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Barriers to the adoption of electric cars: Evidence from an Italian survey

handle: 11368/2971444
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.
- University of Trieste Italy
Barrier, Electric car, Principal component analysi, Polychoric correlation matrix, Cluster analysi, Electric cars; Barriers; Principal component analysis; Cluster analysis; Polychoric correlation matrix
Barrier, Electric car, Principal component analysi, Polychoric correlation matrix, Cluster analysi, Electric cars; Barriers; Principal component analysis; Cluster analysis; Polychoric correlation matrix
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).54 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
