A path analysis of social networks, ICT use and social activity-travel patterns. Pauline van den Berg Theo Arentze Harry Timmermans

Transcription

1 A path analysis of social networks, ICT use and social activity-travel patterns Pauline van den Berg Theo Arentze Harry Timmermans

2 Introduction Social activity travel - responsible for a large portion of - social travel demand is growing - differs from other travel purposes - factors influencing social activity travel

3 Introduction Social activity travel Socio-demographic and land-use characteristics Social networks ICT use for social communication

4 Aim Personal and land-use characteristics ICT use for social interaction Social travel behavior Social network characteristics

5 Structure Data collection Methods and model structure Results

6 Data collection 2-day social interaction diary Joint activities of a social nature Social communications by ICT Type of interaction, time, with whom, location, In case of travel: mode and

7 Data collection January - June 2008 Eindhoven region 747 respondents, 1878 for social activities

8 Data exogenous variables Personal and land-use characteristics - Gender - Age - Child(ren) in household - Work - Education - Car ownership - Involvement in clubs - Urban density - Number of facilities within 1 km - Day of the week

9 Data endogenous variables Social network characteristics - Size ICT-use for social interaction - Number of telephone in 2 days - Number of internet ( , IM, chat) Social activity-travel - Number of walks - Number of bike - Number of car - Social travel

10 Methods Path analysis Relationships between several dependent and independent variables Special case of structural equation modeling (SEM) Deals only with measured variables

11 Model structure 2 models: - Personal and land-use variables are exogenous - Social network affects ICT-use and social travel variables - Telephone and Internet affect each other, and travel - Number of by different modes affect each other Model 1: Numbers of affect social travel Model 2: Feedback loops between travel and number of

12 # Bike # Car

13 Male # Bike # Car

14 Male Age # Bike # Car

15 Male Age Children # Bike # Car

16 Male Age Children Full time work # Bike # Car

17 Male Age Children Full time work High education # Bike # Car

18 Male Age Children Full time work High education # Bike # Car Car

19 Male Age Children Full time work High education # Bike # Car Car Clubs

20 Male Age Children Full time work High education # Bike # Car Car Clubs Low density

21 Male Age Children Full time work High education # Bike # Car Car Clubs Low density # Facilities

22 Male Age Children Full time work High education # Bike # Car Car Clubs Low density # Facilities Weekend

23 Model 1 interaction # Bike # Car interaction

24 Model 1 interaction # Bike # Car interaction

25 Model 1 interaction # Bike # Car interaction

26 Model 1 interaction # Bike # Car interaction

27 Model 1 interaction # Bike # Car interaction

28 Model 2 interaction # Bike # Car interaction

29 Summary Relationships between personal characteristics, social networks, ICT and social activity travel Diary data collected in the Netherlands Path analysis

30 Conclusions Social activity-travel is affected by sociodemographic and land-use variables These links are mediated by ICT-use and social network characteristics Many significant effects in line with expectations

31 Conclusions More car for older people Car ownership results in fewer bike and more car Club membership results in larger social network, more walks and bike In low urban density larger social network and more car During the weekend, fewer ICT and social and longer social travel s

32 Conclusions Positive effect of social network on ICT and bike. Positive effect of Internet on telephone (complementarity) More telephone results in more car (complementarity) Complementarity rather than substitution between transport modes Social travel is not only a consequence of number of Number of is also adjusted to total travel (model 2)