0.484. 2 or more clubs. 0.593. 0.625. # very strong ties. 0.022. # reasonable strong. -0.010. -0.012. Monday. -0.459. -0.678. Wednesday. -0.603. Saturday. 0.861.
Location-type Choice for Face-to-face Social Activities and its Effect on Travel Behavior
Pauline van den Berg Theo Arentze Harry Timmermans
Introduction
• Predict the generation and spatial distribution of social activities and the travel involved
Structure • Background • Data and methods • Results
Background Activity space: • frequently visited activity locations and routes between these locations
Social activity locations: • home, house of friends and relatives, bars, restaurants, club facilities
Background • Social activities account for 15% of all trips
• Trips for social interaction are longer than average • Social travel distances are growing (more spread social networks)
Background • Insight into frequency of face-to-face social activities, their purpose and the location type, distance and transport mode is needed.
Data and methods • Social interaction diary
Data and methods • Social interaction diary
• • • •
January - June 2008 Eindhoven region 747 respondents 8074 social interactions (4177 face-to-face)
Data and methods – analysis framework
Data and methods – analysis framework For each diary day (N=1494): 1. The number of face-to-face social activities
Data and methods – analysis framework For each diary day (N=1494): 1. The number of face-to-face social activities
For each face-to-face social activity (N=4177): 2. The purpose of the interaction 3. The type of location
Data and methods – analysis framework For each diary day (N=1494): 1. The number of face-to-face social activities
For each face-to-face social activity (N=4177): 2. The purpose of the interaction 3. The type of location
If social travel was involved (N=1878): 4. The distance to the activity location 5. The transport mode used
Data and methods – explanatory variables • • • • • •
gender, age partner, children education, income, work status car ownership, urban density number of clubs, social network size day of the week
Data and methods – explanatory variables • • • • • •
gender, age partner, children education, income, work status car ownership, urban density number of clubs, social network size day of the week
• Earlier predicted variables are explanatory variables in the following models
Results
Results (1) Model 1: Poisson regression model – number of interactions B Male
-0.100
Partner
-0.099
Children under 18
0.240
Primary education
-0.212
Involved in 2 or more clubs
0.163
# very strong network ties
0.007
# reasonable strong ties
0.003
Sunday
-0.412
Results (1) Model 1: Poisson regression model – number of interactions B Male
-0.100
Partner
-0.099
Children under 18
0.240
Primary education
-0.212
Involved in 2 or more clubs
0.163
# very strong network ties
0.007
# reasonable strong ties
0.003
Sunday
-0.412
Results (1) Model 1: Poisson regression model – number of interactions B Male
-0.100
Partner
-0.099
Children under 18
0.240
Primary education
-0.212
Involved in 2 or more clubs
0.163
# very strong network ties
0.007
# reasonable strong ties
0.003
Sunday
-0.412
Results (1) Model 1: Poisson regression model – number of interactions B Male
-0.100
Partner
-0.099
Children under 18
0.240
Primary education
-0.212
Involved in 2 or more clubs
0.163
# very strong network ties
0.007
# reasonable strong ties
0.003
Sunday
-0.412
Results (2) Model 2: MNL – Purpose of social activities N
%
Joint activity
835
20%
Visit/host
592
14%
Talk/chat
1185
28%
Short question/message
353
8%
Info/advice/discussion
535
13%
Other
656
16%
4177
100%
Results (2) Joint activity Male
60
Partner
Question / mess.
-0.068
-0.085
0.079
Results (2) Joint activity Male
60
Partner
Question / mess.
-0.068
-0.085
0.079
Results (2) Joint activity Male
60
Partner
Question / mess.
-0.068
-0.085
0.079
Results (2) Joint activity Male
60
Partner
Question / mess.
-0.068
-0.085
0.079
Results (2) Joint activity Male
60
Partner
Question / mess.
-0.068
-0.085
0.079
Results (2) Joint activity Male
60
Partner
Question / mess.
-0.068
-0.085
0.079
Results (2) Joint activity Male
60
Partner
Question / mess.
-0.068
-0.085
0.079
Results (2) Joint activity Male
60
Partner
Question / mess.
-0.068
-0.085
0.079
Results (3) Model 3: MNL – location-type choice
N
%
Home
904
22%
Home of other person
739
18%
Work / study location
721
17%
Restaurant, bar, cultural
214
5%
En route / outside
416
10%
Sport / club location
401
10%
Other
768
18%
4177
100%
Results (3) Home other Male
Work
Bar, rest.
Sport / club
En route
0.301
60
0.539 -0.442
Partner Children
-0.534
0.877 -0.357
High education
0.774
0.569
-1.077
0.781
No car
0.876
More cars
-0.503
Low urban density
# reasonable strong
0.366
-2.455
Full time work / school
# very strong ties
0.470
0.610
No work / school
No clubs
Other
-0.396 -0.434
-0.322
0.026
0.034 -0.012
Results (3) Home other Male
Work
Bar, rest.
Sport / club
En route
0.301
60
0.539 -0.442
Partner Children
-0.534
0.877 -0.357
High education
0.774
0.569
-1.077
0.781
No car
0.876
More cars
-0.503
Low urban density
# reasonable strong
0.366
-2.455
Full time work / school
# very strong ties
0.470
0.610
No work / school
No clubs
Other
-0.396 -0.434
-0.322
0.026
0.034 -0.012
Results (3) Home other Male
Work
Bar, rest.
Sport / club
En route
0.301
60
0.539 -0.442
Partner Children
-0.534
0.877 -0.357
High education
0.774
0.569
-1.077
0.781
No car
0.876
More cars
-0.503
Low urban density
# reasonable strong
0.366
-2.455
Full time work / school
# very strong ties
0.470
0.610
No work / school
No clubs
Other
-0.396 -0.434
-0.322
0.026
0.034 -0.012
Results (3) Home other Male
Work
Bar, rest.
Sport / club
En route
0.301
60
0.539 -0.442
Partner Children
-0.534
0.877 -0.357
High education
0.774
0.569
-1.077
0.781
No car
0.876
More cars
-0.503
Low urban density
# reasonable strong
0.366
-2.455
Full time work / school
# very strong ties
0.470
0.610
No work / school
No clubs
Other
-0.396 -0.434
-0.322
0.026
0.034 -0.012
Results (3) Home other Male
Work
Bar, rest.
Sport / club
En route
0.301
60
0.539 -0.442
Partner Children
-0.534
0.877 -0.357
High education
0.774
0.569
-1.077
0.781
No car
0.876
More cars
-0.503
Low urban density
# reasonable strong
0.366
-2.455
Full time work / school
# very strong ties
0.470
0.610
No work / school
No clubs
Other
-0.396 -0.434
-0.322
0.026
0.034 -0.012
Results (3) Home other Male
Work
Bar, rest.
Sport / club
En route
0.301
60
0.539 -0.442
Partner Children
-0.534
0.877 -0.357
High education
0.774
0.569
-1.077
0.781
No car
0.876
More cars
-0.503
Low urban density
# reasonable strong
0.366
-2.455
Full time work / school
# very strong ties
0.470
0.610
No work / school
No clubs
Other
-0.396 -0.434
-0.322
0.026
0.034 -0.012
Results (3) Home other
Work
Bar, rest.
Monday
-2.129
Tuesday
-0.757
Wednesday
Sport / club
En route
Other -0.376
-0.609
-0.814
-0.584
Saturday
-2.655
-0.670
-0.697
Sunday
-3.388
-0.658
Friday
# social activities
0.140
Joint activity
0.760
Visit
0.701
1.948
-0.670
-1.969
0.088
0.143
2.132
1.098
-1.237
-1.179
Talk
1.401
Question/message
0.879
0.866
Info/discussion
1.909
1.022
1.016
0.111
-1.720
0.651
0.533
Results (3) Home other
Work
Bar, rest.
Monday
-2.129
Tuesday
-0.757
Wednesday
Sport / club
En route
Other -0.376
-0.609
-0.814
-0.584
Saturday
-2.655
-0.670
-0.697
Sunday
-3.388
-0.658
Friday
# social activities
0.140
Joint activity
0.760
Visit
0.701
1.948
-0.670
-1.969
0.088
0.143
2.132
1.098
-1.237
-1.179
Talk
1.401
Question/message
0.879
0.866
Info/discussion
1.909
1.022
1.016
0.111
-1.720
0.651
0.533
Results (3) Home other
Work
Bar, rest.
Monday
-2.129
Tuesday
-0.757
Wednesday
Sport / club
En route
Other -0.376
-0.609
-0.814
-0.584
Saturday
-2.655
-0.670
-0.697
Sunday
-3.388
-0.658
Friday
# social activities
0.140
Joint activity
0.760
Visit
0.701
1.948
-0.670
-1.969
0.088
0.143
2.132
1.098
-1.237
-1.179
Talk
1.401
Question/message
0.879
0.866
Info/discussion
1.909
1.022
1.016
0.111
-1.720
0.651
0.533
Results (3) Home other
Work
Bar, rest.
Monday
-2.129
Tuesday
-0.757
Wednesday
Sport / club
En route
Other -0.376
-0.609
-0.814
-0.584
Saturday
-2.655
-0.670
-0.697
Sunday
-3.388
-0.658
Friday
# social activities
0.140
Joint activity
0.760
Visit
0.701
1.948
-0.670
-1.969
0.088
0.143
2.132
1.098
-1.237
-1.179
Talk
1.401
Question/message
0.879
0.866
Info/discussion
1.909
1.022
1.016
0.111
-1.720
0.651
0.533
Results (4) Model 1: Tobit regression model – travel distance (log) B Male
0.200
Age < 40
0.439
Children under 18
-0.208
High urban density
-0.263
Tuesday
0.272
Friday
0.283
Saturday
0.362
Sunday
0.417
Joint activity
0.224
Visit
0.513
Short question
-0.413
Home of other person
-0.255
Work or study location
0.689
Results (4) Model 1: Tobit regression model – travel distance (log) B Male
0.200
Age < 40
0.439
Children under 18
-0.208
High urban density
-0.263
Tuesday
0.272
Friday
0.283
Saturday
0.362
Sunday
0.417
Joint activity
0.224
Visit
0.513
Short question
-0.413
Home of other person
-0.255
Work or study location
0.689
Results (4) Model 1: Tobit regression model – travel distance (log) B Male
0.200
Age < 40
0.439
Children under 18
-0.208
High urban density
-0.263
Tuesday
0.272
Friday
0.283
Saturday
0.362
Sunday
0.417
Joint activity
0.224
Visit
0.513
Short question
-0.413
Home of other person
-0.255
Work or study location
0.689
Results (4) Model 1: Tobit regression model – travel distance (log) B Male
0.200
Age < 40
0.439
Children under 18
-0.208
High urban density
-0.263
Tuesday
0.272
Friday
0.283
Saturday
0.362
Sunday
0.417
Joint activity
0.224
Visit
0.513
Short question
-0.413
Home of other person
-0.255
Work or study location
0.689
Results (4) Model 1: Tobit regression model – travel distance (log) B Male
0.200
Age < 40
0.439
Children under 18
-0.208
High urban density
-0.263
Tuesday
0.272
Friday
0.283
Saturday
0.362
Sunday
0.417
Joint activity
0.224
Visit
0.513
Short question
-0.413
Home of other person
-0.255
Work or study location
0.689
Results (5) Model 5: MNL – transport mode choice
N
%
1036
55%
53
3%
Bicycle
482
26%
On foot
275
15%
1846
100%
Car Public transport
Results (5) Car Male
Public transport
Bicycle
-2.313
Children
0.950
0.835
Low education
0.911
0.860
Full time work / school No car
1.964 -3.612
Friday Joint activity
0.970 -0.960
Question / message
-1.074
Sport / club location
1.278
Ln (distance + 1)
3.818
3.868
2.483
Results (5) Car Male
Public transport
Bicycle
-2.313
Children
0.950
0.835
Low education
0.911
0.860
Full time work / school No car
1.964 -3.612
Friday Joint activity
0.970 -0.960
Question / message
-1.074
Sport / club location
1.278
Ln (distance + 1)
3.818
3.868
2.483
Results (5) Car Male
Public transport
Bicycle
-2.313
Children
0.950
0.835
Low education
0.911
0.860
Full time work / school No car
1.964 -3.612
Friday Joint activity
0.970 -0.960
Question / message
-1.074
Sport / club location
1.278
Ln (distance + 1)
3.818
3.868
2.483
Results (5) Car Male
Public transport
Bicycle
-2.313
Children
0.950
0.835
Low education
0.911
0.860
Full time work / school No car
1.964 -3.612
Friday Joint activity
0.970 -0.960
Question / message
-1.074
Sport / club location
1.278
Ln (distance + 1)
3.818
3.868
2.483
Results (5) Car Male
Public transport
Bicycle
-2.313
Children
0.950
0.835
Low education
0.911
0.860
Full time work / school No car
1.964 -3.612
Friday Joint activity
0.970 -0.960
Question / message
-1.074
Sport / club location
1.278
Ln (distance + 1)
3.818
3.868
2.483
Results (5) Car Male
Public transport
Bicycle
-2.313
Children
0.950
0.835
Low education
0.911
0.860
Full time work / school No car
1.964 -3.612
Friday Joint activity
0.970 -0.960
Question / message
-1.074
Sport / club location
1.278
Ln (distance + 1)
3.818
3.868
2.483
Results (5) Car Male
Public transport
Bicycle
-2.313
Children
0.950
0.835
Low education
0.911
0.860
Full time work / school No car
1.964 -3.612
Friday Joint activity
0.970 -0.960
Question / message
-1.074
Sport / club location
1.278
Ln (distance + 1)
3.818
3.868
2.483
Results (5) Car Male
Public transport
Bicycle
-2.313
Children
0.950
0.835
Low education
0.911
0.860
Full time work / school No car
1.964 -3.612
Friday Joint activity
0.970 -0.960
Question / message
-1.074
Sport / club location
1.278
Ln (distance + 1)
3.818
3.868
2.483
Conclusions • Five successive models based on diary data collected in Eindhoven • Insight into frequency of social activities, their purpose and the location type, distance and transport mode
Conclusions • Many significant effects • In particular gender, age, the presence of children in the household, level of education and the day of the week • Earlier predicted variables in the following models
Conclusions • Future research:
• Further analyses of current data set − Time and duration of social activities − SEM: social networks, ICT and social travel
