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Mobility ‘Y’: The Emerging Travel Patterns of Generation ‘Y’ [the
‘Millennial’ Generation]
Dr. Scott Le Vine www.imperial.ac.uk/people/s.le-vine
SUNY New Paltz (USA) and Imperial College London (UK)
2nd Armand Peugeot Chair International Conference Electromobility: Challenging Issues
18th/19th December 2014
Reporting on various studies undertaken in collaboration with: Qinyi Chen, Charilaos Latinopoulos, Peter Jones, Tobias Kuhnimhof, John Polak, Tom Worsley
Research sponsored by: Imperial College, RAC Foundation, Independent
Transport Commission, Office of Rail Regulation, Transport Scotland, Institute for Mobility Research, Welsh Assembly
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‘Peak Car’? • Public sector: Future
roads/rail policies & investments
• Private sector: How are markets for mobility (and those linked to it) changing?
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Taro Hallworth, formerly DfT (now CCC) Tobias Kuhnimhof: “Are young men responsible for Peak Car?”
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Young people, esp. men, are the ones to watch
Le Vine and Jones (2012) ‘On the Move…’
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Headline trends (Int’l., #1)
Tobias Kuhnimhof: “Are young men responsible for Peak Car?”
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Headline trends (GB) • Young male licence-
holding has fallen (but appears to now have stabilised), as has mileage per driver
• Each accounts for roughly half of their pre-recession 30% drop in car mileage
From 6,500 mi./year in 1995/7 to 4,500 in 2005/7 (across GB)
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Males aged 17 -‐ 29
Females aged 17 -‐ 29
Full-licence holding (ages 17-29), GB
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Hypotheses for inc. in non-driving 1. The rise of phased licence-acquisition regimes (GDL) 2. Increased rates of participation in higher education 3. Decreased levels of economic activity (linked with #2) 4. Concentration of young adults in dense cities (where
car-free lifestyles are most viable) 5. Modern information and communication technologies
(online activity, texting, etc.) 6. Heightened environmental awareness among today’s
young adults 7. Historically-high levels of international migration 8. Deferred family formation
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Hypotheses for inc. in non-driving Let us categorise the hypotheses into two categories:
1. Speculative hypotheses (new and/or different relationships) • Growing sensitivity to sustainability issues • Impacts of new technology (Smartphones,
Internet, etc.)
2. Classical hypotheses (relationships that we understand and have traditionally taken into account) • Economic activity (GDP, employment, etc.) • Prices (e.g. petrol/gasoline, public transport
fares)
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Trends in env’t. sensitivity (US)
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As previous – but only ages 18-34
© Gallup, 1984-‐2014. Used with permission
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NB: X-‐axis not proportional
EnvironmentEconomic growth
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Trends in env’t. sensitivity (GB)
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Electronic connectivity? (1)
hCp://thecityfix.com/blog/on-‐the-‐move-‐younger-‐generaMon-‐mobility-‐trends-‐akshay-‐mani/young-‐generaMons-‐on-‐the-‐move-‐embarq/
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Electronic connectivity (2) • Using data from Scotland (2005/6), we were unable to replicate
cross-national results from Sivak & Schoettle (2012) • We found a strong and statistically significant POSITIVE cross-
sectional ceteris paribus relationship between internet usage and licence-holding/car-driving-kms
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• Others are now reporting similar empirical results suggesting complementarity between ICT use and physical mobility: Kroesen and Handy (2015), Taylor et al. (2014), Aguilera et al. (2012)
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Economics (GB) – Trend in GDP
Corry et al. 2011§
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Economics (GB) – HMRC data
Analysis of Survey of Personal Incomes
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Economics (USA)
hCp://www.pbs.org/newshour/businessdesk/2013/10/why-‐millennials-‐are-‐struggling.html
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Drop in economic activity begins early in teenage years (GB again)
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Percen
tage th
at perform
at least one
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Males Females
Analysis of Na9onal Travel Survey diary data
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‘Main’ reasons for not driving, by age
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Percen
tage of adu
lts age 17+ who
do no
t have a full car d
riving licence
Currently learning to drive (question not asked)
Put off by theory/practical test
Cost of learning to drive
Cost of insurance
Cost of buying a car
Other general motoring costs
Family/friends drive me when necessary
Other forms of transport available
Too busy to learn
Not interested in driving
Environmental reasons
Safety concerns/nervous about driving
Physical difficulties/disabilities/health problems
Too old
Busy/congested roads
Driving without licence
Other
Analysis of Na9onal Travel Survey data, reproduced from: LaMnopoulos, Le Vine, Polak and Jones (2013) ‘On the Move Scotland…’
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Pass rates for practical driving test fell
Barbara Noble: Why are some young people choosing not to drive? (2005)
• Average British young adult spends 1.7 years (20+ months) in ‘learning to drive’ status between ages 17 and 29
• Average test-passer has spent c.£1,000 on driving lessons • Today’s (2013/4) pass rates: 52% (theory test),
47% (practical test)
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Conclusions & looking forward (1) • Speculative hypotheses: Available evidence suggests attitudes-
to-sustainability & online-activity are not associated with young adults’ decreased ‘auto-mobility’ (but we must be cautious and open-minded)
• We need to better understand New manifestations of the Classical hypotheses:
• The puzzle is that young adults ‘auto-mobility’ fell during the 2000s despite rising GDP/capita. But their GDP/capita was not increasing – they’ve been in recession since 2001.
• The run-up in fuel prices in the 2000s affected all ages. But the increasing cost/difficulty of acquiring a driving licence disproportionately affected young people (older adults were ‘grandfathered’).
• We speculate that a similar ‘grandfathering’ phenomenon from the run-up in British home prices may be associated with young people’s concentration in urban flat-renting arrangements
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• Nearly all analyses are cross-sectional, so provide limited insights into the time-trend and tell us nothing about the direction of causality (AàB, or BàA, or AßàB)
• Big, important research questions remain: • Are the ‘new’ manifestations of ‘classical’ hypotheses the
whole story (in a statistical sense) – or is there still, after taking them into account, an ‘X’ factor that requires further explanation?
• How trustworthy are the data? (e.g. has intentional mis-representation of status/behaviour increased?)
• Are they happy? What happens when they ‘grow up’? • Have wider outcomes (labour force participation,
housing, etc.) been impacted – if so, how and how are effects distributed across the population of young adults?
Conclusions & looking forward (2)
