New European index launched for shared micromobility

Cities still lack a consistent way to compare how shared micromobility services perform across different markets. Existing benchmarking approaches often rely on incomplete or inconsistent data, limiting their value for policymakers and planners. The Shared Micromobility City Performance Index (SMM-CPI) has been developed in partnership with the Shared Micromobility Alliance (SMA) to address this gap by creating a more reliable, data-driven framework for measuring usage, accessibility and operational performance across cities.

The initiative has been led by Dr David Rüdiger, Managing Director, Connected Mobility Düsseldorf GmbH, City of Düsseldorf, whose work through the Scoop2City programme helped shape the methodology and broader vision for a European benchmarking model. Working alongside Sebastian Schlebusch, Consultant at movingfutures the project brings together city and operator perspectives to explore how shared micromobility data can support better planning, governance and policy development across Europe.

In this Q&A, Sebastian explains how the index was developed, the challenges of collecting comparable data across cities, and how the initiative could evolve into a wider European benchmarking and monitoring ecosystem for shared mobility.

Can you explain how the Micromobility Index began and the problems it is designed to address?

The German Transport Ministry (BMV) established a project called Scoop2City, which aims to build a data-rich learning ecosystem for cities to better regulate and optimise shared micromobility. The Scoop2City consortium partner and SMA member Connected Mobility Düsseldorf (CMD), represented by David Rüdiger, expressed the need for, and the lack of, comparative data based on comprehensive and pragmatic performance indicators that can be used by cities to monitor shared micromobility performance at city and regional level, rather than at operator level.

According to David and as validated with other Shared Micromobility Alliance members, there is a high demand for reliable, spatially differentiated performance indicators for data-driven planning and policy communication.

CMD mandated the development of the methodology from December 1 2025, with the aim of validating it using data from a small number of cities. Given the funding context of the BMV, the decision was made to focus on Germany’s six largest cities by population, alongside Heilbronn as a Scoop2City consortium partner, as well as to bring in SMA members Antwerp and Milan, who were supportive in sharing data.

What has been your experience developing the index so far, particularly in working with Antwerp, Milan and the German cities involved in the MVP phase?

Although operators and cities were very supportive in providing data, it still took more than two months from the initial request to receive all data in the required formats and aggregation levels.

One interesting observation was that each individual operator shared data directly, in some cases even without formal data-sharing agreements and based purely on personal trust, and in other cases through formal agreements. By contrast, cities using Mobility Data Specification* (MDS) platforms only shared aggregated data, and where only one operator per mode was active, they refused to provide information due to concerns about violating their agreements with operators. It looks like the openness for transparency amongst operators is bigger than data sharing agreements would suggest. [*MDS provides cities and operators with a standardised way to share data on vehicle location, trip activity etc and to apply policies and restrictions to micromobility services].

Another challenge was the variation in regionalisation concepts, including functional urban areas, transport regions, clusters and market definitions, across European definitions, local governance structures and operational data organisations. This required engagement with several regional stakeholders and detailed explanations to operators regarding which local administrative units should be included in the analysis, often involving the disaggregation of market data into multiple municipal datasets within metropolitan regions.

How do you define the thematic focus of the index before data collection begins, and how does that shape the overall structure?

The thematic focus is centred on the development of a comparable, data-driven evaluation tool. The methodology maps usage and efficiency, service density and availability, and spatial accessibility at a city aggregated level. It also considers the integration of mechanical bikes, e-bikes and e-scooters, while remaining extendable to car sharing, ride hailing and autonomous taxis in future.

The methodology is also designed to ensure compatibility with national and European monitoring requirements, including the TEN-T Regulation and Sustainable Urban Mobility Plans (SUMPs), by dividing analysis between Urban Nodes, Commuter Zones and Functional Urban Areas.

What is the practical process for working with operators to collect and validate data across different cities?

For the MVP phase, the process has been very manual and cumbersome. It has involved signing individual, project-specific data-sharing agreements, sending detailed data requests covering trip numbers, average active fleet sizes and operational areas, and validating information where possible against aggregated data obtained by cities through MDS platforms.

The preferred long-term scenario would involve defining an organisation, such as the SMA or other, that has the trust of data owners, namely operators, as well as the support of data consumers, mainly cities, ensuring that data is only used for purposes defined by the organisation’s members. Initially, this would focus on scaling and automating the comparative performance index as a benchmarking and monitoring tool for local and regional governance.

This organisation could sign global data-sharing agreements with operators and cities covering all cities of interest, such as all 431 EU Urban Nodes. Ideally, it would receive MDS feeds from all operators across all cities or alternatively establish spreadsheet templates that automatically and regularly populate relevant data and feed directly into a central database.

The objective would be to automate the data collection process sufficiently to scale the MVP. There is also interest in exploring whether the SMA or another neutral body, such as a non-profit organisation, could become the central data warehouse for the project. There is willingness to lead such an effort, but it would require full buy-in from operators and backing from cities and other organisations.

How do you ensure comparability when cities have different regulatory models, data formats or operational conditions?

Comparability comes from the chosen indicators, which are designed to be high-level enough to accommodate differences in regulation, operational models and local market conditions.

The results are intended primarily as conversation starters and impulses for deeper investigation into local contexts. The index is designed as a benchmarking tool that can encourage lower-performing markets to revise regulations and commercial models with operators in order to generate greater impact.

How is the data ultimately visualised, and what kind of comparisons does the platform allow cities to make?

The vision is to make the CPI data available at city and region level as a publicly available dataset, similar to Eurostat demographic data, with regular updates.

The methodology and results of the first set of cities are now available at https://scoop2.city/ and on the Shared Micromobility Alliance website. We will also discuss the results at a dedicated session at Micromobility Europe on June 2–3, alongside discussion involving city and operator representatives about the value of the tool for cities.

What lessons have emerged so far from the MVP phase that would influence a broader European rollout?

One major lesson is the relevance of the database for TEN-T impact monitoring. The database could provide the quantitative layer for shared mobility reporting within Sustainable Urban Mobility Plans.

Beyond that, there is also interest in coordinating the development of standardised qualitative datasets, based on surveys, to provide insights into areas such as mode shift and trip characteristics. This could potentially build on methodologies such as the one developed by Way-to-Go in its 2024 Shared Mobility Belgium Report together with all shared mobility operators active in Belgium. At present, many cities conduct these surveys separately, but greater consistency would benefit all stakeholders.

Together, these two products, namely an annual comparative performance index using a consistent methodology and annual user surveys using consistent questions and answer formats across modes, operators and markets, could become a powerful benchmarking and monitoring ecosystem.

If this index expands across Europe, what would successful adoption look like, both in terms of city participation and policy impact?

The first step would involve securing buy-in from cities and operators within the Shared Micromobility Alliance (SMA), followed by the development of broader data-sharing agreements beyond the MVP markets and letters of intent from operators to support more seamless data-sharing approaches, whether through MDS APIs or automated spreadsheets.

We would also welcome commitments from Urban Nodes that are SMA members to mentor municipalities within their Functional Urban Areas and beyond and help integrate and coordinate shared micromobility planning and governance at regional level.

The second step would involve alignment with the SUMI initiative to ensure methodological consistency around shared mobility data, as well as support from organisations including POLIS, Eurocities, UITP and DG MOVE.

As you prepare the Proof of Concept for the May session, how will you decide which use case to focus on, and how will data availability across cities shape that choice?

With some fine-tuning of the operator data-sharing process, the expectation is that all input datasets will be consistently available, meaning data availability itself should not become a limiting factor. The selected input parameters were deliberately chosen because they are already readily available.

From this perspective, the main use case is to create a sense of competition between cities and regions to become the strongest shared micromobility market in Europe. The project is also intended to support positive political messaging at local, regional and national levels.

Another important objective is to help lower-performing markets improve through follow-up consultation sessions, including online masterclasses, city-specific deep dive workshops and regulatory reviews. Ultimately, the goal is to build stronger and more resilient shared micromobility ecosystems that maximise social return while remaining profitable and efficient.

The Shared Micromobility City Performance Index was launched today at the Shared Micromobility Alliance (SMA) Annual Meeting in Düsseldorf.  To view results and methodology, please click here. For further information on SMA and the index, please email: info@micromobilityalliance.com

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