Barriers to widespread adoption of electric vehicles: An analysis of consumer attitudes and perceptions
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.
About: This article is published in Energy Policy.The article was published on 2012-09-01. It has received 1207 citations till now.
Citations
More filters
TL;DR: In this paper , the authors used the theory of planned behavior (TPB) model to construct a model of purchase intention impact mechanism for electric vehicles (EVs), which considered consumer attitude (AT), subjective norms (SN), cognitive states (CS), product perception (PA), perceived behavioral control (PBC), non-monetary incentive policy (NMIP), as well as monetary policy (MIP).
Abstract: Pakistan's government has been pushing for electric vehicles adoption to decrease energy consumption and pollution. Acceptance of large numbers of electric vehicles will undoubtedly help to ease important issues such as carbon pollution and fuel reliance and to improve economic success. Pakistan is now considering switching from non-Electric vehicle to Electric vehicle (EVs) in spite of numerous cross-sectoral and multifaceted roadblocks. The theory of planned behavior (TPB) model was utilized in this study to construct a model of purchase intention impact mechanism for electric vehicles (EVs). It considered consumer attitude (AT) and subjective norms (SN), cognitive states (CS), product perception (PA), perceived behavioral control (PBC), non-monetary incentive policy (NMIP), as well as monetary policy (MIP). In Pakistan, a questionnaire was administered to potential customers. A total 511 valid survey responses were collected. The factors affecting EV buying intent were examined by Structural equation modeling (SEM) using SPSS AMOS. According to the results no factors tested negative, most of the factors were significant beneficial outcome on consumers' intents to buy electric vehicles (EVs). These findings were discussed with policy recommendations and conclusion.
8 citations
TL;DR: The electric vehicle (EV) industry has been promoted by a series of incentive policy measures in China to reduce both the consumption of petroleum fuels and the emission of greenhouse gases as discussed by the authors.
8 citations
TL;DR: In this paper, the changes in consumers' purchase motivations and latent demand for hybrid and plug-in electric vehicles in the wake of such programs by analyzing the past 11 years of new vehicle buyer survey data in the USA with more than 1 million respondents.
Abstract: Consumer adoption of fuel-efficient vehicles is a crucial step in improving energy efficiency of the light-duty vehicle sector. To promote adoption, policymakers have employed various demand- and supply-side policies including incentives, fuel economy standards, zero emission vehicle mandate, among others. This paper measures the changes in consumers’ purchase motivations and latent demand for hybrid and plug-in electric vehicles in the wake of such programs by analyzing the past 11 years of new vehicle buyer survey data in the USA with more than 1 million respondents. The analysis reveals that electric vehicles—including hybrids, plug-in hybrids, and pure battery electric, collectively termed xEVs—had the potential to secure as much as ~ 11% of the US market in 2015, but the actual market share was only one-third of this. A narrowing of the consumer’s valuation gap between buyers of non-xEVs and xEVs for purchase motivations—including fuel economy, environmental friendliness, technical innovation, and price—is responsible for the increase in the latent demand for xEVs. The term valuation gap refers to the difference between the average rating given by non-xEV and xEV buyers for a particular purchase motivation question in the survey. The closer the ratings, the smaller will be the valuation gap. Policy instruments such as sales-weighted fuel economy target show strong correlation with the consumer valuation gap. In combination with demand-side policies that make xEVs more accessible to mainstream consumers, they could be considered as viable tools if policymakers are seeking to nudge consumers toward xEVs.
8 citations
TL;DR: Investigating the influence of driving in intense traffic conditions while considering the ambient temperature and driving behavior on BEV energy efficiency in a field study supports the hypothesis that traffic conditions significantly impact the vehicle’s efficiency.
Abstract: While the influence of several factors on battery electric vehicle (BEV) efficiency has been investigated in the past, their impact on traffic is not yet fully understood, especially when driving in a natural environment. This paper investigates the influence of driving in intense traffic conditions while considering the ambient temperature and driving behavior on BEV energy efficiency in a field study. A total of 30 BEV inexperienced drivers test drove a 2017 Volkswagen eGolf on a route with various road types in two different traffic intensity scenarios: During morning commute hours with higher traffic congestion and lower congestion hours throughout the middle of the day. Results support the hypothesis that traffic conditions significantly impact the vehicle’s efficiency, with additional consumption of approximately 4–5% in the high traffic scenario. By creating and comparing driving in traffic to an underlying base case scenario, the additional range potential by avoiding traffic for this particular vehicle can be quantified as up to seven miles. New patterns of BEV efficiencies emerged, which can help stakeholders understand how eco-driving can be strategically improved by selecting trip times and routes that avoid high traffic intensity.
8 citations
TL;DR: In this paper , the authors developed a machine learning framework to examine spatial disparities in EVCS placements by using a predictive approach, and compared the most accurately predicted EVCS placement density with a spatial inequity indicator to quantify how evenly these placements would be for Orange County, California.
Abstract: Electric vehicles (EV) are an emerging mode of transportation that has the potential to reshape thetransportation sector by significantly reducing carbon emissions thereby promoting a cleaner environment and pushing the boundaries of climate progress. Nevertheless, there remain significant hurdles to the widespread adoption of electric vehicles in the United States ranging from the high cost of EVs to the inequitable placement of EV charging stations (EVCS). A deeper understanding of the underlying complex interactions of social, economic, and demographic factors which may lead to such emerging disparities in EVCS placements is, therefore, necessary to mitigate accessibility issues and improve EV usage among people of all ages and abilities. In this study, we develop a machine learning framework to examine spatial disparities in EVCS placements by using a predictive approach. We first identify the essential socioeconomic factors that may contribute to spatial disparities in EVCS access. Second, using these factors along with ground truth data from existing EVCS placements we predict future ECVS density at multiple spatial scales using machine learning algorithms and compare their predictive accuracy to identify the most optimal spatial resolution for our predictions. Finally, we compare the most accurately predicted EVCS placement density with a spatial inequity indicator to quantify how equitably these placements would be for Orange County, California. Our method achieved the highest predictive accuracy (94.9%) of EVCS placement density at a spatial resolution of 3 km using Random Forests. Our results indicate that a total of 74.18% of predicted EVCS placements in Orange County will lie within a low spatial equity zone – indicating populations with the lowest accessibility may require the highest investments in EVCS placements. Within the low spatial equity areas, 14.86% of the area will have a low density of predicted EVCS placements, 50.32% will have a medium density of predicted EVCS placement, and only 9% tend to have high EVCS placements. The findings from this study highlight a generalizable framework to quantify inequities in EVCS placements that will enable policymakers to identify underserved communities and facilitate targeted infrastructure investments for widespread EV usage and adoption for all.
8 citations
References
More filters
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.
65,095 citations
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.
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.
1,064 citations
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.
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.
595 citations
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.
551 citations
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).
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.
541 citations