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.

In recent years, the surge in the adoption of electric vehicles has played a vital role in reducing fossil fuel consumption and greenhouse gas emissions. However, limited cross-national research has been conducted on the determinants of electric vehicle adoption in developing and developed countries. This study examines the factors influencing the intention to adopt electric vehicles in India (378 participants) and Spain (265 participants). This study develops an integrated model that combines the unified theory of acceptance and use of technology (UTAUT2) and the value-belief-norm (VBN) model while accounting for the impact of national culture. The model is tested using structural equation modeling. The results indicate the integrated UTAUT2-VBN model is a valuable tool for explaining the differences in adoption intention across cultures. Moreover, the national cultural system plays a significant moderating role in most relationships within the model. This study offers valuable insights into the factors influencing electric vehicle adoption in different cultural contexts, which can inform policies and strategies to promote sustainable transportation.

Internal combustion engine vehicles are a key source contributing to urban air pollution. In order to reduce noxious emissions and reliance on fossil fuels, governments and the automobile industry have started promoting the adoption of electro mobility (EM) options over the last few years, albeit with limited success in terms of market penetration. This study aimed to improve the current understanding of factors influencing customers’ intentions to adopt EM options. Building on the theories of perceived value and reasoned action, this study posits a behavioural model based on four dimensions of perceived value and two technical performance characteristics of EM vehicles with regards to their influence on customer attitudes towards EM options, as a precursor to purchase. The model was tested empirically using structural equation modelling analysis using data gathered through an online survey of 404 consumers in Spain. The results of this study showed that emotional issues, product price, vehicle acceleration and low engine noise levels have a considerable impact on consumer attitudes, which, in turn, have a positive impact on purchase intentions of EM vehicles. However, quality and social value were not found to have a positive influence on consumer attitudes. On the basis of this research it is recommended that, in order to promote the use of EM vehicles, governments and manufacturers alike should make better use of emotional issues in their social and product marketing strategies, as well as focusing on specific product attributes such as performance (e.g., vehicle acceleration and low engine noise levels) and value for money in terms of energy consumption.

The transportation sector's substantial greenhouse gas emissions necessitate solutions that promote sustainability. One potential approach is the higher adoption of electric vehicles (EVs). This study aims to empirically investigate the determinants of customers' intentions to adopt EVs, with a strong focus on the concept of green value. Framed in adaption‐innovation theory and based on the customer perceived value model, this research analyses the influence of emotion, price, quality, social, green value and green advertising skepticism on purchase intention and customer engagement. Employing a PLS approach to fit the conceptual model to data obtained from an online survey of potential customers in Germany, Spain, and Chile ( N = 791), we found evidence of a substantial and significant impact of green advertising skepticism on purchase intention and green perceived value. Notably, the social value of electric vehicles is the most crucial driver of customers' buying intention and is more important than price and green perceived value.

The adoption of electric vehicles (EVs) by consumers is regarded as a key strategic goal for the reduction in transport-related air pollution levels. Although sales of EVs continue to rise year on year, generally, the attainment of the strategic goals set by various governments for the adoption of EVs remains a distant target. The purpose of this study is to identify the customer profile of early adopters of EVs in Spain: one of Europe’s largest economies, yet the country with the lowest uptake of EVs at present. The analysis presented here is based on an online survey of 404 potential consumers of EVs in Spain. A cluster analysis of the data was performed based on a set of three socio-demographic characteristics (gender, age, and income), one psychographic (green moral obligation—GMO) and two EV attributes (price and driving range). The results of this analysis showed that there exist two segments with respect to higher or lower customer intentions related to the adoption of EVs. These findings represent a theoretical contribution to current understanding of the customer profile of adopters of EVs and will contribute to the development of communication and retail strategies aimed at customers fitting the profile of early adopters of new technologies.