SmartwayZ.NL and Argaleo together developed Mobility Matching, a first application on the Digitwin platform: a method that shows for 3,712 work locations in the Netherlands how accessible they are without a car, and more importantly, which measure delivers the most impact there. The application runs nationwide on open data and can be enriched per location with an employer’s own data. The provincial government offices of Noord-Brabant are the first fully developed case.
The problem is not a lack of data
Governments, employers and mobility partners now have plenty of mobility data. Maps with travel times, cycling potential, public transport supply and origin-destination patterns abound. Yet the question that really matters in an administrative meeting often remains unanswered: which measure will actually change travel behaviour here?
That question is harder than it looks, because the answer differs per location. Two business parks can score similarly on paper for accessibility and still require completely different interventions. In one place, the gain lies in promoting e-bikes or adjusting an employer scheme. In another, in higher public transport frequency or a better multimodal connection. Without that refinement, investments are distributed based on intuition, not on impact.
What the application does
Mobility Matching combines public and private data sources into an integrated picture of accessibility, car dependency and the scope for influencing mobility behaviour. The application brings together, among other things:
- business parks and work locations (IBIS), neighbourhoods (CBS)
- public transport stops and stations with actual peak-hour service (GTFS)
- fast cycle routes, existing and planned (NDW)
- bicycle accidents and road safety (BRON)
- park-and-ride locations and multimodal facilities (OSM)
The added value is not in those layers themselves; each of them is publicly available. The value emerges by crossing accessibility with adaptability: how many of today’s car trips realistically have an alternative, and how open to influence is behaviour at that location. On that basis, every work location is assigned an opportunity class, from promising match to structural mismatch.
Matching: every work location is assigned an opportunity class by crossing accessibility with adaptability
In the current configuration, this produces the following picture for the Netherlands as a whole: 605 work locations fall into the promising match class, 799 are promising but lack the organisational capacity to act, 178 require policy or investment, 688 have limited potential and 1,442 show a structural mismatch. Together this covers almost three million jobs. The thresholds are adjustable, so a province or transport region can set its own priorities without losing comparability.
That second category is the most interesting from a governance perspective. More than eight hundred locations where infrastructure and travel distances allow an alternative, but where nobody takes the initiative. That is not an infrastructure problem but an organisational one, and it calls for a very different kind of measure than asphalt or an extra bus.
Nationally applicable, locally refinable
Mobility Matching is built in two layers. The foundation is a generic analysis of the multimodal accessibility of work locations based exclusively on open data. As a result, the method works everywhere in the Netherlands, immediately, without a municipality or province having to supply datasets first.
If an organisation does have its own mobility data, a tailored layer is added on top. Employees’ home locations, current modal choices, use of schemes. This sharpens the picture considerably: not just what is theoretically possible, but what can actually shift for these people at this location.
Data and infrastructure around a work location: fast cycle routes, public transport stops with peak-hour service, bicycle accidents and park-and-ride locations in one view
The Noord-Brabant provincial offices as the first case
For the first tailored application, the provincial government offices of Noord-Brabant were used. By enriching the generic analysis with employees’ home locations and current modal choices, it became clear which mode is most open to influence here and which measures deliver the most impact.
What the case shows above all is that the cause of car dependency hides in details that remain invisible on an accessibility map. The bicycle or e-bike looks like a realistic alternative from a distance, until it turns out that good parking facilities are missing. There is a bus stop around the corner, but with an average waiting time of thirty minutes. Precisely those details determine whether someone leaves the car at home, and precisely those details therefore determine which measure makes sense.
‘Two work locations that score similarly on paper require completely different measures in practice. Mobility Matching makes that difference visible. That turns investing in sustainable mobility into a targeted choice instead of a distribution.’
Joost de Kruijf, SmartwayZ.NL
Why this fits the way we work
Mobility Matching follows the same line as our other work in the mobility domain: translating complex, fragmented data into a shared and objective working picture that parties can base decisions on together. Earlier, we developed a nationwide methodology for the accessibility of daily amenities for SmartwayZ.NL and the province of Noord-Brabant, scoring 14,515 CBS neighbourhoods in a mutually comparable way. Mobility Matching does the same for work locations, with the emphasis on what you can do next.
It is therefore not a replacement for existing models and traffic studies, but an instrument that sits earlier in the process: it helps determine where to focus attention and which type of measure is promising, before detailed modelling begins. For this development, SmartwayZ.NL and the province of Noord-Brabant chose Argaleo’s Digitwin platform as the foundation.
Nationwide view of work locations, coloured by a chosen indicator, here the distance to a railway station
What comes next
In the coming period, SmartwayZ.NL and Argaleo will focus on scaling Mobility Matching nationally. The method works nationwide and the first case is in place; the next step is real-world application. To that end, we are entering into conversations with provinces, transport regions, employers and other organisations that want to tackle their mobility challenge in a targeted way.
See Mobility Matching in action or contribute a case?
Would you like to see the application in action, explore what the approach could mean for your organisation, municipality or project, or contribute a real-world case? Get in touch with us, or email SmartwayZ.NL at info@smartwayz.nl. If there is sufficient interest, we will host an open webinar to show the application and discuss the first results.
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