Alison Chisholm achisholm@brookes.ac.uk
Overview
• Background: why interest in walking and
cycling?
• Contribution and aims of this study
• Methods
• Assessment of built environment
• Qualitative methods
• Strengths of multi-methods approach
• The challenge of influencing policy
Walking and Cycling for Healthy and Sustainable Communities
Part of £4M
programme to
develop
‘cross-disciplinary
research
consortia in the
area of walking
and cycling’
Impact of Constructing Non-motorised Networks and Evaluating
Changes in Travel
Why the interest in walking and
cycling?
Walking and cycling for short journeys in urban areas could significantly:
Contribute to
a reduction
in carbon
emissions
Improve the
quality of the
urban
environment
Promote
improved
personal health
Reduce
traffic
congestion
• Distance travelled on foot and by cycle
continues to decline.
• Nearly two thirds of trips are under 8 km in
length and two fifths under 3 km.
• One quarter of car trips are under 1.6 km
where car efficiency is at its lowest
Comparison of proportion of trips
Transport sector’s contribution to climate change
Road
Transport
contributes
23% of UK
GHG
emissions
An increase of
11% since
1990
Transport one
of the few
exceptions to
downward
trends in other
sectors
the role of walking and cycling in
tackling obesity & associated diseases
DoH (2004) At least five a week: Evidence on the impact
of physical activity and its relationship to health
Obesogenic* environments
*defn: ‘Tending to make people fat’
“Countries that rely heavily on walking and cycling have
lower rates of obesity.”
What will this study contribute?
Bias towards quantitative modelling of travel
behaviour which typically:
• includes only generalised personal characteristics (for
instance, age, gender, household size etc)
• focuses at the level of the individual neglecting effects of
situational household interactions set within a specific
geographical context.
“While there is elegance in simplicity, we are regularly faced with
complex underlying processes that are driving reality resulting in
failures of our parsimonious models to explain highly
heterogeneous behavior at the micro scale …”
Walker, J. (2006) Opening up the black box: Enriching behavioral
models of spatial and travel choices. Journal of Transport Geography 14, pp.396–398
Key aims of this study
To develop better understanding of the
complex ways in which households and
individuals make everyday travel decisions about
short trips in urban areas
To provide new evidence of how different
individuals and households make decisions about
walking and cycling and how they respond to
different interventions by focusing on neglected
areas of micro-scale household decision making ,
within the context of the built environment
initial questions to guide the research
How are walking and cycling incorporated into
everyday routines of families, households and
individuals?
Do most individuals construct an identity of
themselves and others as cyclists or walkers?
How do specific interventions to promote
cycling and walking affect everyday decision
making about short-distance travel?
How do walking and cycling as everyday means
of transport interact with other modes?
How are decisions about specific walking and
cycling routes made?
How is the particular complexity and
contingency of travel decision making best
conveyed to planners and policy makers?
The UWAC research will…
1. Focus on actual trips rather than asking respondents to
respond to hypothetical situations relating to modal change.
2. Situate cycling within the complex and contingent
circumstances of household decision making and the
geographical context where journeys take place.
Survey of population
Questionnaire survey (c15,000) across four case study sites
Purpose is to gather background data on travel behaviour,
attitudes and intentions and to identify households to
participate in qualitative study
Analysis of urban structure
Measures of urban structure (land use and
transport system characteristics).
Use of Multiple Centrality Assessment to
investigate street patterns.
Moudon, AV and Lee, C (2003) Walking and bicycling: An evaluation of environmental audit instruments. American Journal of Health Promotion 18(1): p. 21-37
Assessing the built environment
Relationship between the built
environment and walking and cycling
Key environmental correlates of walking and cycling
• Land use mix
• Population density
• Connectivity (directness of travel between two
points directly related to characteristics of street
design)
• Proximity
Less clear associations with walking and cycling
• Design characteristics (e.g. cycling/walking
infrastructure, aesthetics, traffic calming measures)
• Transport system characteristics
UWAC assessment of the environment
What?
How?
Connectivity
Multiple Centrality Assessment
(MCA)
Land-use mix and
residential density
GIS and 2001 census
Transport system
characteristics
Primary data and local authority
data
Non-built environment
Secondary data from police, Met
office, MCA and local authority
multiple centrality assessment (MCA)
An approach to spatial network analysis: a set of theories and
techniques for the objective analysis of spatial configuration
Based on the premise that the
configuration of the urban street
network is a key determinant of
movement
A street segment is “central” if it is
traversed by many of the shortest
paths connecting all the pairs of
nodes
MCA image of Leicester city centre
UDSU - Urban Design Studies Unit at University of
Strathclyde
Land-use mix and residential density
What?
• Degree to which different land uses are contained within a
geographical area
• Implies provision of local facilities which enable day-to-day
activities on foot/bicycle
• Number of households per square km
• Evidence of relationship with walking and cycling
How?
• Measure presence/absence within buffer of 1st and 2nd order
services and calculate composite for each
• Count occurrences of specific land uses within buffer
• Record average distance to work (from 2001 census)
Transport system characteristics
What?
• Motor traffic speed, volume and composition
• Public transport availability
• Walkability
• Cycle-friendliness
How?
• Local authority data,
• Primary data drawing selectively on elements of established
assessment instruments
Non-built environment
What?
• Crime
• Precipitation
• Slope
• Road ‘safety’
How?
• Police records
• Met office
• MCA
• Traffic collision rate
Mixing methods, integrating data
and influencing policy…?
Qualitative Methods employed across 100 households
Ethnography
Sit-down
household
interviews
Total of 5 households in each
location.
Total of 10 households in each
location.
3 month study period in each
location & up to 5 study visits.
Household members interviewed
twice with period of 6 months
between interviews.
Five investigative tools
1. Sit-down interviews
2. Observation
3. Mapping exercises
4. Mobility inventories
5. ‘Go-alongs’
Potentially activity diaries/blogging.
Focus on household decision
making
Current travel and change over
time.
‘Go-along
interviews’
Total of 10 households in each
location focusing on one regular
cycle journey.
Route choice & experience whilst
mobile and before & after the
journey.
“This route is the quickest, straight on the main
road. It’s horrible, but to take a different route
I’d be adding extra time to my journey.”
“I borrowed someone’s bike for a time and I was
also pulling Margaret and Thomas in the back,
in a trailer, which was fine on the way to
school, but cycling home it’s uphill a bit.”
(Anna: mum, 38)
Cathy: got a bike last year for her birthday, lived on the
Quay at that time, and on that day cycled on the
path to Glasson Dock: she loved it, she was FREE,
seeing the scenery, cycling along, like at home – [I
mention how I almost felt at home cycling there: flat]
(she agrees, yes, flat) and no cars, just cycling,
looking around.
Once she went on bike to the shop, and the traffic was
so fast, she stopped and called her husband ‘you
have to come and pick me up, I am too afraid, I can’t
cycle on….’
Cathy (mother, 28)
Jane has two kids aged 1 and 3, and walking daughter 3
to nursery in morning is fine (1 year old in pram) but
when picking her up in evening, daughter is too tired,
can’t walk, and so she picks her up in the car, with
the baby, for what is a 800 m journey. She says it is
ridiculous, but on her own with two kids, that’s the
only way she can do it. She has a double buggy which
was fine when both were smaller, but now the two of
them in it are too heavy for her to push the buggy up
the hill.
Petra (45) single, no kids:
: “I use the car because it gives me a sense of power. I play my music and I know how to drive and negotiate the streets.”
“I use the car because it gives me a sense of
power. I play my music and I know how to
drive and negotiate the streets.”
(Petra: 45, single, no kids)
Strengths of multi-method approach
Rich dataset of thick descriptions allows us to embrace
complexities, understand meanings, identities,
embodied experiences
Acknowledges importance of context and complexity
Address problems that matter to communities, bring
together a community of participants to share and
refine findings
Triangulation between methods through iterative data
generation/analysis process – seek confirmation?
Corroboration? Incongruence
Influencing policy
A key aim of the project is to influence policy –
but ‘high-level’ policy is often based on ‘hard’
quantitative data and “monetisation”.
Advisory group allows dialogue with range of
policy-makers, including DfT, local authorities
and pressure groups – opportunity to
persuade them of value of qualitative data
Broad conceptualisation of policy process and
policy makers, including the community
THANK YOU
Alison Chisholm
achisholm@brookes.ac.uk
& on behalf of the UWAC study team
Helen Harwatt (Institute for Transport Studies, University of Leeds)
Dave Horton (Lancaster Environment Centre, Lancaster University)
Tim Jones (Department of Planning, Oxford Brookes University)
Ann Jopson (Institute for Transport Studies, University of Leeds)
Colin Pooley (Lancaster Environment Centre, Lancaster University)
Griet Scheldeman (Lancaster Environment Centre, Lancaster University)
Miles Tight (Institute for Transport Studies, University of Leeds)
lec.lancs.ac.uk/research/society_and_environment/walking_and_cycling.php
Some suggested reading
Brownson, R.C., et al. Measuring the Built Environment for Physical Activity State of
the Science. American Journal of Preventive Medicine 36 (4): p S99-123
Cavill, N. and A. Davis, Cycling and health: What's the evidence? 2007, Cycling England:
London
Johnson, R.B., A.J. Onwuegbuzie, and L.A. Turner, Toward a Definition of Mixed
Methods Research. Journal of Mixed Methods Research, 2007. 1(2): p. 112-133.
Lo, R.H., Walkability: what is it? Journal of Urbanism, 2009. 2(2): p. 145-166.
Millington, C., et al., Development of the Scottish Walkability Assessment Tool (SWAT).
Health & Place, 2009. 15(2): p. 474-481.
Ogilvie, D., et al., Interventions to promote walking: systematic review. BMJ, 2007.
334(7605): p. 1204-.
Pucher, J. and R. Buehler, Cycling for Everyone Lessons from Europe. Transportation
Research Record, 2008(2074): p. 58-65.
Saelens, B.E. and S. Handy, Built Environment Correlates of Walking: A Review.
Medicine & Science in Sports & Exercise, 2008. 40(7 (Supplement 1)): p. S550-S566.
Sallis, J.F., Measuring Physical Activity Environments: A Brief History. American Journal
of Preventive Medicine, 2009. 36(4, Supplement 1): p. S86-S92.