Measuring the maturity and performance of urban mobility systems

Using 11 criteria Arthur D. Little assessed the mobility maturity and performance of 66 cities worldwide. The mobility score per city ranges from 0 to 100 index points; the maximum of 100 points is defined by the best performance of any city in the sample for each criteria. In addition the study reviewed and analyzed 39 key urban mobility technologies and 36 potential urban mobility business models.

The average score of the 66 cities was close to 65 index points (64.4 points). Which means that in average the 66 cities just achieve two thirds of the potential that could be reached today, applying best practice across all operations. Only two cities (Hong Kong, Amsterdam) scored above 80 points, with just 15 per cent of cities scoring above 75 points.

The detailed analysis reveals a number of remarkable results:

  • First, there is a clear correlation between the use of innovative mobility concepts on one hand and mobility effectiveness and efficiency on the other hand. Cities that promote walking, cycling, bike-sharing, car-sharing and smart mobility cards as part of an integrated mobility vision and strategy do reduce travel times, fatal accidents and carbon emissions. All but two of the top ten performing cities have a strong focus on public transport, walking and cycling, with individual motorized mobility commanding less than half of the modal split.
  • Second, the average score achieved by the 66 cities in the sample is 65 points (64.4) and only 15 per cent of the cities score above 75 points. In other words, the average city achieves only two thirds of what is possible today by applying best practice across all operations and only 10 cities perform in the top quartile possible today. This analysis indicates the significant performance-improvement potential cities have and highlights the urgent need for cities to address the urban mobility challenge proactively.
  • Third, even for cities that score highest, namely Hong Kong (81.9) and Amsterdam (81.2), the scope for improving toward the maximum score of 100 is still significant. Hong Kong, for example, scores very high in terms of smartcard penetration – allowing people to use one and the same contactless payment card across transport modes – but lags in terms of car- and bike-sharing. In other words, a near-perfect mobility system does not yet exist in the world today and full satisfaction with urban transport is not observed in any of the cities studied.
  • Fourth, city size does not have a significant influence on the mobility score. For example, the small cities of Rome and Athens have much lower scores (57.9 and 53.3 respectively) than the large cities of London and Madrid (78.5 and 71.8 respectively). However, the two other city characteristics that we studied, namely city prosperity and the prevalence of public transport (‘modal split’), do have a significant influence on the mobility score. The richer the city and the lower the share of individual transport, the higher the score.
  • Fifth, cities in mature regions are not necessarily a model that cities in emerging regions should aspire to emulate. Many of the former, such as Tokyo, Prague, Moscow, Atlanta and Miami, still do not appear to have a vision and documented strategies that clearly articulate what they want their future mobility systems to look like. Furthermore, if cities in emerging regions replicate the pathway that cities in mature regions have followed, they run the risk of introducing the very same problems of poor modal split, high carbon emissions and low travel speed. US cities in particular tend to score low, as their modal split is heavily biased toward cars and their carbon emissions are a multiple of those in Europe.

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