Barriers to the adoption of electric cars: Evidence from an Italian survey. (November 2020)

• Record Type: Journal Article
• Authors: Giansoldati, Marco; Monte, Adriana; Scorrano, Mariangela
• Is Part Of: Energy policy. Volume 146(2020)
• Publication Date: 2020-11
• Subjects: Electric cars -- Barriers -- Principal component analysis -- Cluster analysis -- Polychoric correlation matrix; Energy policy -- Periodicals; Politique énergétique -- Périodiques; Electronic journals; 333.79
• DOI: 10.1016/j.enpol.2020.111812
• Languages: English
• ISSNs: 0301-4215

Abstract

Abstract: Italy has a very low level of uptake of electric cars (ECs), equal to 0.6% for the year 2019, despite significant efforts put in place by policy makers to stimulate their use. This paper investigates the barriers to wider EC diffusion via a survey administered in 2019 to a representative sample (N = 870) of the Italian population. We discuss and rank the barriers, aggregate them via principal component analysis (PCA) on the basis of the polychoric correlation matrix, perform a cluster analysis and analyse the socio-economic determinants of the respondents. The findings of this paper suggest a series of improvements that could be made by various actors. To overcome the financial barriers to EC uptake, Italian policy makers should reinforce incentives at the national and local levels and car manufacturers should bring to the market cheaper ECs belonging to the A and B segments. The charging-related barriers require investments on fast charging stations along the main toll highways and a new regulation regarding multi-house dwellings. Finally, reliable and complete information is needed to enhance knowledge about the technological and environmental pros and cons of ECs. Highlights: We assess the barriers for a wider uptake of electric cars in Italy. Survey respondents rank the still insufficient stations as the major barrier. Safety, acceleration, technology and driving pleasure are not a barrier. The principal components analysis unveils a general aversion towards electric cars. Cluster analysis identifies four homogeneous groups of respondents.