Before individuals decide on the type of car to buy, they may consider not only the price, performance, fuel consumption, comfort, and other objective factors, but also its being a symbol of self-image and social status, which are more likely to be related to their selfidentity. A symbol is a mark, sign, or word that indicates, signiﬁes, or is understood as representing an idea, object, or relationship. Symbols allow people to go beyond what is known or seen by making combinations between otherwise very diﬀerent notions and experiences. According to the social role theory, an individual used to compare herself or himself with others to increase her or his self-recognition and self-evaluation . In the study of BEV adoption behavior, this comparison is embodied as a symbol of identity and social status. By adopting BEVs, messages such as “save energy”, “protect the environment”, “reduce carbon emissions”, “be responsible to society”, and “care for other people” can be delivered to the adopter's community. These messages are intentionally or unintentionally conveyed, and can increase some potential consumers’ preferences for BEVs , which has a positive impact on adoption intention. Noppers et al.  studied the eﬀect of instrumental, environmental, and symbolic attributes on the adoption of BEVs. Their study covered eight symbolic attributes, which reﬂect the inﬂuence of BEVs on self-identity and social status, such as ‘‘BEVs show who I am’’ and ‘‘BEVs improve my social status’’. When asked directly, respondents suggested that symbolic attributes were less important than instrumental and environmental attributes. However, results from the regression method indicated that such symbolic attributes can predict adoption intention to a large extent. This further suggests that the importance of symbolic attributes for adopting BEVs may not be well recognized by consumers. Based on the self-image congruency theory, Schuitema et al.  considered two identities: pro-environmental and an authority on cars: the pro-environmental consumers put a greater store on the value of BEVs as symbols and were more likely to generate more positive perceptions of BEVs. Given some of the shortcomings of BEVs, popularizing BEVs by exploiting their value as a symbol appears to be an eﬀective method.
(1) Theory of planned behavior. Based on the TPB, Moons and De Pelsmacker  measured subjective social norms through two aspects, interpersonal and external: the former measured the opinion of people around respondents about their BEV adoption behavior, and the latter was used for reﬂecting the eﬀect of media. Afroz et al.  used a diﬀerent approach, which involved asking the respondents whether CFVs can lead to air pollution, smog, and emissions of greenhouse gases. Both the studies indicated that subjective social norms are a major inﬂuence, after attitude, although Moons and De Pelsmacker  also found their eﬀect to be less than that of emotions. (2) Diﬀusion of innovation. The theory of diﬀusion of innovation (DOI) seeks to explain how, why, and at what rate new ideas and 325
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Although these factors have been reviewed separately in this paper, some of them are usually analyzed together. It is suggested that the intention for consumers to adopt BEVs is likely to be a mixture of demographic, situational and psychological factors. In addition, present studies usually model diﬀerent factors in parallel and the hierarchical relationship between them is ignored. Therefore, further understanding of BEV adoption intentions not only depends on more comprehensive studies, but also on the interactions between diﬀerent variables. There are some defects in the process of data collection and further studies are required. Due to the diﬃculty in measuring adoption intention, present studies generally use survey methods. In the course of the survey, some people have never been in touch with BEVs, and this lack of understanding may limit the validity of their response. Although some respondents were given a short term practical experience, and some studies selected BEV users for the survey, the small sample of these studies may cause biases. Whether they can represent the majority of consumers, and whether the results concluded from them can be generalized to the majority remains to be explored. In addition, the present surveys are usually carried out for one-time or short-term periods, which cannot reﬂect the diachronic changing of economic development, social culture, automotive technology, government policy, ecological environment, social status of consumers, as well as their dynamic impact on adoption intention. Therefore, more representative and larger scale dynamic surveys are needed in the future. Limitations with regards to demographic factors are discussed as follows. Although some studies found that individual income was not an inﬂuence, the possible reasons for this were not mentioned. One exception is Bjerkan et al. , but the reasons they suggested are based on a qualitative analysis and are not tested by real data. In addition, some family factors that may inﬂuence adoption intention were not examined in recent studies, such as the structure of family members , especially numbers of older members and children . Families with more of these members usually concern more about internal space, comfort and safety, which may inﬂuence their adopting intention. Driving range, charging problem and purchasing cost are the main situational barriers. Studies that focus on how to guide consumers to reasonably plan their travel time and distance, how to add and complete charging infrastructures to satisfy consumers’ demand, and how to educate consumers to calculate total cost according to their driving habits, can better provide data to solve these barriers. Meanwhile, with constantly developing technology, the technical features of BEVs are also changing. Therefore, the ever-changing impact of BEV technical features is very important for researchers, policy makers and manufacturers to know, because it can help improve the strategies in popularizing and marketing BEVs. As environmental attributes of BEVs are drivers of adoption intention, an important researching area here is how to relieve consumers’ doubts. In terms of government policy, understanding the impact of speciﬁc policies in some countries and regions can help improve future policy making [66,67]. Consumers are the targets of BEV related policies; their opinion and perception about present policies can aﬀect their adoption intention . Studies that provide understanding of the evaluation of policies and those that examine the factors that satisfy or dissatisfy consumers should be undertaken. Finally, the limitations in psychological factors are discussed. Although some studies suggested that increasing consumers’ practical experience through certain activities would improve the likelihood of BEV adoption, their organization and implementation is not easy. This is mainly because there are too many stakeholders involved, such as consumers, manufacturers, retailers and governments. Designing wellorganized activities and examining their eﬀect could yield important results and implications. Furthermore, many studies have shown the importance of societal inﬂuence; however, few studies discuss how to
3.4.7. Other psychological factors Apart from the above factors, a few other psychological factors have also been analyzed, and among these, the eﬀects of environmental concerns, values, and lifestyle have been veriﬁed. Environmental concern is always regarded as the extent to which consumers are aware of environment-related problems and whether they are in favor of solving the problems or express their intention to contribute personally to the solution . Generally speaking, people who are environmentally aware are more willing to realize environmentally conscious behavior. Sang and Bekhet  asserted that adopting BEVs is no exception, and concern for the environment has positive eﬀects on adoption intention. Similarly, Pierre et al.  stated that people with pioneering-ecological tendencies tend to use BEVs, since they are more sensitive to protection of the environment and energy conservation. Schuitema et al.  suggested that consumers who consider themselves pro-environmental are more likely to be BEV adopters. It is clear that environmental concerns play a positive role in inducing consumers to adopt BEVs, and the current studies generally suggest helping consumers to be highly concerned about the environment through appropriate publicity and education. Peters and Dütschke  veriﬁed the signiﬁcant eﬀect of values on adoption intention. Values can be deﬁned as the standards that individuals use to judge and select speciﬁc behavior as well as to evaluate themselves and others. Because values reﬂect an individual's sense of what is right and what is wrong or what “ought” to be, they inﬂuence the choices made by the individual. Consumers with altruistic values tend to regard vehicle choice as an environmental issue, whereas consumers with egoistic values tend to choose vehicles based on selfinterest and beneﬁts. Lifestyle can denote the interests, opinions, behaviors, and behavioral orientations of an individual or a group. The concept of lifestyle is a combination of intangible or tangible factors. Tangible factors relate speciﬁcally to demographic variables, whereas intangible factors concern the psychological aspects of an individual. The concept originated from the theory of market segmentation, which focuses on the diﬀerences between living standards of individuals. Axsen et al.  proposed that if products are inconsistent with an individual's living standards, the individual may refuse to adopt those products. Results based on a sample of 711 households in San Diego showed that BEVs in general appeal more to individuals with pro-environmental and technology-oriented lifestyles. Various theories such as the TPB, DOI, TAM, self-image congruency, protection motivation, and lifestyle include some factors that have not been highlighted in this review. However, in general, psychological factors are more complex than situational and demographic factors. 4. Conclusions As shown in this review, researchers from many countries have engaged in analyzing the factors inﬂuencing BEV adoption intentions. Once these factors are accurately identiﬁed, the formulation and implementation of guide policies can be provided accordingly. In this review, 40 papers related to BEV adoption intention were selected from 1846 papers using a two-step identiﬁcation process. Based on the study of those 40 papers, the factors inﬂuencing BEV adoption intentions were divided into three categories: (1) demographic factors including individual variables (e.g. gender, age, education, income, and occupation) and family variables (e.g. vehicle ownership, accessibility to plugin vehicles at home, population, and the number of driving licenses); (2) situational factors such as technical features, cost, environmental attributes, and government policy; and (3) psychological factors such as experience, attitudes, emotions, perceived behavioral control, societal inﬂuence, and symbolic value. After reviewing the above factors, the following suggestions are oﬀered for improving the utility of future studies. 326
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use this to induce consumers into adopting BEVs. Future work should focus on ways to guide consumers into adopting BEVs; this can be achieved through fostering and establishing a social culture, which may promote the implementation of suitable government policies. In addition, the symbolic value of BEVs is diﬀerent among countries, due to cultural diﬀerences. Future work should focus on examining the symbolic value of BEVs in diﬀerent countries. As for emotions, which were found to be very important in inﬂuencing adoption intention, the theorization of emotions is still lacking. In addition, emotions are treated as variables at the same level of other psychological factors (e.g. attitudes), and the relationship between them needs to be researched further. Although other researchers were less concerned by other psychological factors, they should not be disregarded in future studies. These factors may change with the development of contemporary society, and should be considered in future studies. Acknowledgments This study was supported by the Fundamental Research Funds for the Central Universities (No. 2017BSCXB24). References  Zhang Y, Peng H, Liu Z, Tan W. Direct energy rebound eﬀect for road passenger transport in China: a dynamic panel quantile regression approach. Energy Policy 2015;87:303–13.  Zhang X, Xie J, Rao R, Liang Y. Policy incentives for the adoption of electric vehicles across countries. Sustainability 2014;6(11):8056–78.  Raslavičius L, Azzopardi B, Keršys A, Starevičius M, Bazaras Ž, Makaras R. Electric vehicles challenges and opportunities: lithuanian review. Renew Sustain Energy Rev 2015;42:786–800.  Bjerkan KY, Nørbech TE, Nordtømme ME. Incentives for promoting battery electric vehicle (BEV) adoption in Norway. Transp Res Part D: Transp Environ 2016;43:169–80.  Sang Y, Bekhet HA. Modelling electric vehicle usage intentions: an empirical study in Malaysia. J Clean Prod 2015;92:75–83.  Al-Alawi BM, Bradley TH. Review of hybrid, plug-in hybrid, and electric vehicle market modeling studies. Renew Sustain Energy Rev 2013;21:190–203.  Rezvani Z, Jansson J, Bodin J. Advances in consumer electric vehicle adoption research: a review and research agenda. Transp Res Part D: Transp Environ 2015;34:122–36.  Lane B, Potter S. The adoption of cleaner vehicles in the UK: exploring the consumer attitude–action gap. J Clean Prod 2007;15(11–12):1085–92.  Hidrue MK, Parsons GR, Kempton W, Gardner MP. Willingness to pay for electric vehicles and their attributes. Resour Energy Econ 2011;33(3):686–705.  Hackbarth A, Madlener R. Consumer preferences for alternative fuel vehicles: a discrete choice analysis. Transp Res Part D: Transp Environ 2013;25:5–17.  Carley S, Krause RM, Lane BW, Graham JD. Intent to purchase a plug-in electric vehicle: a survey of early impressions in large US cites. Transp Res Part D: Transp Environ 2013;18:39–45.  Prakash N, Kapoor R, Kapoor A, Malik Y. Gender Preferences for alternative energy transport with focus on electric vehicle. J Soc Sci 2014;10(3):114–22.  Plötz P, Schneider U, Globisch J, Dütschke E. Who will buy electric vehicles? Identifying early adopters in Germany. Transp Res Part A: Policy Pract 2014;67:96–109.  Egbue O, Long S. Barriers to widespread adoption of electric vehicles: an analysis of consumer attitudes and perceptions. Energy Policy 2012;48:717–29.  Hackbarth A, Madlener R. Willingness-to-pay for alternative fuel vehicle characteristics: a stated choice study for Germany. Transp Res Part A: Policy Pract 2016;85:89–111.  Li X, Clark CD, Jensen KL, Yen ST, English BC. Consumer purchase intentions for ﬂexible-fuel and hybrid-electric vehicles. Transp Res Part D: Transp Environ 2013;18:9–15.  Erdem C, Şentürk İ, Şimşek T. Identifying the factors aﬀecting the willingness to pay for fuel-eﬃcient vehicles in Turkey: a case of hybrids. Energy Policy 2010;38(6):3038–43.  Zhang Y, Yu Y, Zou B. Analyzing public awareness and acceptance of alternative fuel vehicles in China: the case of EV. Energy Policy 2011;39(11):7015–24.  Peters A, Dütschke E. How do consumers perceive electric vehicles? A comparison of german consumer groups. J Environ Policy Plan 2014;16(3):359–77.  Bühler F, Cocron P, Neumann I, Franke T, Krems JF. Is EV experience related to EV acceptance? Results from a German ﬁeld study. Transp Res Part F: Traﬃc Psychol Behav 2014;25:34–49.  Jensen AF, Cherchi E, Mabit SL. On the stability of preferences and attitudes before and after experiencing an electric vehicle. Transp Res Part D: Transp Environ 2013;25:24–32.  Tamor MA, Moraal PE, Reprogle B, Milačić M. Rapid estimation of electric vehicle acceptance using a general description of driving patterns. Transp Res Part C: Emerg Technol 2015;51:136–48.
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