In the face of considerable uncertainty surrounding travel trends, and with the desire to find a better way of managing this uncertainty, Steer initiated a Research & Innovation (R&I) project to:
- improve our understanding of those demographic, social and technological trends likely to impact on future travel behaviour; and
- build a framework which will enable us to explore the effects of these trends on transport in a systematic manner and explore alternative policies and scenarios.
The specific tasks are:
- A literature review involving a meta-analysis of recent published reports and papers dealing with transport trends, along with the collation of the latest published statistics.
- Primary research in the form of an online survey amongst 2,000 consumers, used to explore:
- how demographic, social and technological trends affect travel behaviour;
- how these trends affect demographic groups differently.
- A Delphi exercise in which we are engaging with experts to obtain a better idea of how the trends are likely to influence future travel behaviour. To date an initial round of engagement has been completed with a second round to start shortly, in which participants will be provided with feedback from the research undertaken to date.
- To develop a framework model which can be used to test different assumptions and scenarios by examining how trends develop and interact over time. For this purpose, we are utilising the Vensim System Dynamics software.
Summary of key trends
From the literature review a list of 27 trends were identified which were then combined into eleven ‘Super Trends’:
- City attraction
- Empowered consumer
- Going on-line
- Maturing population
- Millennial living
- Need for Wellness
- Population increase
- Time poverty
- Working flexibly
These have been explored to varying degrees within the literature review, consumer research and survey of experts depending upon the availability of data and scale of likely impact. A very brief summary of each trend is provided below with the full report providing the detail.
While there is massive potential for increased automation, culminating in the emergence of driverless cars or CAVs (Connected and Autonomous Vehicles), both its speed of take up and impact are highly uncertain, with possible impacts including:
Potential positive impacts of CAVs
Potential negative impacts of CAVs
Reduced road accidents
Additional vehicle trips
Increased road capacity
Additional trips by empty vehicles
Reduced road congestion
Increased road congestion
Increased mobility for older people and
those with a disability
Greater income-related inequality
Faster adoption of EVs leading to reduced emissions
This uncertainty is further compounded by the influence of government policies which could either speed up or delay the adoption of CAVs.
There is an acknowledged trend towards an increase in the urban population and this is hypothesised to be one of the reasons that growth in rail travel has exceeded the forecasts. Given that it is relatively well understood and cannot be regarded as a 'disruptive' event it has not been explored further within this project. It will, however, be included as an underlying trend within the System Dynamics model.
The adoption of electric vehicles (EVs) has not been explored within this R&I project since there are readily available forecasts for the adoption of EVs and the change in power source is unlikely to have a significant impact on car trip rates (over and above that included within the Need for Wellness trend).
A related trend is the take-up of e-bikes: at this point in time, this was considered too early-stage to be included but is worth monitoring.
There are quite a number of interesting trends affecting consumer behaviour, though their impact on mode choices and travel demand is not likely to be significant when compared to the other trends identified. They do, however, have important implications for how people pay for transport and plan their travel, and could also have implications for equality if some consumers are left behind during the rush to a more digital world.
The ‘going online’ trend is the increasing use of Information Communication Technology (ICT), the Web, mobile devices and other digital technologies for trips to work and for shopping. The key interest from a transport perspective is the extent to which ICT is a replacement for travel compared with supplementing commuting and shopping journeys. This issue was a key topic explored within our consumer survey and amongst our panel of experts.
Some of the key findings were:
- There has been a slow but steady decline in commuting over the last twenty years with explanations postulated including an increase in home working.
- At the same time, there has been an increase in working from home, though not sufficient to account for the decline in commuting (just 4.5% of employees work mainly from home).
- Another potential explanation is growth in occasional home working, though our research suggests this has a negligible impact on overall travel demand (though can still have implications for public transport ticketing).
- Our expert panel thought that the number of people regularly working from home could double over the next ten years, though opinions regarding the impact on commuting travel varied widely.
- There has been a rapid growth in online shopping, and also an increase in use of local grocery shops near to home. As a result, visits to supermarkets and the high street have declined. However, the decline in visits to bricks & mortar shops is less than the increase in online shopping since for many, these are complementary activities. Thus, for grocery shopping, just 8% rely just on online shopping with home deliveries, while for non-food shopping it is just 7%.
- Expert panellists thought that increased online shopping would reduce shopping travel by around 10% over the next ten years, though views did vary, particularly when thinking ahead twenty years.
The maturing population is affected by a number of inter-related factors including an ageing population, a more active elderly population, delayed retirement, and older people being more wealthy. Reflecting the more general trend, up until 2014 the overall trip rate for people aged 50+ was falling but since then (up to 2017) has increased by 14%.
The net impact of these influences is also evident in the data on car licence holding which has been increasing, particularly for women aged 70+.
Whilst the gender gap has been narrowing, it is still substantial (50% v 80% car licence holding for women v men) and if this were to reach parity it would imply a substantial increase in car travel.
The view of our experts is that licence holding amongst older men will remain stable while for women it will increase to around 60%, still substantially lower than for men but still representing a 20% increase.
The Millennial living trend is based on a number of developing technologies which primarily affect young people and “Millennials”. One key aspect of this is the growth in the sharing economy typified by Airbnb, car clubs, and cab/taxi sharing apps such as Uber. These examples could reflect a more general move away from ownership to a pay as you need model.
Another important dimension of the Millennial living trend is delayed adulthood which is reflected in young adults staying in education longer than starting work later, and starting a family at an older age.
There is an observable impact of Millennial living on travel behaviour with the miles driven by 17 to 34-year-olds falling by 20% in the decade up to 2014.
In terms of predictions for the future, our experts thought the existing trends would continue and, for example, car ownership levels to fall for both males and females from approximately 30% to 25% in ten years and then down to 20% in twenty years.
It is interesting to note that when asked, those aged under 35 expected to increase their car driver trips over the next three years so there’s no guarantee that car use amongst this age group will fall in the future.
Mobility as a Service (MaaS) refers to new ways for individuals to arrange and pay for transport services. The key innovations behind MaaS platforms are that multiple public and private transport operators can offer services via a single gateway, a smartphone app. It has the potential to encourage users to be less reliant on a private car and instead, use a range of modes with the choice for a particular journey depending on specific needs.
At this point in time, MaaS is at too early a stage to make reliable predictions, though it was considered in the Delphi survey with experts. The feeling was that MaaS would reduce the need to own a car and thereby reduce car use slightly, with this effect growing over time.
Need for Wellness
The Need for Wellness trend reflects a range of related factors such as concerns over health and fitness, the ‘obesity crisis’, and concerns over air quality.
The potential impact of this trend on transport is to favour active modes and reduce the attractiveness of cars. However, it is doubtful that this potential impact is yet to materialise and in fact, the volume of walking trips has been in decline and there is little evidence of a noticeable shift in attitudes to the car.
Nevertheless, there is widespread recognition that climate change is likely to mean an increasing number of extreme weather events, and that there is a need to do something about improving air quality. The fact that concerns over the environment do not seem to translate into changes in personal travel behaviour means there is likely to be a role for government to intervene with policies such as clean air zones, promoting ultra-low emission vehicles, or road pricing and our the experts were largely in agreement that this would be the case.
The population is projected to continue to grow (by 9% in the next 20 years), with this being one of the primary drivers behind transport forecasts. However, the link between population and travel is becoming increasingly uncertain as the various social trends kick in.
The underlying factor behind the time poverty trend is the desire to fit ever more into the day with new demands on time continually emerging. One consequence of this is that most people expect to always be able to go online.
Amongst our expert panel though, opinion was divided as to whether or not this will impact on travel behaviour.
On the other hand, the majority agreed with the notion of fixed travel time budgets, with this potentially mean that savings in one aspect of travel (such as commuting) release more time for other activities (leisure travel).
Our consumer survey seems to back up the idea of a fixed travel time budget in that respondents identified no change in the time spent travelling (on average).
There has been a slow decline in commuting over the last twenty years or so with potential explanations for this including (aside from working from home) employees working fewer days a week, an increase in employment without a usual place of work, and an increase in part-time and flexible working.
People who work flexible hours make nearly a quarter fewer commuting trips than those working regular office hours. This does confirm that changes in working patterns are at least one of the explanations for the observed fall in commuting travel.
However, it is also worth noting that the overall trip rate for those working flexible and regular office hours is broadly the same, implying that fewer commuting trips is being compensated for by additional travel for other purposes.
Impacts of Artificial Intelligence and robotics on employment structures and changing social preferences on work-life balance could all have a significant impact on what work looks like. Our expert panel reflected this uncertainty with opinions divided as to whether the historic trend will continue on the same trajectory, accelerate, or decelerate.
Through this R&I project we have made considerable progress in understanding the trends affecting transport and as a result are in a position of categorise them in terms of their potential impact on travel demand, and the level of uncertainty associated with forecasting their impacts. This categorisation is visualised below.
The next step will be to validate this categorisation through further engagement with experts via a second round of the Delphi survey, and testing via a System Dynamics framework model.
Within this System Dynamics model the aim will be to include parameters which can be used to project the effects of relatively predictable or less impactful trends (e.g. Population growth, Maturing population, City attraction, Working flexibly, Need for Wellness) then use a scenario approach for exploring the more uncertain trends.
The outcome will be a framework for testing policy options within a realistic context which takes account of acknowledged demographic, social and technological trends.