A governance framework to ensure smart mobility reduces congestion
In the third of a series of six articles, Professor David Hensher of the University of Sydney discusses whether MaaS can really deliver sustainable gains in the reduction of congestion and emissions, and improvement in accessibility and public transport performance.
As the interest in innovation in delivering customer-focussed mobility services grows, and especially the tendency to support the role of the market, and entrepreneurs and start-ups in the mix, including their roles as providers of digital platforms, government needs to start contemplating the role it might (or should) have in ensuring that outcomes are consistent with the broad goals for our society (‘smart’ liveable cities in particular).
MaaS and smart cities
MaaS has often been described as a concept that can deliver sustainability gains in terms of reduced congestion and transport emissions and improved accessibility and improved public transport performance, but I question this given the limited evidence and thoughtful considerations above. MaaS is also billed as an innovation opportunity, underpinned by the development of new business models in transport, such that it can deliver economic benefits.
Hollands (2015) points to a concern about smart cities being driven by corporate power and commercial interest at the expense of understanding the consequences for social and urban development ‘‘which is crucial to the liveability and sustainability of these cities” (Hollands, 2015: 68). Lyons (2017) also echoes these same sentiments.
Docherty et al. (2017) suggest that it is far from clear that these opportunities will be recognised or, even where they are, realised due to the complexities of steering any transition in the mobility system. Governing the smart mobility transition will be a key role of government in the presence of the growing network of actors and the new resource interdependencies (including who owns crucial big data – see later) that are almost certain to emerge.
Karlsson et al. (2017) suggest that overall, the assessments suggest that a broader introduction of MaaS could result in overall positive impacts, in terms a modal shift, a change in attitudes and an increase in perceived accessibility to the transport system. However, in their empirical research in Scandinavian countries, conflicts between impacts on different levels were identified where, for example, increased accessibility to the transport system – a desired impact on an individual and societal level – may result in an increase in the number of trips made – possibly a desired impact on an individual level but an undesired impact on a societal level with negative implications for emissions as well as congestion.
When planning for a further introduction of MaaS from a societal perspective, such conflicts must be addressed in order to best determine how to potentially integrate overall societal goals into the MaaS offer and the business model1.
Whilst the numbers of vehicle kilometres generated under different smart mobility models can be debated, a key issue is the set of assumptions about how a system would have to be governed were it to achieve public value? Such tightly regulated approaches do not exist today in even the most progressive welfare societies (Docherty et al. 2017), and there has yet to be a commitment to the types of parking restriction and charging measures that would be necessary to make the transition from today’s mixed fleet to a fully shared system beneficial.
In reflecting on this matter, one might think that we have been there before. The smart transition, to date, has clear echoes of other transport markets through the decades, which have tended towards conditions of oligopoly or monopoly. Without effective regulation, preventing anti-competitive behaviour, such as a global-scale company providing mobility services from strangling new market entrants at birth through price attacks, could be impossible.
A further issue to be considered is how these new systems handle allocated access to public space of different sorts. The recent lack of transparency in data sharing around the first more highly automated driving system accidents in the US is also a concerning initial marker.
One possible way forward under a smart future might be for government to consider supporting mobility subscriptions rather than the transport services which underpin them, which could include a social contract as part of the right to operate, a new kind of ‘Public Service Obligation’ for Smart Mobility? For example, as suggested by Docherty et al. (2017), a kind of ‘Tobin’ per-transaction charge could be levied in areas with very high sharing densities which subsidises the areas which would otherwise be under served.
The user-side subsidy funding model associated with specific modes such as buses, as discussed in the previous section, could also be part of this model, ensuring that the MaaS subscription plan not only offers a multi-model contract but also has inbuilt competitive processes in setting the prices to attract customers who will pay for a plan that is accompanied by a reimbursement claim equivalent to the level of subsidy provided to a customer. The customer then controls the market and MaaS providers compete for business.
This does not guarantee that all MaaS providers would want to include public transport in the mix, but it does ensure that there is sufficient public transport available that is an attractive alternative to the car based services where this is deemed by government to be a desirable feature in the jurisdiction of interest.
We may also need an independent office2 of the smart mobility regulator? Much will depend on how brokers (aggregators) and orchestrators of the intelligent mobility model respond by designing multimodal subscription plans with public transport in the mix.
Like this article? Move it along on social media.
1. The author and colleagues at ITLS are undertaking a stated preference study to establish broker (aggregator) and orchestrator preferences for different subscription plans (allowing for equity, risk, modes and possible government subsidy). Current mode-specific operators and non-mobility providers are in the sample.
2. Such an office can set the network price with inputs like time of day, location and modal efficiency used to define the rate of mobility credit consumption under an economically deregulated broker market.