This research uses a practical attempt to explore further determinants of consumer behaviour needs to be considered in modern TAM’s. Based on This study applies a qualitative and a quantitative method. On the one hand, qualitative data was collected with the World Café approach and on the other hand, the quantitative data was collected by an online-survey, resulting in an effective sample of 126 respondents. The findings show that consumers attitude towards self-driving cars is positive and negative. Those descriptive variables for the context of autonomous driving have to be identified as a first step. Conclusively, implications and future research topics are presented.
자율주행자동차의 발전은 자동차 자체뿐만 아니라, 사람들의 삶을 지금까지와는 다른 차원으로 변화시켜줄 것이다. 운전자의 운전 관여가 축소되거나 배제되는 고도자율주행기술이 현실화되면 이에 대한 새로운 법제를 구축하는 일이 중요하다. 이와 함께 스스로 상황에 맞는 판단을 하고 목적지까지 주행하는 자율주행자동차의 등장으로 기존의 인적요소에 의해 발생하던 사고는 대폭 감소할 것으로 예상되나, 자율주행에 의한 운행 중 사고가 발생하는 경우 운전자와 제조업자의 책임 소재, 손해배상 등 기존에 존재하지 않은 새로운 유형의 사고 처리와 관련된 다양한 법적 문제가 발생할 가능성이 커졌다.
이 글에서는 현행 법체계 하에서 자율주행자동차의 운행이 허용되는지, 관련 서비스의 제공이 제도적으로 뒷받침되는지 살펴보았다. 또한, 주요 국가의 자율주행자동차 운용에 관한 입법례와 우리나라의 제도적 현황을 검토하고, 자율주행자동차로 인한 사고 및 책임 소재에 대한 고찰을 통해, 우리 현행 법규에 대한 개선방안을 모색하였다.
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.