Abstract
Battery Electric Vehicles are regarded as highly important to reach environmental goals, such as CO2 savings in the transport sector. Despite governments making strong efforts to encourage their adoption and diffusion, sales still remain at a notoriously low level. One of the reasons may be the lack of a deeper understanding of the differences among potential adopters of Battery Electric Vehicles. To close this research gap, the authors segment adopter groups in a new way. They simultaneously use preferences for product attributes and personal characteristics to identify and characterize adopter groups of Battery Electric Vehicles. In this way, adopters can be effectively segmented, uncovering a more precise picture of adopters’ needs. Moreover, the authors introduce a three-step-procedure combining inputs from an adaptive choice-based conjoint experiment with a questionnaire. This approach can be used to segment adopter groups of other eco-innovations, as well. Based on three adopter groups of Battery Electric Vehicles (Utilitarian Savers, Performance Seekers, and Green Technologists), the authors develop tailored measures for decision-makers in policy and management to foster the adoption and diffusion of Battery Electric Vehicles.
Highlights
Eco-innovations, such as Battery Electric Vehicles (BEVs), have gained increasing attention over the past years [1,2,3]
In Step 2, we used the relative importance of the product attributes from the adaptive choice-based conjoint (ACBC) experiment to conduct ANOVA
We identified three different adopter groups, i.e., ‘Utilitarian Savers’, ‘Performance Seekers’, and ‘Green Technologists’
Summary
Eco-innovations, such as Battery Electric Vehicles (BEVs), have gained increasing attention over the past years [1,2,3]. To decrease road transports’ dependence on oil-derived fuels, and to maximize the positive effect of BEVs on the environment, a broad range of consumers need to adopt BEVs [13,14]. A deeper understanding of the adoption of BEVs and the heterogeneity of adopters is needed. Other approaches differentiate between adopters and non-adopters of BEVs [17,18]. More detailed approaches differentiate adopter groups based on either their preferences for product attributes [19] or their personal characteristics [20,21]
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