Social activity-travel patterns : the role of personal networks and communication technology

Abstract

Social activities are responsible for an important portion of trips and they constitute the fastest growing segment of travel. Moreover, social activities and mobility are important aspects of people’s quality of life. Therefore, social activities are important for transport planners to take into account. As social activities involve meeting with other persons at a certain time and location, the spatial-choice behavior for social activities is critical for successful urban design and planning. Over the last decades, researchers have attempted to explain individual (social) travel behavior as a result of socio-demographic and land-use variables. However, recently, it has been acknowledged that other variables that offer opportunities for social mobility have to be added. As social travel demand is derived from a wish or need to perform activities with other people, it is important to incorporate social networks into the study. Moreover, social activities are likely to be influenced by the use of new information and communication technologies (ICT’s), as these ICT’s offer new possibilities for the maintenance of social networks that are becoming more geographically spread. Knowledge about the relationship between ICT’s, social networks and social activity-travel behavior is rather limited. In order to assess future transportation needs for social activities, research is needed. The aim of this dissertation is therefore to study the way in which social activity-travel patterns are influenced by people’s personal characteristics, properties of the built environment, ICT-use and social networks. To that end, a data collection instrument was designed. The instrument consists of a two-day paper-and-pencil social interaction diary a questionnaire on personal characteristics and a follow-up questionnaire on personal social network members. The social interaction diary captured data on ICT-mediated social interactions, as well as face-to-face social activities and travel for these activities. In addition, the social interaction diary was used to collect data on the people with whom the respondents interacted during those two days, including age, gender, social category, distance and frequency of communication with different modes. In addition to the social interaction diary a questionnaire was designed to gather data on the respondents’ personal and residential characteristics. To allow the estimation of the impact of the built environment a requirement for the data collection was to secure sufficient variation in characteristics of the built environment. To this end, the sample was stratified by urban density. The data were collected between January and March 2008 in the region of Eindhoven, among 747 respondents, aged 15 or over. To capture the respondents’ social networks, a follow-up questionnaire was used, which was mailed to a subsampleof the respondents. In this social network questionnaire, respondents were asked to record information on all their social network members, including gender, age, social category, how long they have known each other, distance to their homes and the frequency of interaction with each alter by different modes (face-to-face, telephone, SMS, e-mail, IM). The social network questionnaire was completed by 116 respondents. Quantitative analyses were performed on the data. The analyses focus on exploring and testing multivariate relationships in the data. Analyses were carried out to examine the effects of personal characteristics and properties of the built environment on size and composition of social networks; contact frequency and choice between different communication modes, and social activity-travel patterns. The analyses also explored to what extent and how the nature and strength of the relationship between personal characteristics and properties of the built environment and social activity-travel patterns is mediated by ICT-mediated communication and characteristics of social networks. Regression and discrete choice models were used to predict one dependent variable as a function of one or more independent variables. To analyze simultaneously the direct and indirect dependencies between use of communication technology, social networks and activity-travel patterns, a structural equation approach was used. Because the data have a hierarchical structure (individuals (egos) have multiple alters or interactions), multi-level analysis was used. The estimation results of the models allow us to reconstruct the generation of social activities and travel demand for social purposes. The empirical results suggest that the built environment, ICT-use and social networks all play an important role in the generation of social activity-travel and have to be taken into account in transport policy.