Transport Toolkit: Real Time Information Systems

What are they and what do they aim to do?

Real-time information systems provide passengers with estimated arrival times for different public transport modes across a range of different platforms. The information is driven by location-based systems, for example, GPS tracking devices on vehicles, increasingly utilised by bus operators. The information can be delivered in various different forms, including via information screens at stops or stations, transport operators’ websites, text message alert services or third-party apps. Recently, the widespread availability of this data has enabled users to rapidly adapt their behaviours ‘on the go’ to react to new information about service performance.

This toolkit considers what the evaluation evidence tells us about the impact of real-time information systems on local economic growth. As none of the available studies examine local economic growth effects directly, we focus on ridership effects. Increased ridership may reduce congestion, which acts as a barrier to growth. Some of the additional journeys, e.g. if they are work-related, may also directly generate economic benefits. Furthermore, whilst user benefits are not the focus of our toolkit, increased ridership may be a sign of improved service experience for public transport passengers.

The toolkit does not attempt a full assessment of the overall costs and benefits of real-time information systems. Instead, it is intended to inform discussions about potential wider economic benefits that may be used to justify investment.

How effective are they at increasing ridership?

The available evaluations suggest that the provision of real-time information for bus routes may only lead to modest increases in ridership. Effects are small, but positive in two out of four studies (the other two studies find no effect).

One study suggests that there are larger ridership effects when real-time information systems are implemented on longer and more frequent routes (though it is important to note that increases on smaller routes may be more difficult to identify).

One study finds that transport networks which primarily serve captive markets (i.e. smaller urban areas which largely cater for commuter flows) do not benefit from ridership increases following implementation of real-time information systems – although there could be user benefits to existing commuters.

The effectiveness of real-time information systems may be associated with the level of technological adoption. One study found larger effects when system were implemented in later years, attributing this to greater familiarity with technology and improvements in the technology (e.g. smartphone apps). Another study which found a positive effect on ridership also reported high levels of tech use among their sample respondents.

How secure is the evidence?

This toolkit summarises the available ex-post (i.e. after introduction) evaluations of the effect of real-time information on ridership. We focus on evaluations that identify effects which can be attributed, with some degree of certainty, to the introduction of real-time information. More details and discussion of our inclusion criteria are covered in the annex.

The evaluations provide some guidance on possible impacts on ridership. But given that results are likely to be scheme specific additional sources of evidence (e.g. bespoke surveys, ex-ante modelling, etc.) should play an important role in making decisions around real-time information data in any specific context.

Generally, the evidence base on the wider economic benefits of real-time information is quite weak and focussed only on ridership, meaning that the conclusions are based on a limited number of studies. We found no evaluations which directly explore the effects of real-time information on wider economic factors such as employment or growth. More rigorous studies, which look at a wider range of economic benefits, are required. We found no systematic reviews and no meta-analysis.

We found four studies that examined the effectiveness of real-time information on ridership. All four studies use panel data methods to compare changes in ridership for lines that receive real-time information to change in ridership on lines that did not (yet) receive the system.

The evaluations do not distinguish between different types of real-time information, or how this information has been accessed (e.g. effectiveness of text message services versus smartphone apps).

All of these studies come from the United States. For a full list of studies and summaries of their findings, please see the Annex.

Is real-time information cost-effective?

None of the four studies provide a detailed analysis of the wider economic benefits of real-time information (e.g. in terms of congestion, employment or productivity) so we cannot assess these benefits relative to costs.

A number of the studies attempted to identify the impact of real-time information systems on operators’ revenues. But it is important to note that cost-effectiveness in terms of operator revenues and costs was not the focus of our review. A much wider evidence base is available that could inform assessments of possible effects on operator revenues and costs.

Things to consider

  • Should real-time information systems be implemented universally? Given the evidence suggests that effects on ridership might depend on the type of transport network and route, it may be best to implement the systems selectively.
  • What sort of technology should be used for real-time information systems? The limited evidence suggests there may be an association between technology adoption and ridership effects. However, there is a lack of evidence of what is the best technology to use for systems in terms of increasing ridership.
  • In what ways should the system be promoted? One of the successful schemes covered in this toolkit was accompanied by a coordinated marketing campaign to promote the new service.
  • How will transport operators be persuaded to adopt real-time information systems? Given the modest uplifts in ridership reported, and the substantial costs associated with real time information systems, operators may need to be incentivised to introduce systems.
  • What kind of evidence will be used to inform decision making? Results are likely to be scheme specific. The existing evaluation evidence provides some guidance, but additional sources of evidence (e.g. bespoke surveys, ex-ante modelling, etc.) should play an important role in making decisions around real-time information in any specific context.
  • Could evaluation help inform final decisions on real-time information systems? Evaluation could assess the impact of schemes through use of pilot schemes or incremental roll out over time. Better evaluations could focus on providing missing evidence such as on wider economic benefits (e.g. employment), cost-effectiveness and effectiveness across types of technology.

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