Heterogeneity of autonomous vehicle adoption behavior due to peer effects and prior-AV knowledge

Despite all the promising benefits, the adoption of fully autonomous vehicles (FAVs) is expected to require a long transitional process. While innovators and early adopters tend to adopt the technology fast, most will gradually adopt the technology after varying periods. Meanwhile, today’s social networking technologies have strengthened the influence of peer effects and caused noticeable changes to decision-making behavior. To date, there is relatively little study on how peer effects influence autonomous vehicles (AVs) adoption. The current paper explores how AV adoption is influenced by various factors, especially by different levels of individual susceptibility and prior-AV knowledge . Susceptibility is a latent variable measuring to what extent individuals will follow the influence of their peers in AV adoption. Prior-AV knowledge is another latent variable that measures people’s knowledge about AVs, which will further impact their price sensitivity. A stated preference (SP) survey was carried out in five cities in China. 1132 new car buyers were surveyed, resulting in 3855 valid records for vehicle preference. The Integrated Choice and Latent Variable (ICLV) Model is used to measure the susceptibility and prior-AV knowledge attributes, and identify their contribution to the heterogeneity of AV adoption intentions. The results show that many demographic factors influence the adoption of AVs. Younger individuals, those with higher education levels, higher income, and more driving experience are more readily influenced by their peers. High market penetration has a significant influence on FAV adoption, but to a varying degree depending on the individual susceptibility level. People with prior-AV knowledge, who are more likely to be older drivers, have no children under 18, have higher incomes and higher education levels, are found to be less sensitive to vehicle price.