The PhD projects aims to better understand the social embedding of transport choices and to make this knowledge available for use in the agent-based transport demand model mobiTopp.
Digitalization and automation are often highlighted as a window of opportunity to achieve a transition toward a more sustainable transport system. However, impact assessments on the basis of modelling often entail detailed assumptions about the extent to which new services are made available, but are full of uncertainties about interrelated societal developments and corresponding effects on the demand side. The social contexts in which technologies are embedded and the dynamics within them are typically excluded from modelling frameworks. The absence of the social makes it difficult to assess socio-technical transitions. Social contexts shape opportunities and constraints of mobility choices likewise. Therefore, a better understanding of the changeability and stability of mobility patterns allows better assessing the transformative potential of such innovations. In order to take account of the social contexts, model structures should be created that go beyond their usual application in transport planning.
Social network analysis is used to examine obligations and opportunities associated with relationships among actors. Social networks are understood very broadly as a web of relationships formed by individual, corporate, and collective actors. Accordingly, a social network consists of relationships with close friends and family members as well as with certain supermarkets or the workplace.