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Analyzing Sources of Variability in Travel Time Use in a Combined Framework Using Extended Structural Equation Models and the UK National Travel Survey Data

Kaveh Jahanshahi, Ying Jin, Ian H. Williams

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Abstract

This paper presents a new approach to investigating comprehensively the influences upon the variations in personal travel times. The influences include socio-economic and demographic characteristics of the travellers and their households, accessibility, land use characteristics of their residential areas, and the interactions between different trip purposes. Existing literature has variously examined such influences, but so far as the authors are aware this is the first time that all the above influences are examined within one combined framework. This is made possible through the use of extended structural equation models. The work presented here is focused on home to work journeys and shopping which takes the bulk of the personal travel times. The methodology is a general one and the investigation can be further expanded to include other travel purposes in the investigation, and indeed to investigate personal travel distances or trip rates. The authors use the UK National Travel Survey data from 2003 to 2008, which is a consistent and sufficiently large sample for this purpose. At the national level, they find that over the six years from 2003 to 2008 there is no evidence of any significant trend in travel time spent, either for home to work journeys or shopping, provided that appropriate explanatory variables are included in the model. At a personal level, they find that there is a wide range of variables that exert significant influences both directly and indirectly. Because socio-economic and demographic variables have a pronounced effect on residential location patterns and because all of these in turn influence car ownership rates, there is naturally a high degree of inter-correlation between the set of such influences on travel time, which is why the SEM-based approach has proved essential. The findings also show significant interactions among the trip purposes which should be considered for inclusion within advanced travel demand models.

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What this paper is about

This paper presents a new approach to investigating comprehensively the influences upon the variations in personal travel times. The influences include socio-economic and demographic characteristics of the travellers and their households, accessibility, land use characteristics of their residential areas, and the interactions between different trip purposes. Existing literature has variously examined such influences, but so far as the authors are aware this is the first time that all the above influences are examined within one combined framework. This is made possible through the use of extended structural equation models. The work presented here is focused on home to work journeys and shopping which takes the bulk of the personal travel times. The methodology is a general one and the investigation can be further expanded to include other travel purposes in the investigation, and indeed to investigate personal travel distances or trip rates. The authors use the UK National Travel Survey data from 2003 to 2008, which is a consistent and sufficiently large sample for this purpose. At the national level, they find that over the six years from 2003 to 2008 there is no evidence of any significant trend in travel time spent, either for home to work journeys or shopping, provided that appropriate explanatory variables are included in the model. At a personal level, they find that there is a wide range of variables that exert significant influences both directly and indirectly. Because socio-economic and demographic variables have a pronounced effect on residential location patterns and because all of these in turn influence car ownership rates, there is naturally a high degree of inter-correlation between the set of such influences on travel time, which is why the SEM-based approach has proved essential. The findings also show significant interactions among the trip purposes which should be considered for inclusion within advanced travel demand models.

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Available abstract

This paper presents a new approach to investigating comprehensively the influences upon the variations in personal travel times. The influences include socio-economic and demographic characteristics of the travellers and their households, accessibility, land use characteristics of their residential areas, and the interactions between different trip purposes. Existing literature has variously examined such influences, but so far as the authors are aware this is the first time that all the above influences are examined within one combined framework. This is made possible through the use of extended structural equation models. The work presented here is focused on home to work journeys and shopping which takes the bulk of the personal travel times. The methodology is a general one and the investigation can be further expanded to include other travel purposes in the investigation, and indeed to investigate personal travel distances or trip rates. The authors use the UK National Travel Survey data from 2003 to 2008, which is a consistent and sufficiently large sample for this purpose. At the national level, they find that over the six years from 2003 to 2008 there is no evidence of any significant trend in travel time spent, either for home to work journeys or shopping, provided that appropriate explanatory variables are included in the model. At a personal level, they find that there is a wide range of variables that exert significant influences both directly and indirectly. Because socio-economic and demographic variables have a pronounced effect on residential location patterns and because all of these in turn influence car ownership rates, there is naturally a high degree of inter-correlation between the set of such influences on travel time, which is why the SEM-based approach has proved essential. The findings also show significant interactions among the trip purposes which should be considered for inclusion within advanced travel demand models.

Key concepts: Travel survey, Structural equation modeling, Travel behavior, Sample (material), Work (physics), Survey data collection, Econometrics, Geography

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Analyzing Sources of Variability in Travel Time Use in a Combined Framework Using Extended Structural Equation Models and the UK National Travel Survey Data — Research Paper | ScholarLens