Netherlands: Mobility-as-a-Service future areas

When asked which geographical area is the most suitable environment for Mobility-as-a-Service platforms, most mobility experts in the Netherlands named the center of a large city. Looking at the distribution of all the areas, the experts appeared to agree that shared mobility platforms were most likely to succeed if they operated in an urbanized area. Less than a quarter of the experts named rural areas as a good geographical environment.

In the same survey, the experts suggested that the most likely MaaS customers were singles and childless families. Combining these findings, this means that young, urban, childless couples were seen as the perfect customers for shared mobility initiatives.

Shared mobility or MaaS platforms offer vehicles such as cars, bicycles or e-scooters for (short-time) rent to their users. Often, these vehicles are picked up and dropped off in designated areas, although some mobility services such as Car2Go allow users to leave the vehicles anywhere in the city.

Geographical areas with the highest potential for Mobility-as-a-Service platforms according to experts in the Netherlands in 2019

Characteristic	Share of experts
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Release date

September 2019

More information

Region

Netherlands

Survey time period

October 1, 2018 to January 4, 2019

Number of respondents

100 respondents

Age group

18 years and older

Special properties

MaaS experts

Method of interview

Online survey

Supplementary notes

The source adds the following information: "The report’s findings are largely based on analyses of online questionnaires distributed among a group of MaaS experts, all of whom are professionals in the field of traffic and transport with knowledge of MaaS through their current or recent work. This group of experts was comprised of researchers, policymakers, consultants and service providers. We also took the following steps to ensure that those we consulted were in fact experts in the field: snowballing (experts were recommended by other experts), explicit reference to the MaaS expertise in the invitation to fill in the questionnaire, and cleaning from the dataset those who did not regard themselves as experts."

Multiple answers were possible.

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