On the Road to an Electric Mobility Mass Market—How Can Early Adopters be Characterized?

Abstract

Different field trials and corresponding acceptance studies with new technologies were carried out between 2010 and 2013 at the Chair of Energy Economics at the Karlsruhe Institute of Technology (KIT). Those involved Electric Vehicle (EV) users, Liquefied Petroleum Gas (LPG) and Compressed Natural Gas (CNG) vehicle users as well as persons with strong interest in EV and smart energy home technologies. In order to characterize early adopters the same item-sets concerning attitudes regarding climate change, prices and innovations as well as corresponding socio-demographic characteristics were used throughout all these studies. Survey datasets originating from these studies are joined to be analyzed together. Regression methods are applied in order to characterize early EV adopters based on a subsample of EV company car users in the French-German context. A binary logistic regression model explaining private EV purchase intentions is developed. According to this model, early private EV adopters are likely to have a higher level of income, to have a household equipped with two or more cars and to travel more than 50 km a day, not necessarily by car. This model additionally shows that possibilities to experience EV (e.g. by test drives) are important leverages to support adoption of EV by private car buyers. Respondents who already decided to privately purchase an EV show significantly lower general price sensitivities than the LPG and CNG vehicle users.

Appendix A

See Tables 3, 4, 5 and 6.

Table 3 Rotated component matrix

Table 4 Adjusted significance levels concerning differences of the samples’ levels of environmental sensitivity, innovativeness and price sensitivity

Table 5 Variables in the equaton of model P _c

Table 6 Variables in the equaton of model P _a