Whom to hang out with and where? Analysis of the influence of spatial setting on the choice of activity company

Over the past decade there has been an increasing interest into to role of social interactions and social networks for activities and travel. This coincides with a growing awareness that social and recreational trips make up a considerable share of total mobility and deserve more attention in order to understand trends in mobility. Given this trend remarkably little attention has been given to the investigation of the choice of company for social and recreational activities and travel. This paper contributes to filling this gap, by presenting estimation results of models of company choice for social activities, shopping, sport and recreation and cultural activities, based on activity diary data collected in 2007 in the Netherlands. Specific attention is given to the influence of urban form and accessibility of services on company choice. The estimation results suggest that accessibility of facilities has an impact on company choice. However, the mechanisms seem to differ between activity types. For social activities, shopping and sports/recreation, it seems that better access to facilities leads to more joint activity participation, presumably because coordination between involved parties in time and space becomes easier. In other cases (social and cultural activities), close access to facilities seems to lead to a higher probability of single activity engagement, possibly since impulsive activities (usually single) are easier to implement and pooling of facilities is not necessary

Dynamic social networks and travel

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

Modelling the dynamics between social networks and activity-travel behavior: framework and research agenda

Social networks are evidently dynamic; they evolve continuously. Our circle of friends, neighbours and contacts keeps changing with our age and lifecycle events (e.g. marriage). So do our beliefs about our (cognitive) environment, later translated into our activity-travel behaviour. To understand long-term behaviour and decision changes, it is imperative to understand these patterns in a dynamic setting. In this paper, we review the state of the art in travel behaviour research related to social networks and put forward our research concept for a project that is part of a larger research program which aims at developing dynamic activity-based models

On the subjective quality of social Interactions:Influence of neighborhood walkability, social cohesion and mobility choices

Contemporary research in the field of transportation is paying due attention to the geography and composition of personal social networks. However, still little is known about the quality of social interactions, although arguably the subjective quality of social interaction is more important for individuals’ quality of social life than the quantity of it. It is, therefore, important to gain insight in the subjective aspects of social activities in addition to the objective aspects. To that end, this study summarizes empirical evidence of factors that make a particular social interaction valuable. Value or the quality of social interactions is measured by individual’s subjective evaluation of the importance of social interactions. Based on social interaction diary data collected in 2014, two analyses were conducted - a negative binomial regression model to predict the number of (very) important face-to-face interactions per individual, and a two-level ordinal logit model to predict the importance of each interaction. Explanatory variables were individuals’ personal, neighborhood and mobility characteristics. Results suggest that neighborhood and mobility characteristics are important in explaining the quality of social interactions. Frequency of important social interactions is positively associated with frequency of walking or cycling. The frequency of important social interactions was also found to be higher for people living in neighborhoods with higher levels of perceived social cohesion and walkability, and lower for people living in rural areas, in neighborhoods with higher percentages of older residents and in neighborhoods with higher percentages of ethnic minorities. Policymakers, urban planners and decision makers should therefore aim to increase walkability and neighborhood social cohesion, with due attention to neighborhoods with high percentages of elderly and immigrant population