This volume is based on selected papers presented at the triennial IATBR (International Association for Travel Behavior Research) conference in August 2003. We also published the previous four volumes in this series (by Hensher, Mahmassani, Ortuzar, Stopher); the Hensher volume included a paper by Nobel Prizewinner Dan McFadden and sold out its initial printrun.

In aiming to understand and model peoples’ out-of-home movements, the academic field of transport planning is confronted with two major challenges. Firstly, leisure travel is increasing in importance and is more complex and variable than work-related travel, being less rigid in temporal and spatial patterns and more influenced by external factors such as social contacts or weather conditions. Secondly, traditional aggregated transport models do not include any information on peoples’ social interactions or their personal social networks. In contrast, the recent development and availability of disaggregated models allows more detailed modelling of elements such as individual characteristics, motivations, constraints and travel costs, as well as a consideration of influences from an actor’s social environment. People travel not only within an infrastructure but also within a social structure. These two main factors have driven transport planners to focus on peoples’ interaction and their social network. In recent years there have been a remarkable number of data collection efforts in the field, surveying information on the link between travel behaviour and social motivation. Providing an overview of selected exemplary studies, this volume addresses the overlap between transport planning and methods of social network analysis; applied methods of social network analysis and related empirical results; and current challenges and new research questions in this field.

The recent availability of longitudinal data on individual trip making and activity behaviour has provided analysts with new insights into the structures and motives of daily life travel. Multi-week travel diary data-sets and GPS observations are exciting sources of information for the description and modelling of the variability of individual travel patterns. Through an analysis of these strong new data sets, this book questions what are the most suitable methodological tools to represent the structures of long-term travel behaviour. It also examines what the data tells us about the travellers' motives and looks at how planning should translate the findings into forecasting tools and transport strategies. In doing so, the multifaceted and ambiguous character of daily life travel is revealed, illustrating how, while sound routines in time and space seem to dominate daily life, individuals show a considerable amount of variability and flexibility in travel and activity behaviour.

The recent availability of longitudinal data on individual trip making and activity behaviour has provided analysts with new insights into the structures and motives of daily life travel. Multi-week travel diary data-sets and GPS observations are exciting sources of information for the description and modelling of the variability of individual travel patterns. Through an analysis of these strong new data sets, this book questions what are the most suitable methodological tools to represent the structures of long-term travel behaviour. It also examines what the data tells us about the travellers' motives and looks at how planning should translate the findings into forecasting tools and transport strategies. In doing so, the multifaceted and ambiguous character of daily life travel is revealed, illustrating how, while sound routines in time and space seem to dominate daily life, individuals show a considerable amount of variability and flexibility in travel and activity behaviour.

The recent availability of longitudinal data on individual trip making and activity behaviour has provided analysts with new insights into the structures and motives of daily life travel. Multi-week travel diary data-sets and GPS observations are exciting sources of information for the description and modelling of the variability of individual travel patterns. Through an analysis of these strong new data sets, this book questions what are the most suitable methodological tools to represent the structures of long-term travel behaviour. It also examines what the data tells us about the travellers'' motives and looks at how planning should translate the findings into forecasting tools and transport strategies. In doing so, the multifaceted and ambiguous character of daily life travel is revealed, illustrating how, while sound routines in time and space seem to dominate daily life, individuals show a considerable amount of variability and flexibility in travel and activity behaviour.

The recent availability of longitudinal data on individual trip making and activity behaviour has provided analysts with new insights into the structures and motives of daily life travel. Multi-week travel diary data-sets and GPS observations are exciting sources of information for the description and modelling of the variability of individual travel patterns. Through an analysis of these strong new data sets, this book questions what are the most suitable methodological tools to represent the structures of long-term travel behaviour. It also examines what the data tells us about the travellers'' motives and looks at how planning should translate the findings into forecasting tools and transport strategies. In doing so, the multifaceted and ambiguous character of daily life travel is revealed, illustrating how, while sound routines in time and space seem to dominate daily life, individuals show a considerable amount of variability and flexibility in travel and activity behaviour.

In aiming to understand and model peoples’ out-of-home movements, the academic field of transport planning is confronted with two major challenges. Firstly, leisure travel is increasing in importance and is more complex and variable than work-related travel, being less rigid in temporal and spatial patterns and more influenced by external factors such as social contacts or weather conditions. Secondly, traditional aggregated transport models do not include any information on peoples’ social interactions or their personal social networks. In contrast, the recent development and availability of disaggregated models allows more detailed modelling of elements such as individual characteristics, motivations, constraints and travel costs, as well as a consideration of influences from an actor’s social environment. People travel not only within an infrastructure but also within a social structure. These two main factors have driven transport planners to focus on peoples’ interaction and their social network. In recent years there have been a remarkable number of data collection efforts in the field, surveying information on the link between travel behaviour and social motivation. Providing an overview of selected exemplary studies, this volume addresses the overlap between transport planning and methods of social network analysis; applied methods of social network analysis and related empirical results; and current challenges and new research questions in this field.

In aiming to understand and model peoples’ out-of-home movements, the academic field of transport planning is confronted with two major challenges. Firstly, leisure travel is increasing in importance and is more complex and variable than work-related travel, being less rigid in temporal and spatial patterns and more influenced by external factors such as social contacts or weather conditions. Secondly, traditional aggregated transport models do not include any information on peoples’ social interactions or their personal social networks. In contrast, the recent development and availability of disaggregated models allows more detailed modelling of elements such as individual characteristics, motivations, constraints and travel costs, as well as a consideration of influences from an actor’s social environment. People travel not only within an infrastructure but also within a social structure. These two main factors have driven transport planners to focus on peoples’ interaction and their social network. In recent years there have been a remarkable number of data collection efforts in the field, surveying information on the link between travel behaviour and social motivation. Providing an overview of selected exemplary studies, this volume addresses the overlap between transport planning and methods of social network analysis; applied methods of social network analysis and related empirical results; and current challenges and new research questions in this field.

In aiming to understand and model peoples’ out-of-home movements, the academic field of transport planning is confronted with two major challenges. Firstly, leisure travel is increasing in importance and is more complex and variable than work-related travel, being less rigid in temporal and spatial patterns and more influenced by external factors such as social contacts or weather conditions. Secondly, traditional aggregated transport models do not include any information on peoples’ social interactions or their personal social networks. In contrast, the recent development and availability of disaggregated models allows more detailed modelling of elements such as individual characteristics, motivations, constraints and travel costs, as well as a consideration of influences from an actor’s social environment. People travel not only within an infrastructure but also within a social structure. These two main factors have driven transport planners to focus on peoples’ interaction and their social network. In recent years there have been a remarkable number of data collection efforts in the field, surveying information on the link between travel behaviour and social motivation. Providing an overview of selected exemplary studies, this volume addresses the overlap between transport planning and methods of social network analysis; applied methods of social network analysis and related empirical results; and current challenges and new research questions in this field.

This volume is based on selected papers presented at the triennial IATBR (International Association for Travel Behavior Research) conference in August 2003. We also published the previous four volumes in this series (by Hensher, Mahmassani, Ortuzar, Stopher); the Hensher volume included a paper by Nobel Prizewinner Dan McFadden and sold out its initial printrun.

In aiming to understand and model peoples’ out-of-home movements, the academic field of transport planning is confronted with two major challenges. Firstly, leisure travel is increasing in importance and is more complex and variable than work-related travel, being less rigid in temporal and spatial patterns and more influenced by external factors such as social contacts or weather conditions. Secondly, traditional aggregated transport models do not include any information on peoples’ social interactions or their personal social networks. In contrast, the recent development and availability of disaggregated models allows more detailed modelling of elements such as individual characteristics, motivations, constraints and travel costs, as well as a consideration of influences from an actor’s social environment. People travel not only within an infrastructure but also within a social structure. These two main factors have driven transport planners to focus on peoples’ interaction and their social network. In recent years there have been a remarkable number of data collection efforts in the field, surveying information on the link between travel behaviour and social motivation. Providing an overview of selected exemplary studies, this volume addresses the overlap between transport planning and methods of social network analysis; applied methods of social network analysis and related empirical results; and current challenges and new research questions in this field.

The recent availability of longitudinal data on individual trip making and activity behaviour has provided analysts with new insights into the structures and motives of daily life travel. Multi-week travel diary data-sets and GPS observations are exciting sources of information for the description and modelling of the variability of individual travel patterns. Through an analysis of these strong new data sets, this book questions what are the most suitable methodological tools to represent the structures of long-term travel behaviour. It also examines what the data tells us about the travellers' motives and looks at how planning should translate the findings into forecasting tools and transport strategies. In doing so, the multifaceted and ambiguous character of daily life travel is revealed, illustrating how, while sound routines in time and space seem to dominate daily life, individuals show a considerable amount of variability and flexibility in travel and activity behaviour.

The recent availability of longitudinal data on individual trip making and activity behaviour has provided analysts with new insights into the structures and motives of daily life travel. Multi-week travel diary data-sets and GPS observations are exciting sources of information for the description and modelling of the variability of individual travel patterns. Through an analysis of these strong new data sets, this book questions what are the most suitable methodological tools to represent the structures of long-term travel behaviour. It also examines what the data tells us about the travellers' motives and looks at how planning should translate the findings into forecasting tools and transport strategies. In doing so, the multifaceted and ambiguous character of daily life travel is revealed, illustrating how, while sound routines in time and space seem to dominate daily life, individuals show a considerable amount of variability and flexibility in travel and activity behaviour.

The recent availability of longitudinal data on individual trip making and activity behaviour has provided analysts with new insights into the structures and motives of daily life travel. Multi-week travel diary data-sets and GPS observations are exciting sources of information for the description and modelling of the variability of individual travel patterns. Through an analysis of these strong new data sets, this book questions what are the most suitable methodological tools to represent the structures of long-term travel behaviour. It also examines what the data tells us about the travellers'' motives and looks at how planning should translate the findings into forecasting tools and transport strategies. In doing so, the multifaceted and ambiguous character of daily life travel is revealed, illustrating how, while sound routines in time and space seem to dominate daily life, individuals show a considerable amount of variability and flexibility in travel and activity behaviour.

The recent availability of longitudinal data on individual trip making and activity behaviour has provided analysts with new insights into the structures and motives of daily life travel. Multi-week travel diary data-sets and GPS observations are exciting sources of information for the description and modelling of the variability of individual travel patterns. Through an analysis of these strong new data sets, this book questions what are the most suitable methodological tools to represent the structures of long-term travel behaviour. It also examines what the data tells us about the travellers'' motives and looks at how planning should translate the findings into forecasting tools and transport strategies. In doing so, the multifaceted and ambiguous character of daily life travel is revealed, illustrating how, while sound routines in time and space seem to dominate daily life, individuals show a considerable amount of variability and flexibility in travel and activity behaviour.

In aiming to understand and model peoples’ out-of-home movements, the academic field of transport planning is confronted with two major challenges. Firstly, leisure travel is increasing in importance and is more complex and variable than work-related travel, being less rigid in temporal and spatial patterns and more influenced by external factors such as social contacts or weather conditions. Secondly, traditional aggregated transport models do not include any information on peoples’ social interactions or their personal social networks. In contrast, the recent development and availability of disaggregated models allows more detailed modelling of elements such as individual characteristics, motivations, constraints and travel costs, as well as a consideration of influences from an actor’s social environment. People travel not only within an infrastructure but also within a social structure. These two main factors have driven transport planners to focus on peoples’ interaction and their social network. In recent years there have been a remarkable number of data collection efforts in the field, surveying information on the link between travel behaviour and social motivation. Providing an overview of selected exemplary studies, this volume addresses the overlap between transport planning and methods of social network analysis; applied methods of social network analysis and related empirical results; and current challenges and new research questions in this field.

In aiming to understand and model peoples’ out-of-home movements, the academic field of transport planning is confronted with two major challenges. Firstly, leisure travel is increasing in importance and is more complex and variable than work-related travel, being less rigid in temporal and spatial patterns and more influenced by external factors such as social contacts or weather conditions. Secondly, traditional aggregated transport models do not include any information on peoples’ social interactions or their personal social networks. In contrast, the recent development and availability of disaggregated models allows more detailed modelling of elements such as individual characteristics, motivations, constraints and travel costs, as well as a consideration of influences from an actor’s social environment. People travel not only within an infrastructure but also within a social structure. These two main factors have driven transport planners to focus on peoples’ interaction and their social network. In recent years there have been a remarkable number of data collection efforts in the field, surveying information on the link between travel behaviour and social motivation. Providing an overview of selected exemplary studies, this volume addresses the overlap between transport planning and methods of social network analysis; applied methods of social network analysis and related empirical results; and current challenges and new research questions in this field.

In aiming to understand and model peoples’ out-of-home movements, the academic field of transport planning is confronted with two major challenges. Firstly, leisure travel is increasing in importance and is more complex and variable than work-related travel, being less rigid in temporal and spatial patterns and more influenced by external factors such as social contacts or weather conditions. Secondly, traditional aggregated transport models do not include any information on peoples’ social interactions or their personal social networks. In contrast, the recent development and availability of disaggregated models allows more detailed modelling of elements such as individual characteristics, motivations, constraints and travel costs, as well as a consideration of influences from an actor’s social environment. People travel not only within an infrastructure but also within a social structure. These two main factors have driven transport planners to focus on peoples’ interaction and their social network. In recent years there have been a remarkable number of data collection efforts in the field, surveying information on the link between travel behaviour and social motivation. Providing an overview of selected exemplary studies, this volume addresses the overlap between transport planning and methods of social network analysis; applied methods of social network analysis and related empirical results; and current challenges and new research questions in this field.