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TitleSocial Activity-Travel Patterns: The Role of Personal Networks and
LanguageEnglish
File Size914.8 KB
Total Pages161
Table of Contents
                            Contents
List of figures
List of tables
1. Introduction
2. Theoretical framework
3. Data collection
4. Basic sample characteristics
5. Predicting social network characteristics
6. Social interaction between social network members
7. Social interaction and ICT-use
8. Social activity-travel patterns
9. Social networks, ICT and social activity-travel
10. Conclusion and discussion
References
Appendix 1: Questionnaire
Author index
Subject index
Summary
Curriculum Vitae
                        
Document Text Contents
Page 1

Social Activity-Travel Patterns: The Role of

Personal Networks and Communication

Technology












PROEFSCHRIFT











ter verkrijging van de graad van doctor aan de

Technische Universiteit Eindhoven, op gezag van de

rector magnificus, prof.dr.ir. C.J. van Duijn, voor een

commissie aangewezen door het College voor

Promoties in het openbaar te verdedigen

op donderdag 13 september 2012 om 16.00 uur









door








Pauline Elisabeth Wilhelmina van den Berg








geboren te Bergeijk

Page 2

Dit proefschrift is goedgekeurd door de promotor:



prof.dr. H.J.P. Timmermans



Coporomotor:

dr. T.A. Arentze







































Copyright © 2012 P.E.W. van den Berg

Technische Universiteit Eindhoven

Faculteit Bouwkunde, Urban Planning Group





Cover design by Joep Verheijen

Printed by the Eindhoven University Press Facilities





BOUWSTENEN NR 162



ISBN 978-90-6814-644-8

NUR-code 955: Bouwkunde

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purpose of discussing or sharing information. This is an intuitive finding, indicating

that education level and full time work are related to a need or preference for

sharing information.

For car ownership no significant effect is found on the purpose of a social

interaction. A large social network is found to have a negative effect on choosing

joint activities and talking as a social interaction purpose.



Table 7.2: Estimation results for social interaction purpose



Joint

activity

Visit /

host

Talk Question Appoint-

ment

Discuss

Random parameters

Constant -0.074 -1.283 ** 1.384 ** 1.179 ** 0.316 0.316

Nonrandom parameters

Male -0.429 * -0.391 * -0.418 ** -0.376 ** -0.170 0.109

Age < 30 0.397 0.393 0.387 0.501 0.663 * 0.038

Age >50 -0.161 -0.308 -0.488 ** -0.424 * -0.257 0.134

Partner -0.585 ** 0.200 -0.434 ** -0.142 -0.252 0.083

Children -0.429 -0.139 -0.154 -0.171 -0.163 -0.064

Low education -0.345 0.015 -0.325 * -0.426 ** -0.487 ** -0.383 *

High education 0.279 0.003 0.074 0.049 0.020 0.460 **

No work -0.150 -0.338 -0.264 * -0.579 ** -0.224 -0.320 *

Full time work 0.200 0.137 0.220 0.138 0.253 0.408 *

Car 0.360 0.190 0.172 -0.068 0.124 -0.297

Small network -0.192 -0.227 -0.203 -0.138 -0.121 -0.048

Large network -0.801 ** 0.158 -0.292 * -0.222 -0.270 -0.257

Club member 0.240 0.199 -0.051 0.280 0.048 0.282 *

Saturday 0.370 0.570 ** 0.254 0.093 0.114 -0.201

Sunday -0.105 0.663 ** -0.203 -0.271 0.209 -0.363

Group 0.702 ** 0.572 ** -0.392 * -1.559 ** -1.634 ** -0.704 **

1 Relative -0.071 -0.155 -0.042 0.139 -0.442 * 0.172

Very strong tie 0.884 ** 0.528 * 0.473 ** 0.390 * 0.371 -0.248

Somew. strong 0.755 ** 0.657 ** 0.517 ** 0.315 0.596 ** 0.248

Known 15 yrs -0.003 0.808 ** 0.155 0.262 0.564 ** 0.047

Ln distance -0.118 * 0.055 0.202 ** 0.002 0.100 * 0.133 **

St. deviations 0.380 ** 0.102 0.288 ** 0.434 ** 0.525 ** 0.377 **

Number of observations 5822

Number of groups 741

Log likelihood function -9836.79

Restricted log likelihood -11329.09

R-squared 0.132

R-squared adjusted 0.128

** significant at the 0.01 level, * 0.05 level

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69



People who are involved in one or more clubs are found to be more likely to discuss

or share information. Whereas a positive effect on joint activities would be

expected, this effect is not significant.

With regard to day of the week the results indicate that people are more

likely to visit or receive guests during the weekend. This is a plausible finding as

people have more free time during the weekend and visits tend to take more time

than social interactions for other purposes.

As was the case in the previous chapter, in this model the characteristics of

the contacted person(s) are found to be highly significant in explaining social

interaction behavior, in this case the purpose of the social interaction. Social

interactions with a group are more likely to be for the purpose of a joint activity or a

visit and less likely for talking, questions or messages, making an appointment and

discussing or sharing information. Social interactions with a relative are less likely

to have the purpose of making an appointment.

If the tie between ego and alter is very strong or somewhat strong the

interaction is more likely to have the purpose of a joint activity a visit, talking, a

question or making an appointment, relative to the purpose ‘other’. If ego and alter

have known each other 15 years or more they are more likely to make an

appointment and visit each other, relative to other purposes. Finally, the results

indicate that if the distance between ego and alter is larger, they are less likely to

perform joint activities and more likely to interact for the purpose of talking, a

question or message, making an appointment or discussing. This is probably also

related to a different communication mode. The next section analyzes the choice for

a communication mode for social interaction.

7.4 Communication mode choice

The last model in this chapter is used to analyze the communication mode choice

for social interaction. Again, a panel mixed logit model (as described in section 5.3)

is estimated because each respondent has several choice situations and preference

heterogeneity between the respondents is expected. The choice between face-to-

face, landline phone, mobile phone, SMS, e-mail and IM is considered. The first

category, face-to-face, serves as the reference category in the model. Thus, the

coefficients estimated are interpreted relative to choosing face-to-face social

interaction.

As in the previous model, the explanatory variables in this model are the

personal characteristics of the ego as well as the characteristics of the contacted

person(s). Again in this model, the alternative specific constants are introduced as

random parameters. They estimated as normally distributed parameters in order to

allow parameters to get both negative and positive values. Again, 100 Halton draws

are used in the simulation.

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Curriculum Vitae









Pauline van den Berg was born on February 1
st
, 1980, in Bergeijk, the Netherlands.

After finishing pre-university education in 1998 at Rythovius college in Eersel, she

studied Cultural Anthropology at Catholic University of Nijmegen. She graduated

in 2002.



From 2002 to 2007 she studied Architecture, Building and Planning at Eindhoven

University of Technology. She graduated in 2007 within the Urban Planning Group.

Her graduation project dealt with the design of a data collection instrument for

collecting data on social networks, ICT and social activity-travel patterns.



After her graduation she continued her research on the role of social networks and

ICT in social activity-travel patterns at the Urban Planning Group in a PhD project

of which the results are presented in this dissertation.



Her research interests are in the areas of human behavior and its social and cultural

context, urban and transport planning, activity-travel behavior and data collection

techniques.

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