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logo embedterlabsBetter Embedded Labs for
More Synergistic Sustainable
Urban Transformation Planning

Context

The municipality has a long-term vision of reducing car parking spots in the city whilst increasing urban flora ('from grey to green'), whilst promoting active mobility (i.e. walking & cycling) for health reasons. However, there is strong resistance from retailers and employers to reduce space for car mobility in the city.

Doing What?

The experiment temporarily transforms parking lots from a large employer in the city centre into urban flora, whilst facilitating car alternatives for the last urban miles (through a multi-modal travel info app, bicycle sharing scheme, parking at the border of the city etc.).
The largest employer in the city centre is the University of Maastricht. The department responsible for parking has confirmed its participation

Learning what?

The experiment seeks to learn (1) what can be effective and acceptable alternatives for car mobility for commuters to the city centre. How can space that comes available best be used? (2) what do the results mean for mobility policy in Maastricht (e.g. does this approach deserve scaling up, and if so, how)?

Who is involved?

Maastricht University (lead), Municipality Maastricht, Maastricht Bereikbaar (MB) (=public private partnership).
The municipality brings in policymakers and parking lots at the border of the city. MB arranges the car alternatives (either shared bicycle or public transport).

How are the experiments 'better-embedded'? (general)

The general approach here is that the experiment is better embedded in a (broader than currently customary) learning network or 'learning community' with citizens, urban planners & policymakers and other relevant stakeholders, divided into two groups: Lab participants and a Lab reflection group. They jointly formulate learning questions and monitor the lessons learnt.

How are the experiments 'better-embedded'? (city-specific)

The learning network around the experiment includes the head of the mobility department, the spatial department, the health department as well a senior representative of the employer. The findings from the ULL can inform the policies of the city as well as the employer regarding urban parking and green spaces as well as new, collaborative modes of urban planning, involving all stakeholders.

How is the impact of the experiment evaluated, both in terms of learning processes and policy mix?

We evaluate the learning processes and the impact of the experiment on the urban (mobility) policy mix through (1) Before-and-after stakeholder workshops (with participants and a reflection group) and will inquire into (first) expected and (later) experienced challenges and learning outcomes of the experiment. (2) Individual semi-structured interviews with a representative share of participants and reflection group members, and also policymakers who were neither participants nor reflection group members. (3) Ethnographic work (already ongoing) will study qualitative change in the learning network engaged in the experiment.

How does the experiment support transformative capacity?

Our approach extends learning processes beyond the small group of enthusiastic lab practitioners with a reciprocal effect: it draws on questions and knowledge from the (potentially conflicting) established policy and planning logics, yet, at the same time, includes a broader range of stakeholders it diffuses the lab lessons better into the mainstream policy development community. We test how this learning network enhances the transformative capacity of the city.