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In the context of an increasing interest in understanding travel for non-mandatory activities, such as recreation and socializing, this work focuses on studying the relationships between activity participation, social networks, and expenditures in daily travel patterns associated with leisure activities in order to understand people's strategies for performing activities in daily life. Using a 7-day time use diary from a resident sample of Concepción, Chile, along with information about people's socio-demography, social network and expenditure behavior, structural equations models were estimated to study the role of social networks on people's space–time and monetary patterns. The results suggest a positive relationship between people's interaction with their social networks, their expenditure levels, and their space–time activity patterns. The analysis adds empirical evidence towards a better understanding of people's decision-making processes by using a time use and a social networks approach. The model results reveal that out-of-home leisure time has a strong impact on the interactions with alters and monetary expenditures. In this context, "with whom" and how much time someone spends doing a specific activity act as key intermediary dimensions to explain leisure activity participation and travel behavior. [ABSTRACT FROM AUTHOR]

The recent interest in the role of transport in social interactions has been partly motivated by the hope of achieving a better understanding of the role that transport plays in network capital, or the resources that people can gather from their social networks. Despite the relevancy of this question for policy, little empirical work has been done to elucidate this relationship. This paper illustrates a method of data collection and analysis, using the social networks approach to assess the role of transport in social support, both emotional and material. The personal networks of two neighbourhoods in Concepcion, Chile, with different income levels, are compared, focusing on the role of car ownership in network capital, and the relevance of the time and space characteristics of social contacts. The results suggest that having a car at home does not lead to homogeneous access to network capital, which depends heavily on the kind of social resource studied and the income context (neighbourhood) in which the individuals are embedded. The findings also underscore the need to treat social capital as a truly multidimensional concept and the usefulness of the personal networks approach for assessing these complex relationships. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a social activity-travel generation model, which explicitly incorporates the individual’s social dimension through the concept of personal networks, modeling the multilevel structure of social relations defined by these networks. The objective of the analysis is to study the relevance of the social dimension as a source of explanation of social activity-travel generation behavior between an individual and each relevant person of their social life. The paper uses a disaggregated perspective of personal networks, explicitly incorporating the characteristics of each network member as well as the characteristics of the overall social structure. Using an ordinal multilevel specification that accounts for the social network in which individuals are embedded, four dimensions are studied: personal characteristics, “with whom” activities are performed, social network composition and structure, and ICT (information and communication technology) interaction. The results show that a proper and complete understanding of social activity generation requires going beyond the individualistic paradigm, explicitly incorporating the role of the social dimension in the study of this decision-making process. [Copyright &y& Elsevier]

This paper explores the relationship between travel behaviour, ICT use and social networks. Specifically, we outline a theory of social action that can inform how ICTs relates to social activity travel and explore the efficacy of this theory in an empirical setting. We begin by outlining two factors that influence the propensity to travel: an individual's will to initiate events with members of one's social network, referred to as agency, and the social accessibility of network members themselves. Social accessibility defines a series of practical constraints for social-activity travel and agency defines the extent to which an individual will actively work within these constraints to maintain their social network. The theoretical section first unpacks these concepts while embedding them in the research literature, finishing with an operationalisation of agency and social accessibility. Using this theory, the empirical section investigates the relationship between agency, social accessibility, and factors associated with both the respondents and their personal networks. More specifically, we examine how agency levels of interaction are related to differences in demographics, global measures of network structure and composition, and measures of media use, particularly of Internet and telephone. We conclude that individuals who are proximate or more active are more likely to maintain reciprocal relationships, and that more distant or infrequent ties require greater maintenance on the individual's part. We believe that studies of activity-travel and ICTs will benefit from a theoretical lens that articulates some of the transformative effects of ICTs on travel vis-à-vis its effects on social life. Social accessibility and agency can help focus that lens thereby enabling researchers to make potentially more elaborate and realistic models that move beyond the spatial and temporal dimensions into social dimensions. [ABSTRACT FROM AUTHOR]

This paper investigates the spatial distribution of social activity locations. The research makes use of a social interaction potential (SIP) metric to estimate the potential for an individual to participate in a face-to-face social activity at any particular location in the city. The metric is shown to constitute a contact probability field that is sensitive to timegeographic constraints such as home locations, workplaces, and travel times. Empirical case studies drawn from samples in Ghent, Belgium and Concepción, Chile are used to evaluate the effectiveness of the SIP metric in assigning high potential scores to observed social activity episodes. Moreover, a regression model is used to estimate the marginal benefit of using successive levels of constraint detail. The results illustrate both positive and negative aspects of the SIP metric. The metric behaves very well in general; 75% of the time an observed activity location received a score in the 25th percentile. However, lower valued scores were more common in cases when the time-geographic constraints were not very strong (ie, when the commute duration was short), or when activities took place in the homes of the respondents. In the end, the results are a step towards validating the regional scale SIP metric and indicate that it may be useful in microsimulation models of daily travel and activity participation. [ABSTRACT FROM AUTHOR]

Social interaction patterns are relevant to explain (social) travel behavior. As such, the objective of this paper is to comparatively study the factors that influence social interaction frequency among social network members with different communication modes. Based on data from seven surveys on social networks, this analysis seeks to shed some light on (i) the similarities and differences in social interaction frequency patterns, (ii) the relation of personal and network characteristics with observed patterns, and (iii) the extent to which these associations are consistent across contexts, in terms of effect direction and magnitude. A multilevel-multivariate lognormal hurdle model is used to jointly analyze social interaction frequency patterns across all datasets. Level 1 includes information on ego-alter dyad characteristics, level 2 includes ego-level socio-demographic and aggregate social network characteristics, while level 3 includes information specific to each context where data was collected. In line with network capital theory, results show the existence of very consistent associations between social interaction frequency and some network and dyad characteristics such as network size, ego-alter distance, and emotional closeness, which showed some degree of generality irrespective of context. Building up on previous research, results also suggest that the effect of a higher transport cost-to-earnings ratio is more likely to manifest in the tie-formation phase, in such a way that the geographical spread of the network will tend to be smaller, but conditional on such a network distribution, the cost-to-earnings ratio effect becomes negligible. For other variables such as education level, gender and relationship type, effect patterns were less clear, which might be explained by socio-economic, and other contextual factors, as well as methodological differences across studies. The model presented here can provide average levels of demand for social interactions, which bounded by the geographical distribution of networks, can be used to further understand travel demand in urban environments and transportation systems at the local or regional level. [ABSTRACT FROM AUTHOR]