Analysis of the Electric Vehicles Adoption over the United States

Soltani-Sobh, Ali; Heaslip, Kevin; Stevanovic, Aleksandar; Bosworth, Ryan; Radivojevic, Danilo

doi:10.1016/j.trpro.2017.03.027

Cited by 70 publications

(25 citation statements)

References 25 publications

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“…According to Chu et al (2019), lower recharging cost is an important motivation for buying an EV. Thus, in comparison, the low price of electricity increases the adoption of EV (Soltani-Sobh et al, 2017). It was found that there were significant savings in societal costs and total cost of ownership when compared to diesel vehicles (Bor en, 2019).…”

Section: Context Factorsmentioning

confidence: 99%

Adoption of electric vehicles: Which factors are really important?

Higueras-Castillo

Guillén

Herrera

et al. 2020

International Journal of Sustainable Transportation

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Electric vehicles stand out for their ability to reduce pollution. However, electric vehicle sales have not been brisk despite their positive effects. The objective of this study is twofold: first, to determine the variables that predict the purchase of an electric vehicle from the implementation of an algorithm based on computational intelligence; second, to contrast these results with two panels of experts in consumer behavior and the automobile sector. An empirical study was carried out with 404 potential consumers in Spain with regard to their beliefs, attitudes and purchase intention. The results show that range, incentives and reliability are the most reliable predictors of purchase intention. Likewise, the experts posit that the selection of these three variables would be sufficient to know the purchase intention of potential buyers of electric vehicles. In addition, it provides useful information for policy makers and private companies for decision making in the electric vehicle marketing process.

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Section: Context Factorsmentioning

confidence: 99%

Adoption of electric vehicles: Which factors are really important?

Higueras-Castillo

Guillén

Herrera

et al. 2020

International Journal of Sustainable Transportation

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“…Scholars with the view of promotion believe that government subsidies can have a positive impact on corporate financial performance, market share, and environmental awareness. Soltani-Sobh et al (2017) consider that the government incentives are positively correlated with the Electric vehicle market share growth in the US. Deng et al (2020) divide government subsidies into selective subsidies and non-selective subsidies, suggesting that selective subsidies can help companies maintain high performance, while the effectiveness of non-selective subsidies depends on the intensity of regional legal protection and market competition.…”

Section: The Role Of Government Subsidiesmentioning

confidence: 99%

The Effect of Technology Innovation on Corporate Sustainability in Chinese Renewable Energy Companies

et al. 2021

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Technology innovation has become the main driving force of China’s economic growth. Sustainable development highlights the harmonious symbiosis of the economy and the ecological environment. Renewable energy companies characterized by technology-intensive and environmental friendliness are playing an increasingly important role in achieving economic development while alleviating environmental pressure. Therefore, this paper selects the A-share renewable energy listed companies in China between 2014 and 2019 as samples, using the fixed-effect model and the logit model to explore the effect of technology innovation on corporate sustainability. We find that technology innovation has a positive effect on both financial sustainability (FS) and social and environmental sustainability (SES). Due to the imbalance of regional social and environmental development and different degrees of emphasis placed on environmental and social responsibility, the positive impact of technology innovation on SES is heterogeneous between the east and the central and west regions. Moreover, as the strategic emerging industry, although the renewable energy industry is granted lots of subsidies from the government, the results show that when government subsidies exceed the threshold, the effect of technology innovation on FS is weakened. Government subsidies have a negative moderating effect on the relationship between innovation and SES. Furthermore, we subdivide government subsidies into government subsidies beforehand (GSB) and government subsidies afterwards (GSA). We reveal that the threshold effect of government subsidies mainly comes from GSA, while the moderating effect of government subsidies is caused by GSA and GSB. This paper is an expansion and enrichment of current studies on sustainable development and also puts forward feasible suggestions for the government to formulate precise and effective subsidy policies to stimulate technology innovation.

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“…However, the effects of other incentive policies are controversial. For example, the effectiveness of free parking on EV adoption is found to be significant by Ferguson et al (16) (25,26), and Soltani-Sobh, et al (27). Such highly aggregate studies ignore spatial variation in EV adoption and cannot decipher the effects of zonal characteristics.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Another group of EV adoption literature focuses on aggregate predictions at an international/national/state level using historical EV sales or vehicle registration data. Some recent examples include Sierzchula et al ( 21 ), Jin et al ( 22 ), Narassimhan and Johnson ( 23 ), Lutsey et al ( 24 ), Vergis and Chen ( 25 , 26 ), and Soltani-Sobh, et al ( 27 ). Such highly aggregate studies ignore spatial variation in EV adoption and cannot decipher the effects of zonal characteristics.…”

Section: Literature Reviewmentioning

confidence: 99%

Evaluating Fuel Tax Revenue Impacts of Electric Vehicle Adoption in Virginia Counties: Application of a Bivariate Linear Mixed Count Model

Jia

Jiang

Chen

et al. 2019

Transportation Research Record: Journal of the Transportation R

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Increasing electric vehicle (EV) shares and fuel economy pose challenges to a fuel tax-based transportation funding scheme. This paper evaluates such fuel tax revenue impacts using Virginia as a case study. First, a bivariate count model is developed using vehicle registration data in 132 counties from 2012 to 2016. Model results indicate strong correlation between presence of battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs) on a county basis. Counties with higher percent of males are associated with higher BEV (but not PHEV) counts. In contrast, higher average commute time is predicted to increase the number of PHEVs in each county, but not BEVs. Greater population density, population over 65, population with graduate degrees, and household size are found to increase PHEV and BEV counts, whereas more households with children is associated with fewer EVs. The analysis forecasts 0.6–10% statewide EV adoption by 2025, with an adoption rate of 2.4% in the most likely scenario. Nine scenarios, combining different predictions of EV adoption and fuel economy improvement, project 2025 statewide fuel tax revenue to decrease by 5–19%, relative to 2016 receipts. Furthermore, model results suggest that, on average, a light-duty vehicle in a rural area will pay 28% more in fuel taxes than its urban counterpart by 2025. The framework proposed here provides a reference for other regions to conduct similar analysis using public agency data in the vehicle electrification era.

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Analysis of the Electric Vehicles Adoption over the United States

Cited by 70 publications

References 25 publications

Adoption of electric vehicles: Which factors are really important?

Adoption of electric vehicles: Which factors are really important?

The Effect of Technology Innovation on Corporate Sustainability in Chinese Renewable Energy Companies

Evaluating Fuel Tax Revenue Impacts of Electric Vehicle Adoption in Virginia Counties: Application of a Bivariate Linear Mixed Count Model

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