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Journal ArticleDOI

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

TLDR
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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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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Citations
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A meta-analysis of the importance of the driving range in consumers’ preference studies for battery electric vehicles

TL;DR: In this paper, a meta-analysis of the studies that evaluate the importance attributed by the consumers to the driving range of the battery electric vehicles (BEVs), including primary studies up to the year 2018, was performed.
Posted ContentDOI

Potentials for Electric Vehicles in France, Germany, and India

TL;DR: In this paper, the potential for diffusion and take-off of electric vehicles varies in different countries depending on some framework conditions like infrastructure and energy generation as well as on individual factors measured by surveys in the different countries.
Journal ArticleDOI

Reducing the time loss bias: Two ways to improved driving safety and energy efficiency.

TL;DR: This study investigated the debiasing effect of two educational interventions, the Paceometer and a newly designed Pop-up assistant, in a video-based controlled-access highway driving scenario and confirmed the improvement of time loss estimations for bothdebiasing tools and the superiority of the Pop- up assistant.
Book ChapterDOI

To Cluster the E-Mobility Recharging Facilities (RFs)

TL;DR: A case study of 13 charging points with 48 EV users located in the inner urban core of a metropolitan area in North East England, the city of Newcastle upon Tyne, incorporating space-time analysis of the EV population is presented.
References
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Journal ArticleDOI

The theory of planned behavior

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.
Journal ArticleDOI

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

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.
Journal ArticleDOI

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

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.
Journal ArticleDOI

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

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.
Journal ArticleDOI

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

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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