Beate Kubitz was awarded a fellowship in June 2020 to study how rural and suburban transport could unlock Mobility as a Service (MaaS).

Beate’s research will focus on Greater Manchester – the area served by Transport for Greater Manchester (TfGM) and the Greater Manchester Authority (GMA) – as an example of how transport tends to work across the larger urban area.  

The project will analyse travel patterns in outer suburbs and periurban areas and map data to lived experience. How realistic is it that people outside the urban core can make the journeys they need to without using cars? And what is the impact of this on city centres? It will look at new mobility and active travel infrastructure as ways of addressing connectivity in less dense areas and assess the impact they could have both on their immediate surroundings but also on the urban core.

Beate is a transport consultant with experience in future mobility and the role it plays in carbon reduction through research, innovation and policy development. Her experience includes developing plans for Mobility Hubs for Calderdale Metropolitan Borough Council, evaluating electric mobility for Manchester City Council, Manchester Metropolitan University and the University of Manchester as well as research and analysis on Mobility as a Service solutions for Leeds City Region Future Mobility Strategy and Cambridgeshire and Oxfordshire County Councils.

Previously she worked for the shared transport organisation CoMoUK (previously Carplus Bikeplus), and automotive technology startup CarTap. She edits the Annual Survey of Mobility as a Service (for Landor Links) and has contributed to policy development on data and mobility for organisations including the Open Data Institute and the British Standards Institution. As a consultant she has also evaluated car clubs and bike share for shared transport operators.

Recently she set up a volunteer zero carbon cargo bike delivery service in the small town of Todmorden. Her approach to transport is hands on, data driven and informed by lived experience as well as models.