Seminar presentation by Dr Greg Marsden www.its.leeds.ac.uk/people/g.marsden www.its.leeds.ac.uk/about/events/seminar-series www.disruptionproject.net www.fleximobility.solutions

1. Disruption and the mobility system:
concepts, empirics and issues
Professor Greg Marsden

2. Infrastructures are Stable - How
they are used is not – non
‘transport’ change
• Pensions
• Work
• Education
• Ethnic diversity
• Technology
• Ageing
1. Change is prevalent and has not been fully recognised
2. Scale of changes dwarfs most of our transport interventions

3. Looking for change
• “when seeking to identify nascent transport
tendencies there is little value in focusing on
global or national averages” (p380)… Whilst
millions of people might be locked in to car
dependent lifestyles, “from a socio-technical
transitions perspective these people are
largely irrelevant” (Cohen, 2012: 380).

4. Disruption as a source of learning
• when things break down, new solutions may
be invented. Indeed, there is some evidence
to suggest that this kind of piece-by-piece
adaptation is a leading cause of innovation,
acting as a continuous feedback loop of
experimentation which, through many small
increments in practical knowledge, can
produce large changes
Graham and Thrift, 2007

5. Disruption – Definitional Issues
Source: Network Rail

6. What has been disrupted?
• Infrastructure
• Services Running on Infrastructure
• (Some of) the activities which go on via the
infrastructure
• The expectations of performance
• Nothing at all

7. Disruption to What?
• Vollmer (2013: 2) focuses his insights around a
key notion that what is disrupted is the
“coordination of activities and expectations”
within a collective entity.

8. Disruption as a relative concept
• Level of service
• Expected journey times
• Use versus non-use
• This time versus last time
• Consequences (and insurance actions..)

9. Scale, Frequency etc… and the
Tautology of ‘Normal Disruptions’
• Vollmer (2013: 1) …because disruptions are a
part of everyday life “many disruptions
happen and attract little further notice
beyond the situation in which people confront
them” he also suggests that others come to be
regarded as “more drastic and consequential”.
– Scale
– Frequency
– Familiarity

10. Coordination of Activities – Snow and
Ice
Activity Delayed
Start
Delayed
Finish
Postponed Cancel New
Destination
Conducted
At Home
Other n
Commute 49% 32% 8% 41% 2% 12% 5% 974
Biz Travel 21% 17% 41% 41% 2% 5% 4% 126
Return Home 26% 46% 16% 16% 4% 0% 5% 74
Health 7% 7% 48% 37% 0% 0% 7% 85
School/ Child
Care
14% 5% 10% 80% 0% 3% 2% 278
Other Care 22% 23% 34% 25% 1% 8% 9% 77
Shopping 16% 8% 46% 34% 5% 5% 2% 250
Sport 3% 1% 24% 75% 1% 0% 0% 113
Leisure 5% 3% 28% 59% 2% 1% 7% 151
Family/
Friends
9% 4% 46% 45% 2% 2% 1% 194
Other 12% 8% 15% 24% 1% 1% 11% 95

11. York floods 2012

12. Coordination of Activities
• “The amount of time it would take me to travel both back to
Stillingfleet – I left the office early, my office in town hall, to make
sure I could get back to Stillingfleet to meet my son. And then I was
worried about my mum, who comes to look after my son when I go
out to work in the evenings because I’m a single parent
• “So did you think about “Can I trade favours with childcare?” “Yeah.
I did have to do that on the Thursday actually. I had a friend’s little
boy for most of the afternoon so that he could go there early
evening”
• “So finally got out… I had to go to a golden wedding do yesterday in
Middle Thorpe and I did manage yesterday morning.”
• “In fact today we’ve been to a christening so we had to get into the
city centre...Traffic was an enormous problem”

13. Expectations
• “People just don’t go to work
now if it floods. We were never
off, we never missed a day, and
my husband was in local
government and worked at
Malton and he got there every
day...
• “I for one will try and get in
however it happens. And like
you say, I’d expect my team to
do the same. But I’m not going
to get upset if they ring up and
say I can’t get in because of bad
weather.”

14. Expectations – Snow and Ice
Regression Model
• If the respondent is not physically expected to be in
work then there is high probability that they will not
make the journey, suggesting they will work from
home.
• If the employer is not accommodating then there is a
stronger possibility that the employee will make the
journey into work.

15. Examples of Planned Disruption (1)
Olympics
• Significant amount of change to commute journeys
– 54% of the sample made at least one change to their commute
– 25% made more than one change
– Reducing (31%) and Retiming (25%) most common response
• More changes for those with a greater preparedness to
change

16. Examples of Planned Disruption (2)
City of York Office Consolidation

17. Mobility System

18. Radical Change
Business as Usual
Rapid Incrementalism
Politics?
Politics?

19. Conclusions
• Definitional issues we haven’t paid attention to
• Disruption as an on-going ‘every day’ process
• ‘Breakdown’ as a source of learning and innovation
• Disruption to patterns of coordination and expectations
• Implications are that we need to tie in the transport system
with the activities we take part in – mobility system – to
effect change
• So for evaluation…
• So for infrastructure management…
• So for valuing assets…
• So for understanding travel behaviour this means…

20. EPSRC Grant EP/J00460X/1

21. References
• Graham, S. and Thrift, N., 2007, "Out of order"
Theory, Culture & Society 24 1-25.
• Cohen, M.J., 2012, The future of automobile
society: a socio-technical transitions
perspective, Technology Analysis & Strategic
Management, 24(4) 377-390
• Vollmar, H. (2013) The Sociology of Disruption,
Disaster and Social Change Punctuated
Cooperation, Cambridge University Press