Embed Size (px)
Citation preview
SCHOOL OF URBAN PLANNING
Pro Walk/Pro Bike Conference September 11, 2012
Kevin Manaugh PhD Candidate McGill School of Urban Planning
Context
Why do people walk? Quality of walking environment Convenience Necessity Environmental Awareness Cultural or family values Financial Constraints Enjoyment Exercise Social connections
Walkability/Propensity to Walk
A vast literature explores walkability from a built environment standpoint
A vast literature also explores propensity to walk from a behavioural/psychological perspective
However, attempts to integrate these strands are less common
Many research and policy contexts ignore issues of motivation and satisfaction
Big Questions
Built form versus personal, household, neighbourhood,
cultural characteristics in walking decisions
Does satisfaction with walking trips vary by personal motivations? In addition to distance, slope, safety etc.
1) Context/Research Questions
How well do existing walkability indices explain the
variance in the choice to walk? Does this vary by trip purpose and socio-
demographic factors? What are the social equity implications of this?
0
10
20
30
40
50
60
70
80
90
100
1 2 3 4 5 6 7 8 9 10
Perc
enta
ge o
f w
alki
ng tr
ips
Quality of Walking Environment
0
10
20
30
40
50
60
70
80
90
100
1 2 3 4 5 6 7 8 9 10
Perc
enta
ge o
f w
alki
ng tr
ips
Quality of Walking Environment
0
10
20
30
40
50
60
1 2 3 4 5 6 7 8 9 10
Percentage of shopping trips by walking by decile
Walkscore
WI (800 m)
Walk Oppotunities
Pedshed (800m)
0
10
20
30
40
50
60
1 2 3 4 5 6 7 8 9 10
Percentage of shopping trips by walking by decile
Walkscore
WI (800 m)
Walk Oppotunities
Pedshed (800m)
581 trips 271 by foot
468 trips 24 by foot
0
5
10
15
20
25
30
35
40
1 2 3 4 5 6 7 8 9 10
Percentage of School trips by walking by decile
Walkscore
WI (800 m)
Walk Oppotunities
Pedshed (800m)
0
5
10
15
20
25
30
35
40
1 2 3 4 5 6 7 8 9 10
Percentage of School trips by walking by decile
Walkscore
WI (800 m)
Walk Oppotunities
Pedshed (800m)
253 out of 917 trips
105 out of 1063 trips
Sensitivity Analysis
Probabilities calculated at the mean* by walkscore deciles
No car low
income Retired Wealthy
no kids Middle age no
Kids Middle Class Large
Families Young
Families Wealthy
First Decile 72.1% 36.1% 12.6% 21.4% 30.6% 29.7% 18.5% 3.3% Fifth Decile 74.8% 65.2% 38.4% 43.6% 43.6% 49.7% 35.8% 16.2% Tenth Decile 78.0% 89.4% 79.5% 74.1% 61.0% 74.1% 63.1% 63.2%
*36 year old female making a 734 meter (average length) shopping trip
Urban Form Streets Intersections Sidewalks Trails
Content Destinations Parks Transit Schools
Resident Needs Desires Expectation Culture
Urban Form Streets Intersections Sidewalks Trails
Content Destinations Parks Transit Schools
Resident Needs Desires Expectation Culture
Urban Form Streets Intersections Sidewalks Trails
Content Destinations Parks Transit Schools
Resident Needs Desires Expectation Culture
Walkability
Conclusions (Part 1)
Equity Issues
• People with limited choices are walking in neighborhoods that are not ideal for walking
• Generalized indices (and performance measures) might miss this distinction
• People walking does not necessarily equal good walking environment
• Greater observed response among wealthy households should not imply directed policy response
Lessons Learned
Walkability is not “one size fits all” but depends on: Trip Purpose Socio-economic factors Gender Age
Can perhaps best be described as a “match” between built form factors and needs, preferences, and desires of local residents.
What next?
Does Distance Matter? Exploring the links between motivations and satisfaction in walking trips
Part 2
Context
How do values and motivations relate to satisfaction
with walking trips? Much of travel behaviour research focuses on built
environment and proximity/accessibility issues Motivations to engage in active transportation and
derived satisfaction are often ignored
Context
Most utility-maximization frameworks assume that
travel time and distance are elements of a trip to be minimized
However, recent research has highlighted the fact that this may not always be the case
For example, do ‘environmentalists’ or ‘exercise junkies’ show a different response to trip characteristics?
Data
Survey Description of commute Motivations for using chosen mode Residential choice factors Trip satisfaction
GIS Slope Other walkability variables Trip Distance
Methodology
Correlations among values, motivations, satisfaction
levels, and trip characteristics
Clustering of respondents by motivations to engage in active transportation
Initial Findings
No significant relationship between satisfaction and
distance travelled or slope of path Clustering of respondents by (self-reported)
motivation for walking
Cluster Count
Elevation change
(m) Very
satisfied (%) Distance (m)
Min (m)
Max (m)
Active cost Mimimizers 134 61.0** 19.4%**** 2034.2* 335.5 6068.6 Close Cost Mimimizers 88 29.7 25.0%**** 958.3 337.0 2354.3 Active Environmentalists 53 57.0** 52.8%*** 1801.3* 327.0 4020.9 Convenience 224 24.6 35.7% 846.3 194.5 3267.4 Close and exercise 106 30.9 40.6%*** 963.7 26.5 2862.5 Convenience and exercise 66 51.7** 39.4%*** 1675.6* 431.6 3561.6
*Statistically significant (ANOVA) F(5,671) = 61.18, p < .01(in relation to non-asterisks) ** (ANOVA) F(5,671) = 37.926, p < .01(in relation to non-asterisks) ***Chi-square (5, N = 671) = 27.58, p = .0001, higher than expected value **** Chi-square (5, N = 671) = 27.58, p = .0001, lower than expected value
Cluster membership
0
10
20
30
40
50
60
70
80
90
100
1 2 3 4 5 6 7 8 9 10
Satis
fact
ion
Distance
0
10
20
30
40
50
60
70
80
90
100
1 2 3 4 5 6 7 8 9 10
Satis
fact
ion
Distance
0%
10%
20%
30%
40%
50%
60%
70%
1 2 3 4 5
Perc
ent V
ery
Satis
fied
Quintile of Distance
0%
10%
20%
30%
40%
50%
60%
70%
1 2 3 4 5
Perc
ent V
ery
Satis
fied
Quintile of Distance
Expon. (Close Cost Mimizers)
Expon. (Convience)
Expon. (Convinience and exercise)
0%
10%
20%
30%
40%
50%
60%
70%
1 2 3 4 5
Perc
ent V
ery
Satis
fied
Quintile of Distance
Expon. (Active cost Mimizers)
Expon. (Close and exercise)
0%
10%
20%
30%
40%
50%
60%
70%
1 2 3 4 5
Perc
ent V
ery
Satis
fied
Quintile of Distance
Expon. (Active Environmentalists)
0%
10%
20%
30%
40%
50%
60%
70%
1 2 3 4 5
Perc
ent V
ery
Satis
fied
Quintile of Distance
Expon. (Active cost Mimizers)
Expon. (Close Cost Mimizers)
Expon. (Active Environmentalists)
Expon. (Convience)
Expon. (Close and exercise)
Expon. (Convinience and exercise)
0%
10%
20%
30%
40%
50%
60%
70%
1 2 3 4 5
Perc
ent V
ery
Satis
fied
Quintile of Distance
Expon. (Active cost Mimizers)
Expon. (Close Cost Mimizers)
Expon. (Active Environmentalists)
Expon. (Convience)
Expon. (Close and exercise)
Expon. (Convinience and exercise)
2817 metres 507 metres
Conclusions
People walk for a variety of reasons and motivations (many of which have nothing to do with built environment factors)
People's satisfaction with walking is correlated with these motivations
Satisfaction rates are generally high
Conclusions
Some people, particularly those with more
environmental awareness and propensity to exercise, are more satisfied with longer distance and greater slope
Conclusions
This might have important implications about how
walking behavior is understood, predicted, and modeled, particularly in terms of further expanding utility maximization models to include preferences
Conclusions
Policy implications: Is the goal to:
Increase mode share? (GHG and CC) Increase total walking? (Population Health) Improve satisfaction of those already walking? (Equity)
Conclusions
What does this all mean?
What are the most important, effective, efficient levers to increase walk/bike mode share?
Policies, social marketing, infrastructure?
