Abstract

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.

摘要

电动汽车因其减少污染的能力而脱颖而出。然而，尽管有积极影响，电动汽车的销售并不活跃。本研究的目标有两个：首先，通过基于计算智能的算法的实施来确定预测电动汽车购买的变量；其次，将这些结果与消费者行为和汽车行业的两个专家小组进行对比。对西班牙 404 名潜在消费者的信仰、态度和购买意向进行了实证研究。结果表明，范围、激励和可靠性是购买意愿最可靠的预测因素。同样地，专家认为，选择这三个变量就足以了解电动汽车潜在买家的购买意愿。此外，它还为政策制定者和私营公司在电动汽车营销过程中的决策提供了有用的信息。