- Delft University of Technology, Transport and Planning, Department MemberImperial College London, Civil and Enviromental Engineering, Department Memberadd
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... more
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.
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This paper presents a model of social network evolution, to predict and simulate changes in social networks induced by lifecycle events. We argue that social networks change with lifecycle events, and we extend a model of friendship... more
This paper presents a model of social network evolution, to predict and simulate changes in social networks induced by lifecycle events. We argue that social networks change with lifecycle events, and we extend a model of friendship selection to incorporate these dynamics of personal social networks. The model uses theories of homophily and reciprocity and is formulated in a random utility maximization framework to predict the formation of social ties between individuals in the population. It is then extended to predict the evolution of social networks in response to life cycle events. The model is estimated using attribute data of a national sample and an event-based retrospective dataset collected in 2009 and 2011 respectively. Findings suggest that homophily has a strong effect on the formation of new ties. However, heterophily also plays a role in maintaining existing ties. Although the motivation of this research stems from incorporating social network dynamics in large-scale travel behaviour micro-simulation models, the research can be used in a variety of fields for similar purposes.
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Highlights • The paper summarizes empirical evidence regarding mode choice decision for social trips. • Past behaviour and inherent preferences were taken into account using theory of path dependence. • Life cycle events... more
Highlights
• The paper summarizes empirical evidence regarding mode choice decision for social trips.
• Past behaviour and inherent preferences were taken into account using theory of path dependence.
• Life cycle events were considered as key moments for a subsequent decision making stage.
• Results suggest that mode choices for social activities are for the most part path dependent.
• There is also evidence of switching towards faster and more flexible modes after a life cycle event.
• The paper summarizes empirical evidence regarding mode choice decision for social trips.
• Past behaviour and inherent preferences were taken into account using theory of path dependence.
• Life cycle events were considered as key moments for a subsequent decision making stage.
• Results suggest that mode choices for social activities are for the most part path dependent.
• There is also evidence of switching towards faster and more flexible modes after a life cycle event.
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This paper discusses examples of studies that reflect the recent shift in interest to study dynamics in activity-travel behavior. Studies are classified according the time window of impact (long term life cycle related change vs. short... more
This paper discusses examples of studies that reflect the recent shift in interest to study dynamics in activity-travel behavior. Studies are classified according the time window of impact (long term life cycle related change vs. short term travel information induced change), and exogenous versus endogenous change. As examples of exogenous change, road pricing, increase in energy costs and new technology (electric cars) are selected. Implications of these research findings for Asian countries are discussed.
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Commonly, frequency of social interaction is modelled as a function of an ego’s socio-demographic characteristics and dyad characteristics of ego and alters. This study is based on the contention that proximity to alters and accessibility... more
Commonly, frequency of social interaction is modelled as a function of an ego’s socio-demographic characteristics and dyad characteristics of ego and alters. This study is based on the contention that proximity to alters and accessibility to services and degree of urbanization moderate this relationship. In addition, marking the contribution of this study to the literature, social interaction frequencies are dynamic and change over time. Therefore, face-to-face interaction frequencies are subjected to the history of interaction and distance dynamics between actors. By taking these aspects into account, important research questions can be addressed, for instance, would the frequency of meeting between an ego and an alter increase if the alter lives nearby now, but was previously located far away? Or how often would the ego meet an alter who was living nearby but moved to a more distant location now? The answers could provide important feedback to tie maintenance, strength, disappearances and social travel dynamics over time. This study draws from the concepts of path dependence, life course and accessibility and shows that history and accessibility indicators can explain part of the frequency of face-to-face interactions. Life cycle events were taken as triggers of these changes. Retrospective survey data are used for the analyses. Face-to-face social interaction frequency between egos and their alters was recorded before and after the life cycle event. A stepwise ordered logit model estimation reveals that social travel frequency can be better predicted when geographical indicators and path dependence are included in the model specification.
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Several studies in transportation literature have shown that in the short-term social networks play an important role in discretionary activity and travel decisions of an individual. However, social networks may not remain unchanged in... more
Several studies in transportation literature have shown that in the short-term social networks play an important role in discretionary activity and travel decisions of an individual. However, social networks may not remain unchanged in the long term, particularly in response to life-cycle events (for instance, an employment transition). A change in the social network in turn may have a repercussion on activity and travel behaviour, indicating that an investigation of the long term dynamics of social networks are relevant for understanding activity scheduling, or rescheduling behaviour. To this end, the paper advances the concept of social network dynamics in dynamic activity travel behaviour modelling. It explores the dynamics of social networks and life-cycle events, and their influence on activity and travel needs. Dynamics are assumed to be triggered by life-cycle events. For the purpose of the study an event-based retrospective survey was conducted in 2011 in the Netherlands. A structural equation model was developed to elicit activity and travel needs and their dependencies on life-cycle and social network dynamics. The estimated model takes history dependence of activity and travel needs into account. Results suggest that activity and travel dynamics are influenced by life-cycle and social network dynamics. Moreover social network and activity travel dynamics were found to be interdependent (i.e. a change in one leads to change in the other). Furthermore, the study results confirm the general assumption that travel needs are for the most part influenced by activity needs. The paper concludes that the theory and modelling framework of travel behaviour dynamics should take the dynamics of personal networks into account.
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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... more
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 withlife 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.
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The interaction between the use of Information and Communication Technology (ICT) and travel and transportation has been an important issue in transportation research. ICT may substitute work trips and enhance non-work travel.... more
The interaction between the use of Information and Communication Technology (ICT) and travel and transportation has been an important issue in transportation research. ICT may substitute work trips and enhance non-work travel. Particularly for social activity and travel behaviour existing studies suggest that ICT has complementary effects: ICT enhances social travel or increases efficiency in scheduling the activity by introducing flexibility into it or does both. However, with life cycle events personal social networks and associated (social) travel may change. These disaggregated effects ultimately bring in changes to the overall travel schedule of the ego and eventually to the local travel demand. The paper takes these dynamic effects into consideration and argues on the interrelationships between the modes of social communication. It shows that causal interferences between face-to-face and ICT modes of communication can be in either direction. It is not necessarily from ICT to face-to-face as was assumed in the contemporary researches in the field. Using the event based retrospective data collected in 2011 in the Netherlands a multilevel Structural Equation model of social interaction frequency is estimated. Results show that dynamics of personal social networks influence dynamics of social interactions. The study confirms the hypothesis that the modes of social interaction (face-to-face and ICT) have a mutual causal relationship. They substitute and complement each other. Considering network dynamics induced by life-cycle events, face-to-face interaction substitutes ICT interaction and ICT interaction complements face-to-face communication.
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A nearly one hour documentary diving into the cycling practice in the Netherlands. Selected for International Documentary Filmfestival Amsterdam 2017... more
A nearly one hour documentary diving into the cycling practice in the Netherlands.
Selected for International Documentary Filmfestival Amsterdam 2017
https://www.idfa.nl/nl/film/f217b78e-e7a6-4186-a0ca-85c347c1d7fd/why-we-cycle/docs-for-sale
Selected for International Documentary Filmfestival Amsterdam 2017
https://www.idfa.nl/nl/film/f217b78e-e7a6-4186-a0ca-85c347c1d7fd/why-we-cycle/docs-for-sale
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One of the emerging objectives in transportation research is to understand the long-term social decision dynamics of individuals, be it the social network evolution, social interaction repertoires or the influence of social media and ICT... more
One of the emerging objectives in transportation research is to understand the long-term social decision dynamics of individuals, be it the social network evolution, social interaction repertoires or the influence of social media and ICT on travel. Several challenges, however, await this process. A fundamental challenge is to obtain the longitudinal data of tie formation and maintenance. Longitudinal studies are resource demanding in all instances; more so when privacy issues are of concern as information is requested about individual’s social traits. Moreover, the conceptualization and modelling challenges remain. In this paper, we summarize the need and prospect of analysing and modelling long term dynamics of social networks in transportation research, put forward a conceptual scheme, describe the data collection effort and present the first analyses of network dynamics. The study is part of the U4IA project which focuses on the investigation of dynamic repertoires of activity travel pattern due to both exogenous (social networks, urban form, pricing policies, energy costs) and endogenous (evolving individual and household choices) changes across different time frames (short, mid and long term)
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"The interaction between the use of Information and Communication Technology (ICT) and travel and transportation has been an important issue in transportation research. ICT may substitute work trips and enhances non-work travel.... more
"The interaction between the use of Information and Communication Technology (ICT) and travel and transportation has been an important issue in transportation research. ICT may substitute work trips and enhances non-work travel. Particularly for social activity and travel behaviour existing studies suggest that ICT has complementary effects: ICT enhances social
travel or increases efficiency in scheduling the activity by introducing flexibility into it or does both. However, with changing life events social network and associated travel may change for each ego-alter combination. These disaggregated effects ultimately bring in changes to the overall travel schedule of the ego and eventually to the local travel demand. In this paper we explore these dynamic effects. Using the event based retrospective data collected in 2011 in the Netherlands we developed a mixed logit model of face-to-face (F2F) social interaction frequency. We observe primarily a decline in social interaction frequency for existing ego-alter links. In addition to that we find evidence that ICT has a complementary interaction with social travel with some substitution effects particularly for stronger ties."
travel or increases efficiency in scheduling the activity by introducing flexibility into it or does both. However, with changing life events social network and associated travel may change for each ego-alter combination. These disaggregated effects ultimately bring in changes to the overall travel schedule of the ego and eventually to the local travel demand. In this paper we explore these dynamic effects. Using the event based retrospective data collected in 2011 in the Netherlands we developed a mixed logit model of face-to-face (F2F) social interaction frequency. We observe primarily a decline in social interaction frequency for existing ego-alter links. In addition to that we find evidence that ICT has a complementary interaction with social travel with some substitution effects particularly for stronger ties."
