Portland State University
PDXScholar
TREC Friday Seminar Series
Transportation Research and Education Center
(TREC)
2-10-2017
Individual Decision Making in Online Public-Participation
Transportation Planning
Martin Swobodzinski
Portland State University, [email protected]
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Recommended Citation
Swobodzinski, Martin, "Individual Decision Making in Online Public-Participation Transportation Planning" (2017). TREC Friday
Seminar Series. 109.
http://pdxscholar.library.pdx.edu/trec_seminar/109
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Individual decision making in
online public-participation
transportation planning
Martin Swobodzinski, Ph.D.
Assistant Professor of Geography
Director, Center for Spatial Analysis and Research
Portland State University
[email protected]
February 10, 2017
TREC Friday Seminar
Acknowledgements
Participatory GIS for Transportation
Project (www.pgist.org). Research
supported by National Science Foundation
Grant No. EIA 0325916, funded through the
Information Technology Research Program,
and managed in the Digital Government
Program.
Center for Spatial Analysis and Research (CSAR)
Acknowledgements
Principals
Research Assistants
Tim Nyerges, UW
Piotr Jankowski, SDSU
Rhonda Young, UWY
Terry Brooks, UW
Scott Rutherford, UW
Matthew Wilson
Kevin Ramsey
Mike Lowry
Arika Ligmann-Zielinska
Martin Swobodzinski
Adam Hindman
Michael Patrick
John Le
Zhong Wang
Jie Wu
Guirong Zhou
Tao Zhong
Consultants
Robert Aguirre
Fixie Consultants
Puget Works
Partners
Puget Sound Regional
Council
King County
City of Seattle
Center for Spatial Analysis and Research (CSAR)
Participation
8
Citizen Control
7
Delegated Power
6
Partnership
5
Placation
4
Consultation
3
Informing
2
Therapy
citizen power
tokenism
nonparticipation
1
Manipulation
(based on Arnstein, 1969)
Center for Spatial Analysis and Research (CSAR)
Use of Technology
Process
Technology
Satisfaction
Performance
Center for Spatial Analysis and Research (CSAR)
Outcomes
Illustration
Center for Spatial Analysis and Research (CSAR)
Task-Technology Fit
GIS Technology
Geographical
Tasks
Spatial
Abilities
Intrinsic
Incentive
Task-Technology
Fit
Performance
Goal Commitment
System
Utilization
Goal Level
(based on Jarupathirun and Zahedi, 2007)
Center for Spatial Analysis and Research (CSAR)
PGIST
Center for Spatial Analysis and Research (CSAR)
Puget Sound
Snohomish
Kitsap
King
Pierce
Center for Spatial Analysis and Research (CSAR)
LIT Steps
1.Concerns
1
M
o
n
t
h
2.Factors
3.Individual
Package
4.Group
Package
5.Report
Center for Spatial Analysis and Research (CSAR)
Challenge
?
?
user interaction
Groups of
users with
similar user
interaction
individual characteristics
Socio-demographics
Cognitive Style Indicator*
Travel behavior
Computer/Internet proficiency
*(Cools and van den Broeck, 2007)
Center for Spatial Analysis and Research (CSAR)
Server Log File
Center for Spatial Analysis and Research (CSAR)
Capturing
Activities
25 activities
9 activities
deliberation
analysis
information
gathering
Center for Spatial Analysis and Research (CSAR)
total duration
HCI Analysis Overview
Server Logs Extraction
User
Clustering
Activities
Groups of
similar Regression
interaction
Group
Analysis Iteration
Center for Spatial Analysis and Research (CSAR)
Predictors
Clustering Algorithms
Multiple sequence alignment analysis*
• Hierarchical cluster analysis
•
Alice Bob
Alice
*(Abbott, 1990; Shoval and Isaacson, 2007; Fabrikant et al., 2008)
Center for Spatial Analysis and Research (CSAR)
Clustering Summary
•
•
•
HCA: Usable classification for total
time
MSA: Reliability concerns
Analytical synergies MSA
HCA
Center for Spatial Analysis and Research (CSAR)
Logistic Regression Summary
Groups
Groupswith
of
similar
users
with
overall
similar
user
interaction
interaction
duration
Socio-demographics
Cognitive Style Indicator*
Travel behavior
OnlineComputer
transportation
discussions
Literacy
*(Cools and van den Broeck, 2007)
Center for Spatial Analysis and Research (CSAR)
What about Individual Choices?
*COOLS, E. & VAN DEN BROECK, H. (2007) Development and validation of the
cognitive style indicator. Journal of Psychology, 14, 359-387.
Center for Spatial Analysis and Research (CSAR)
Location Analysis
100%
Outside buffers
Walking distance
Bicyling distance
Driving distance
17%
60%
40%
40%
60%
Center for Spatial Analysis and Research (CSAR)
23%
30%
22%
8%
Cost Analysis
Me
You
vs
$159
$8,731
Median
Sum
Center for Spatial Analysis and Research (CSAR)
$378
$16,348
Location/Cost Analysis Summary
•
•
•
•
Self-centrism prevailing
Need for moderation
Feed observed patterns into process
Complexity! Performance?
Center for Spatial Analysis and Research (CSAR)
Conclusions
•
•
•
•
System, process, outcomes
Capturing, evaluating HCI in webbased DSS (LIT as case study)
Analysis of behavior; profiling of
the ‘public’
PPGIS, spatial equity; greater
good?
Center for Spatial Analysis and Research (CSAR)
Conclusions
Access
Representation
Center for Spatial Analysis and Research (CSAR)
Attrition
Take-home Message
•
•
•
Public :: individuals
Participation = f(opportunities for
participation)
Towards an individual-centered
approach
Center for Spatial Analysis and Research (CSAR)
Thank you!
Martin Swobodzinski
[email protected]
Center for Spatial Analysis and Research (CSAR)