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Companionship and Time Investment in Social Fields at Different Life Cycle Stages:
Implications for Activity and Travel Modeling and Simulation
Jae Hyun Lee Konstadinos G. Goulias
Geotrans Laboratory
Department of Geography University of California, Santa Barbara
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Outline
• Introduction
• Data & Descriptive Analysis
• Model Specification
• Results & Findings
• Limitations
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Introduction
• In time allocation and travel one of the most important factors is human interaction (Kitamura, 1988; Jones, 1990; Bhat & Koppelman, 1999)
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Introduction
• Intra-household interactions are most often included in activity-travel analysis, and many researchers have shown their significant roles in explaining daily-life (Townsend, 1987; Van Wissen, 1997; Golob and McNally, 1997; Golob 1998)
• In travel behavior research we also see increasing attention on
incorporating the influence on behavior of interactions with external to the household persons (Carrasco and Miller, 2006, 2009; Larsen et al., 2006; Axhausen, 2002; Goulias and Kim, 2005; Arentze and Timmermans, 2008)
• Recent research in travel behavior emphasizes the role played by human interactions on time allocation to activities and travel (Goulias, 2007; Dubernet & Axhausen, 2014)
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• Daily interpersonal contacts is a determinant and motivation of behavior and can be classified according to a field of action of an individual that changes gradually in one's life course (Goulias, 2009) and as an outcome of roles in social networks (Carrasco and Miller, 2006, 2009)
• E.g. Changes in my daily schedule over time
Introduction
6th Grade
8 School 15 Play soccer with schoolmates 17 Snack with schoolmates 18 English Academy
College
6 Swimming 10 Econ Geo Class 13 Group meeting for Assignment 15 Climatology Class 17 Dinner with College friends and Karaoke
Full-time Job at KOTI
9 Work 13 Meeting with Freight model team 17 Meeting with Policy Support System team 19 Dinner with KTDB colleagues
Grad student with Family
8 Swimming 11 TA for Transport modeling class 13 Office hour as TA 14 Geo-Stats Class 18 Dinner with family
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Introduction
• Our interest includes an explicit accounting of daily contacts (with whom and for whom) in a model system of equations that are able to show the role life cycle stages play in differentiating among persons' propensity to interact with other persons in a day
• We also want to do this in a time allocation model system that allows modeling trade-offs among activities and study the day-of-week differences
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Data & Descriptive Analysis
• CentreSim database 2002 – Sample size: 1471 persons from 718 households
– Location: Centre County, Pennsylvania
– Each person provides their two-day activity information along with answers to the question “with whom the activity was completed” and “for whom the activity was completed” for each activity
Source : Google map 7
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Data & Descriptive Analysis
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• Social Network – 1) Family 2) Relatives 3) Friends 4) Businessmates 5) Schoolmates 6)
Clubmates 7) others
• Contacts Variables – Total number of people contacted in two days in a certain category of
relationship
e.g. 1) # of Family contacts in two days 2) # of Relatives Contacts in
two days, and so on.
– Total number of persons for whom each activity was conducted in two days
Data & Descriptive Analysis
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Data & Descriptive Analysis
0 5 10 15 20 25 30
Life-Cycle Stages with the Number of Contacts in Two days
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Data & Descriptive Analysis
0 200 400 600 800 1000 1200 1400 1600 1800 2000
Life-Cycle stages with Total Activity Duration in Two Days
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Data & Descriptive Analysis Life-Cycle Stages with the Number of activities for Self and Others in Two days
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Data & Descriptive Analysis Life-Cycle stages with Total Activity Duration for Self and Others in Two Days
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Path Model (SEM) Specification
Schematic of the Full Model with Broad Categories
Children < 17 years old College Students
Home duties Part-time with Kids
Part-time no Kid Fulltime with Kids
Fulltime no Kid Retired and Disabled
Friday Saturday Sunday
Family Relatives Friends
Club-mates
Work School Sleep
Home-leisure Home-other
Shopping Social Service
Total Travel time
Accessibility
Spatial Category
Life Cycle Category
Day of the Week Category
Number of people with whom interacted in a day
Amount of daily activity time
Amount of daily activity time
Travel time
Family Relatives Friends
Club-mates
For how many people they do something in a day
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Path Model (SEM) Specification
Schematic of the No-Contacts Model with Broad Categories
Children < 17 years old College Students
Home duties Part-time with Kids
Part-time no Kid Fulltime with Kids
Fulltime no Kid Retired and Disabled
Friday Saturday Sunday
Work School Sleep
Home-leisure Home-other
Shopping Social Service
Total Travel time
Accessibility
Spatial Category
Life Cycle Category
Day of the Week Category
Amount of daily activity time
Amount of daily activity time
Travel time
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Exogenous Variables - Life Cycle Stage
Life Cycle Category Detailed Life Cycle Stage
Children 1) Child at home, 2) Child at preschool, 3) Child at kindergarten
through 6th grade, 4) Child from 7th to 12th grade
College 5) College/University students
Homeduties 7) Homeduties with no children, 8) Homeduties with children
Parttime without kids 9) Part time worker (<40 hrs per week) with no children
Parttime with kids 10) Part time worker (<40 hrs per week) with children
Fulltime without kids 11) Full time worker (>=40 hrs per week) with no children
Fulltime with kids 12) Full time worker (>=40 hrs per week) with children
Retired & Disabled 13) Retired, 14) Disabled
All others 6) Looking for a job, 15) All other
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Exogenous Variables - Others
• Day of the week - Friday, Saturday, Sunday; A dummy variable is defined based on the first day of interview. Ex) Friday dummy variable indicates the average duration of activities for Friday and Saturday
• Opportunity based Accessibility measure - The number of employees in all types of business establishments within three miles (median of entire travel distance in the CentreSim dataset)
Home Location
Business Establishments
Area within 3 miles from home(in network distance) 17
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Results – Significant Variables
Children < 17 years old College Students
Home duties Part-time with Kids
Part-time no Kid Fulltime with Kids
Fulltime no Kid Retired and Disabled
Friday Saturday Sunday
Family Relatives Friends
Club-mates
Work School Sleep
Home-leisure Home-other
Shopping Social Service
Total Travel time
Accessibility
Spatial Category
Life Cycle Category
Day of the Week Category
Number of people with whom interacted in a day
Amount of daily activity time
Amount of daily activity time
Travel time
Family Relatives Friends
Club-mates
For how many people they do something in a day
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Results – Full model
Children
College
Homeduties
Fulltime with kids
Fulltime no kids
# of family with
# of Relatives with
Work duration
School duration
Sleep duration
Home-Leisure duration
Service duration
Shop duration
Social duration Total Travel
time
Accessibility
Sunday
Friday
Saturday
Chi-square-261.110, df-63 CFI 0.973, TLI-0.924, SRMR 0.017 RMSEA 0.033 Positive significant path
Negative significant path
Parttime with kids
Parttime no kids
Retired & Disabled
# of Friends with
# of Clubmates with
# of family for
# of Relatives for
# of Friends for
# of Clubmates for
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Results – Full model
Children
College
Homeduties
Fulltime with kids
Fulltime no kids
# of family with
# of Relatives with
Accessibility
Sunday
Friday
Saturday
Chi-square-261.110, df-63 CFI 0.973, TLI-0.924, SRMR 0.017 RMSEA 0.033 Positive significant path
Negative significant path
Parttime with kids
Parttime no kids
Retired & Disabled # of Friends with
# of Clubmates with
# of family for
# of Relatives for
# of Friends for
# of Clubmates for
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Findings
• The model identifies a variety of life-cycle dependent roles of interpersonal interactions and “altruistic” activities in daily behavior
– Persons in homeduties and workers with kids are associated with altruistic activities the most
– Persons in many life-cycle groups do not participate in activities for their relatives
– Children are actively engaged with their family
– Workers without kids and college students interact with fewer family members in a day
– College students and Children are more likely to interact with their friends
– Weekend days are important for interacting with friends and clubmates
– Intra-household contacts and friends play important roles in explaining Maintenance (Service, Shopping) and Discretionary (Home-leisure, Social) activity durations
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Results – Full model
# of family with # of Relatives with
Chi-square-261.110, df-63 CFI 0.973, TLI-0.924, SRMR 0.017 RMSEA 0.033 Positive significant path
Negative significant path
# of Friends with # of Clubmates with
# of family for # of Relatives for # of Friends for # of Clubmates for
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Findings
• When persons need to participate in activities for others, they also interact with them at the same time (e.g., persons in homeduties and their children)
• Sometimes persons participate in activities for others, then interact with them later (e.g. buying a toy for their children)
• Activity participation for others that are not family members inhibits the number of interactions with family members
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Results – Full model
# of family with
# of Relatives with
Work duration
School duration
Sleep duration
Home-Leisure duration
Service duration
Shop duration
Social duration
Total Travel time
Positive significant path
Negative significant path
# of Friends with
# of Clubmates with
# of family for
# of Relatives for
# of Friends for
# of Clubmates for
Accessibility
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Findings
• Home based accessibility played a significant role in explaining Maintenance-Discretionary activity and total travel duration
• The with whom variables are stronger direct predictors of activity durations than the for whom variables
• The for whom variables influence activity duration through indirect effect
• Social activity durations and home-leisure activity durations were most sensitive to the inclusion of human interactions variables in the model
• Trade-off relationships among different types of activity durations were found except from Service to Travel time and Sleep to Leisure at home
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Results – No-Contacts Model
Children
College
Homeduties
Fulltime with kids
Fulltime no kids
Work duration
School duration
Sleep duration
Home-Leisure duration
Service duration
Shop duration
Social duration Total Travel
time
Accessibility
Sunday
Friday
Saturday
Chi-square-261.110, df-63 CFI 0.988, TLI-0.974, SRMR 0.014 RMSEA 0.023 Positive significant path
Negative significant path
Parttime with kids
Parttime no kids
Retired & Disabled
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Results – Differences between two models
Children < 17 years old College Students
Home duties Part-time with Kids
Part-time no Kid Fulltime with Kids
Fulltime no Kid Retired and Disabled
Friday Saturday Sunday
Work School Sleep
Home-leisure Home-other
Shopping Social Service
Total Travel time
Accessibility
Spatial Category
Life Cycle Category
Day of the Week Category
Amount of daily activity time
Amount of daily activity time
Travel time
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Results – Differences between two models
Children < 17 years old College Students
Home duties Part-time with Kids
Part-time no Kid Fulltime with Kids
Fulltime no Kid Retired and Disabled
Friday Saturday Sunday
Work School Sleep
Home-leisure Home-other
Shopping Social Service
Total Travel time
Accessibility
Spatial Category
Life Cycle Category
Day of the Week Category
Amount of daily activity time
Amount of daily activity time
Travel time
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• Many significant indirect paths were found with the full model, and this confirms the need to incorporate human interactions and the paths of influence among daily activity durations
• A comparison between a model with no contacts and the full model with the daily contacts shows Fulltime workers, Parttime workers with kids, and college students are the most sensitive to the interpersonal contacts and the number of altruistic activities in time allocation
• Allocation of time to discretionary activities (particularly social activity and home leisure activity) is the most sensitive to specifications that control for number of daily contacts
Findings
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• Aggregation of activity types confounds the influence of exogenous variables on duration (e.g., shopping), aggregation of children in the same group does not allow us to distinguish among different time allocations
• Although we find a clear influence of the day of the week on human interaction and time allocation, analyzing averages of two days masks the influence of each day of the week
Limitations
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Acknowledgement
Funding for this research was provided by • The University of California Multicampus
Research Program Initiative on Sustainable Transportation
• The University of California Transportation Center (UCTC)
• The University of California Center on Economic Competitiveness in Transportation (UCCONNECT)
• Grants of the University of California Santa Barbara Office of Research and the College of Letters and Science.
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Thanks very much
Questions?
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