This empirical study explores determinants of consumer resistance towards self-driving cars by considering the level of car autonomy. Based on a literature review, this research distinguishes between the effects of functional and psychological barriers on behavioral intention. Several studies have clarified that technological innovation in particular, need to overcome several barriers as a first step, before (potential) users will even start to favor buying such an innovation. Data was collected by an online-survey in December 2017, resulting in an effective sample of 182 respondents. The sample has an average age of M = 24.46 years with 70% male participants and a total of 95% were in possession of a driver license. To ensure that the respondents are able to differentiate between the characteristics or levels of autonomous driving, two independent samples were surveyed on the basis of different scenarios (low and high autonomy). In addition, a structural equation model (SEM) was used to perform an analysis of measurement and structural models using SmartPLS 3.0 software. The findings show that functional and psychological aspects explain consumer resistance towards self-driving cars. Interestingly, the results of a moderation analysis illustrate that the effects of both psychological barriers (i.e., image and traditions/norms) on behavioral intentions vary between a high and a low level of car autonomy. In detail, for those who evaluated the high autonomy scenario (N=92), significant results can be presented for both psychological barriers. Surprisingly, no significant relationship between risk barrier as functional barrier and behavioral intention can be verified. Conclusively, marketers and OEM’s, respectively, should elaborate specific strategies for the different levels of autonomous driving that will be introduced to the market over the next decades. To support these findings, it would be helpful to test the model with a larger sample and new items to test for a potential usage barrier. Moreover, it would be prudent to test additional scenarios and levels of autonomous driving.

• Tabea Sippel(Technische Universität Braunschweig, Germany)