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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.
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.
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