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A social network is a representation of an individual’s social connectedness. Fields as distinct as health, psychology and marketing are involved in social network research. A recent promising addition is the field of travel behaviour. In travel behaviour research, traditional factors of interests are facets of travel choice (such as frequency and transport mode) and ownership of mobility resources (such as car, bicycle, discount cards, period travel passes). Gradually, the concern shifted from trip-based to activity-based approaches to model travel properly as a derived demand from the activities that people conduct in space and time. The attention also shifted from individuals to households. Consequently, joint activity scheduling, task allocation, and resource allocation were incorporated in the choice models (Borgers et al. 2002; Ettema et al. 2004; Schwanen et al. 2007; Zhang et al. 2005). However, joint activities do not only involve household members, but may also include members of a person’s social network. Often, we negotiate with our friends and family about where to go for holidays, who should host the New Year party or what movie to go to this weekend. Each individual is part of social networks and individual behaviour will be influenced by peer groups. Spatial behaviour analysis is incomplete without an understanding of this social dimension. To better understand people’s activity-travel patterns, we need to understand how people select and organize their social contacts, adding a whole new dimension of transport behaviour modelling research. However, there is another distinct, and often ignored, feature of personal social networks: it is dynamic. It changes with time and with life course. In this Chapter, we emphasize the need to explain social networks and corresponding activity behaviour in a dynamic perspective. We conclude the chapter with a discussion of constraints and benefits of incorporating these dynamics and suggest directions of future research.

The analyses in the previous chapters of this book have demonstrated and analysed influences from personal networks on social interactions including travel (see Chapter 3) and a Swiss population-wide network (see Chapter 4). Besides the data collection efforts in Switzerland several similar efforts have been undertaken in different parts of the world with the motivation to investigate influences among socio-demographics, personal network characteristics, mobility biographical aspects, social network geographies and spatial patterns between social contacts. In addition to the data collection efforts in Switzerland (Chapter 2, also see Ohnmacht and Axhausen 2005; Chapter 3, also see Frei and Axhausen 2007; Chapter 4, also see Kowald and Axhausen 2012), there have been also collection efforts in Canada (Hogan et al. 2007; Carrasco et al. 2008), the Netherlands (van den Berg et al. 2009), and Chile (Carrasco and Cid-Aguayo 2012). These studies have highlighted similar observations and the relevance of different aspects of individuals’ personal networks on their activity and travel behaviour.

Acknowledging the relevance of social networks on (social) travel behavior, the objective of this paper is to study comparatively the distance patterns between the home locations of social contacts. Analyses are based on five recent personal network data collections from four countries: Canada, Switzerland, the Netherlands, and Chile. Multilevel models, which explicitly account for the hierarchical structure of the data sets, are used to study the role of the explanatory variables to understand the spatiality of social contacts. Modeling results suggest that alter’s characteristics (such as type of relationship, emotional closeness, and duration of the relationship) as well as personal network composition (alters with a certain relationship with the ego) constitute stronger predictors than ego’s socio-demographics across the countries. In addition, the comparative analyses suggest differences between countries on relevant key variables such as ego’s income and the ego-alter tie strength.

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