Is micro-mobility helping or hurting our cities? There are many questions helping to frame this issue in communities all around the world.

• Are the benefits to users of this new niche of transportation services greater than the frustrations experienced by those in our communities who don’t use them?
• Does improved connectivity outweigh new injuries and, in some cases, fatalities documented since their introduction?
• Does micro-mobility encourage a shift away from single occupancy car trips more than vehicles such as e-scooters eat into walking, bicycling, and public transport trips?
• To what extent can we justify the reduction of some longer-distance walking trips as an improvement to equity?
• Will the vehicles we are planning for today even be here tomorrow?

Presently, we have a basic profile of micro-mobility through statistics such as vehicle and trip counts, but it is clear from our conversations with many cities, operators, and other stakeholders, that we all seek better ways to measure how well these programs are working in our communities. While every city is unique, and while micro-mobility is arriving at different times and in varying scales to cities, we submit it is still possible to identify common themes that span the globe from which we can measure success.

In the past few years, micro-mobility services have been arriving at unprecedented speed and scale to cities that are oftentimes ill-prepared to manage them. Typically, these services are introduced by private operators and are deployed as a “floating” system, meaning that only the vehicles themselves are physically present in public spaces. Legislation does not clearly define these new vehicles, and new business models do not fit neatly into existing methods of managing private businesses in public spaces.

The transportation community has responded by producing several helpful publications on the topic of micro-mobility, bringing more clarity and understanding to this phenomenon, documenting the growth and expansion of programs in cities, and providing guidance on good practices. Nonetheless, cities and operators still find it difficult to know if their micro-mobility programs are serving the community well, and how well the elements of their programs compare to other cities around the world. What is still needed is an easier way to measure what it means to have a successful program.

At Ramboll Smart Mobility we wanted to push the discussion away from general statistics about micro-mobility, and towards the identification of strategic goals and tangible key performance indicators (KPI). The KPIs can be measured by any city to better understand how successful and sustainable they are in providing new mobility options to their communities, and where they can improve.

We have thus identified a set of common strategic goals that we believe any city or operator would want to achieve. We have done so by considering perspectives, anecdotes, experiences, and factual data from a range of stakeholders and participants in the micro-mobility community, including: 15 cities, public transit agencies, micro-mobility operators, surveys of the general public, micro mobility focused data management services, and regional expert organizations. We then used a simple methodology to propose some potential KPIs that can be adopted by cities to gauge the sustainability of their micro-mobility programs, as well as compare themselves to other cities around the world.

There is an intentional emphasis on e-scooters in the study, but the effort and the outcomes are intended to apply to micro-mobility as a whole.

The Scope of the Study

The study was possible thanks to contributions from many sources. In the early stages of structuring our effort, we recognized that while there were quite a few publications available and being released about micro-mobility, many of them were focused on a specific city or region or contained general advice and metrics about micro-mobility programs. We wanted to build on these publications to expand the ways of describing micro-mobility programs beyond the summary statistics of fleet size and trip counts, towards metrics that enabled cities to better gauge the success of their efforts.

Our team collected and reviewed the state of practice available via existing studies, publications, and articles to better understand what cities were up to and how their efforts related to the establishment of universal strategic goals. This effort was admittedly not comprehensive, but the spectrum of references considered allowed us to form a strong basis for more targeted input sources. With this foundation we then pursued three data input channels.

1. Operational Data: Our team was able to evaluate some of the data available to the City of Hoboken, NJ via its data management platforms, RideReport, and Populos. In addition, we discussed the use of specific data sets with both Lime and Voi.
2. Municipal Interviews: A major source of our inputs came from one-to-one interviews with municipal officials, operators, and other major actors in the micro-mobility theatre, such as NACTO in North America and POLIS in Europe. We conducted short interviews via phone or online conferencing during which we asked targeted questions about local activities related to the themes presented herein, and specifically about approaches to the strategic goals.
3. Public Surveys: Several public surveys had already been conducted in cities such as Portland and Paris. We considered these results and worked in collaboration with the City of Hoboken to identify more targeted questions that could build upon the in-depth survey already planned for the ending days of Hoboken’s six month micro-mobility pilot program. In addition, a City Councilmember in Hoboken had polled the local constituency with a single-question email survey using data analytics by Involved to gather opinions about the pilot program. These data were useful in validating the City’s survey as well as identifying interesting trends.

 

In total, our research included 15 cities: six in North America, seven in Europe, and two in Asia-Pacific:

We believe the outcome is a strong representation of the successes and challenges that cities of all sizes are experiencing, from unique legislative hurdles faced each location, to the universal needs that every city shares as critical to delivering successful micro-mobility services in their communities.

Measuring the Value and Sustainability of Micro-Mobility Programs

Every city is unique. The people, the cultures, the urban form, the institutional organization, topography, and even the weather impact the way in which transportation services function. While every conversation about micro-mobility is shaped by the influences of the local context, we have approached this project with the premise that we could nonetheless identify common themes that weigh on the minds of the people in any city. These themes are the essential elements that contribute to providing local communities the best possible successful micro-mobility program, including success with respect to the environment, economy, and social well-being. We believe that, regardless of the local context, there are a set of universal strategic goals that every city can agree are important to realize a sustainable micro-mobility program.

In our collaboration with cities and operators experiencing micro-mobility first-hand, as well as other authorities and stakeholders closely connected to the management of micro-mobility programs, we have derived the following twelve universal strategic goals:

The goals were established to allow our discussions to focus on specific metrics that would be useful in better gauging the success of local micro-mobility programs.

The 12 Strategic Goals & Associated KPIs

In relation to the goals, we have suggested a range key performance indicators (KPIs) that can be used to gauge the progress of an individual city and to allow basis for benchmarking across cities.

Strategic Goal	KPIs
Connectivity	Share of micro-mobility trips that would otherwise be a car trip Share of micro-mobility trips longer than 1 km that would otherwise be a walking trip Share of micro-mobility trips combined with public transport Share of users who say that micro-mobility “makes it easier to get around town”
Climate	Share of micro-mobility trips that would otherwise be a fossil fuel car trip Share of micro-mobility trips less than 1 km (.6 miles) that would otherwise be a walking or cycling trip Lifecycle carbon footprint of micro-mobility vehicle by passenger km/mile Share of users who say micro-mobility “facilitated access to public transport” versus “replaced a public transport trip” Trip purpose of “new” micro-mobility trips
Equity	Availability, distance, and usage by geography Availability and usage by time of day Distance to scooters Ridership by age and gender Pricing and payment options provided by operators
Resilience	Capacity in bike lanes Capacity for parking Capacity in public transport Percentage of space allocated to micro-mobility facilities “Robustness” of the service
Local economy	Number of trips ending along main street / total trips Trip volumes along commercial corridors Users’ trip purpose Number of customers at local businesses arriving by e-scooter/micro-mobility
Safety	Available infrastructure Other safety measures implemented Offered safety training or information Hospital injury data: crash and injury types Micro-mobility crashes as a percentage of all crashes
Innovation	Number of tests and pilots projects Involvement of local community
Compliance	Degree of rider compliance with local regulation Citations issued to users for noncompliance/total rides Types of compliance concerns noted by the public Initiatives to improve compliance Policies and fines used to improve compliance
Acceptance	Acceptance of the systems among users and non-users Value of the system to the community Importance of specific infrastructure elements or policies to improve acceptance
Management	Which model is used to manage micro-mobility (voluntary cooperation, pilot program, permitting / licensing scheme) Effectiveness of the mechanisms used to manage micro-mobility Number of city staff assigned to micro-mobility programs, per ride
Data access	Data sharing agreement with operators Data sharing platforms used Types of data collected
Costs	Which model is used to manage micro-mobility (voluntary cooperation, pilot program,  permitting /licensing scheme)? Effectiveness of the mechanisms used to manage micro-mobility Number of City staff assigned to the micro-mobility program per ride