Consumer Preferences and Willingness to Pay for Data Privacy in Automated Vehicles

Although automated vehicles (AVs) are promising to revolutionize the urban mobility, the public raises substantial concerns over the ineffective management of data privacy, while data is crucial for AVs to enhance algorithm and assign legal responsibilities. Given the research gap, we conduct a stated preference experiment to investigate consumer preferences for data privacy of AVs. Discrete choice analysis based on a mixed logit model shows that price premium for data privacy protection, data ownership, and location of data storage significantly affect consumers’ choice of AVs, while the types of collected data and frequency of data collection have insignificant influence. Further, a latent class model identifies two distinct segments for adopting AVs, one showing open-minded attitude towards data privacy or having privacy fatigue, who even oppose collecting no data for AVs, and the other segment with negative data privacy experience and lack of trust towards AVs preferring AVs collecting only location data or no data. We make contributions by revealing not only preferences for data privacy protection of AVs but also the preference heterogeneity for data privacy by different consumer groups. Our research offers rich implications for automakers and policymakers to manage users’ data privacy of AVs.