Content
This study examines the human factors influencing the acceptance of road-facing dashcams in the freight sector. A research model grounded in the Technology Acceptance Model and the Privacy Calculus Model was developed and tested with data collected through an online survey of 157 truck drivers in Germany. The model was analyzed using partial least squares structural equation modeling (PLS-SEM). The findings indicate that perceived usefulness plays a pivotal role in dashcam acceptance, driven by social norms, functionality, and control. In contrast, perceived risks and privacy concerns do not significantly impact the intention to adopt road-facing dashcams. Thus, the technologies' benefits outweigh the individual data protection concerns, making the use at the truck driver's workplace favorable. This research contributes to the broader discourse on how behavioral factors influence interactions with road-facing dashcams in transportation logistics. Managerial insights are provided for the road freight sector regarding the adoption of camera-based assistance systems.