Privacy concerns when using augmented reality face filters? Explaining why and when use avoidance occurs

Abstract Augmented reality face filters (e.g., Snapchat) are ubiquitous in today's market. Yet, we know little about the impact of individuals' concerns for their own and others' privacy and sharing biometric facial data while interacting with such augmented reality face filters. Our study aims to uncover whether privacy concerns affect responses toward augmented reality face filter apps, as well as the underlying mechanisms of this process, specifically perceived usefulness and flow. First, a survey study shows that individual perceptions of privacy concerns indirectly decrease use intentions and word‐of‐mouth via perceived usefulness and flow. Second, integrating construal level theory, we demonstrate in an experimental study that users report lower use intentions and word‐of‐mouth (again mediated through perceived usefulness and flow) when providing a concrete (vs. abstract) privacy policy. Additionally, we offer evidence for boundary effects and show that these patterns emerge only when users interacted with highly hedonic filters. The research demonstrates that privacy concerns related to use of augmented reality face filters indirectly affects future behavioral intentions and explains the phenomenon through lenses of the privacy paradox and construal level theory. By accounting for how people process information, the research evidence novel mechanisms for interrupting the privacy paradox.