Consumer 3D printing is on the rise and has the potential to significantly change the transport and logistics sector. Current literature on 3D printing and transport studies does not provide a systematic model of the impact of 3D printing on transport and related (policy relevant) areas, such as traffic safety, location decisions, accessibility and environmental effects. Based on a literature review and two rounds of expert consultation, we propose and refine a conceptual model as a way to approach this gap in the literature. The expert consultation yields that the conceptual model comprises the relevant and important elements for assessing the impact of 3D printing on transport and transport-related challenges. Location, needs and transport resistance are important: (a) city-level hubs are the most likely locations for 3D printers because they can coordinate material flows and gather expertise; (b) mass-individualisation and personification dictates the needs for 3D printers; (c) distribution networks will be organised more efficiently, less empty vehicles, but raw materials still need shipping. However, experts’ opinions diverged on the impact of 3D printing on transport volumes and environmental impacts.

The dynamics of protection in the context of socio-technical niches have remained under-researched. In this paper we conceptualise the process of policy learning in the context of transitions. We show that a variety of actors inside and outside a technological niche have to learn about the implications and effects of regulations aimed at protection of niches. We analyse this process of policy learning in two cases: high-need drugs and electric vehicles. We conclude that both regulators and the regulated need to learn about the width and depth of protection measures, their duration, the specific set of tools used, and their legitimisation. A crucial issue of implementing protective regulation is the question on what level of aggregation protection measures need to be applied. Learning is often part of the negotiation process between the protector and the protected, but in many cases learning only takes place after policies have been implemented.