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A Comparative Study of Commuter Patterns and Trends in Great Britain, Ireland and the Us

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A Comparative Study of Commuter Patterns and Trends in Great Britain, Ireland and the Us A COMPARATIVE STUDY OF COMMUTER PATTERNS AND TRENDS IN GREAT BRITAIN, IRELAND AND THE US Ian N Williams Ian Williams Services and Cambridge University 1 INTRODUCTION There are a number of reasons why we need to understand better the forces that shape commuter travel. It continues to be a major user of road and rail capacity in congested peak periods so that forecasting the future pattern of commuter trips is a critical task for most urban passenger models. Commuter travel by car has also been a substantial contributor to the past growth in greenhouse gas emissions so that its future growth trajectory is important to the environment. The quality of the transport facilities that connect homes to workplaces affect the land use policy options available to planners and influence the longer term success of planning policy decisions on residential and business construction location decisions. Patterns of commuting have changed through time but these changes do not always follow simple linear trends. In many countries the long-run trend of increases in commuting trip lengths of the 20th century had eased by the last decade. We need to understand the extent to which this is a result of changes in the underlying patterns of the behaviour of workers within the socio-economic environment they inhabit and the extent to which it is simply a reflection of changes in the transport supply characteristics such as cost and time of travel that are standard inputs to our transport models. The reason for initiating the comparative study presented in this paper was to examine those aspects of commuter patterns that have been shown to be similar across a range of countries and a range of years. Our assumption when forecasting travel demand is that such phenomena are more likely to persist in a stable fashion through into the future than those travel patterns and behaviours that have been observed in only some locations or in some years. This analysis also provides guidance on the most appropriate segmentation of commuter types to adopt within travel demand models so as to enable stable and reliable forecasts of future travel demand to be made. Section 2 outlines the data sources on which the comparative analysis of computing patterns is based. These data are then used in Section 3 to identify the main regularities in commuter travel behaviour across countries and through time. Section 4 speculates on some emerging trends and influences that may change future commuter patterns and so these should be considered within our designs for forecasting models. The reasons why it is important to provide an appropriate degree of segmentation in travel demand models are explained in Section 5. Finally, conclusions are drawn in Section 6 on the manner in which the design of commuter travel demand models should be structured and segmented so as to © Association for European Transport and Contributors 2012 1 enable them to generate robust and realistic future forecasts for use in assessing land-use and transport policy decisions. 2 DATA SOURCES This study focuses on commuter travel patterns in three countries: UK, Ireland and the US, with a particular interest in identifying those behavioural characteristics that appear to have similarities across countries and through time. The main data sources on commuter travel available for each of the three countries are summarised in Table 1. Typically the travel surveys provide detailed data on trends through time and on the characteristics of the trips, whereas the Census data sources provide good spatial differentiation on travel patterns and on the characteristics of the workers. However, for the Census data in particular, a substantial effort is required to convert the data to a form that is adequately consistent between years. The aim should be to avoid the emergence of apparent behavioural trends that in reality are just a side effect of differences between years in ways in which the data collection has either been carried out or processed. Table 1 Sources of data on commuting by country Country Source Years Comment UK NTS 1985/86, 1989 onwards LFS 1992 onwards Mode and travel duration (mins) Census 1981, 1991, 2001, 2011 Mode and travel distance Ireland Census 1981, 86, 91, 96, 2002, 06, 11 US NPTS 1977, 83, 90, 95 NHTS 2001, 2009 Replaces the NPTS Census 1980, 1990, 2000 ACS 2005 onwards Replaces the Census Access to sampled individual population Census records on a comparative basis across countries has improved significantly in recent years as a result of the initiative to assemble census data within the International Integrated Public Use Microdata Series (IPUMS - https://international.ipums.org/international/) by the University of Minnesota. This data is assembled on a reasonably common basis at the anonymised individual level for a large number of countries and for many years for each such country. As yet no detailed data on commuter travel has been published from the most recent 2011 Census in either the UK or Ireland. When published, these data will provide interesting insights into the impacts of the economic recession on commuter behaviour. There are other data sources that also provide insights into commuter behaviour that are not discussed here. For example, Dargay and Hanly (2003) use British Household Panel Survey data from 1991 onwards to examine throughout a 10- year period the year-to-year changes for individuals in their commuter travel and residential and workplace locations. Lyons & Chatterjee (2008) provide a wide- ranging review of the behavioural forces that influence the long commuter distances now travelled, drawing innovatively on research from the fields of psychology, sociology and medicine. Williams (2005) reviewed the main influences on commuter patterns, concentrating on the use of 2001 UK Census data to examine cross-sectional influences in the UK so that it complements the focus here on trends through time and on international comparisons. 3 COMMUTING PATTERNS AND TRENDS 3.1 Average trip lengths by segment In this section we examine regularities across countries in the pattern of average commuting trip length for sub-groups of the working population. Figure 1 Commuter distance (one-way crow-fly kms) by industry (SIC), sex, part-/full-time – internal trips within London, South East and East of England Source: UK 2001 Census Table 2 Key to Standard Industry Codes (SIC) Code Industry Code Industry A Agriculture, hunting, forestry I Transport storage and communication B Fishing J Financial intermediation C Mining and quarrying K Real estate, renting and business activities D Manufacture L Public administration & defence, social security E Electricity, gas and water M Education supply F Construction N Health and social work G Wholesale and retail trade, OPQ Other repair of motor vehicles H Hotels and restaurants Using 2001 Census journey to work data for the wider South East set of regions, Figure 1 illustrates how journey to work distances differ systematically by type of worker. The main findings are: Males travel further than females in almost every specific sub category; Full-time workers travel further than part-time workers in almost every specific sub category; The various sub-categories of worker in higher income service industries (SICs: J, K, L) as well as in transport (SIC I) have longer than average journeys, while those in SICs AB (agriculture) and H (catering) have the shortest average distances. The same broad pattern of trip length differentiation by segment is found in the rest of the UK, as illustrated by the histogram in Figure 2 for female workers resident in the East Midlands. 15.00 10.00 5.00 F1-15 F16-30 F30+ 0.00 AB F G CDE H I J F30+ K L F16-30 M F1-15 N OPQ Figure 2 Commuter distance (one-way crow-fly kms) for females by Industry and hours worked - residents of the East Midlands Source: UK 2001 Census Men commute further than women also in the US and in Ireland. In Ireland the excess distance for males relative to females was 28% in 2006 which is little changed from the 27% rate of 1981, despite the overall growth of around 55% in the average trip length for each sex over this 25 year period to give an overall average of 15.6km in 2006. In Great Britain in 2009 (DfT, 2011), males travelled 16.4km to work on average, which is 51% further than females (10.8km), with an overall average of 13.2km. The high proportion of part-timers among female workers (Figure 3) tends to push down the overall average trip length for females relative to males in the UK. In the US (Santos et al. 2011) the average commuter trip length in 2009 was 19.0km, which is significantly longer than in the UK or Ireland. Figure 3 Number of full- and part-time workers by sex by year, UK (000s) Source: Table EMP01, ONS, http://www.ons.gov.uk/ons/dcp171766_276987.pdf Having analysed the differences in commuter distances between groups in the workforce we can see how this in turn will impact on the overall growth in commuter travel through time. Figure 3 illustrates that only 10% of the growth in employment in the UK since 1992 has been in the full-time male group - that which has the longest average commuter trip lengths. The 90% majority of employment growth has been in the other categories all of which tend to have relatively shorter trip lengths. This structural change in the workforce in the economy will have acted through time to depress the rate of growth in the overall UK commuter trip length. When forecasting overall commuter travel demand into the future it will be important to consider what assumptions should be made: about whether the recent relative growth in the proportion of part-time working, particularly for men, will continue or reverse; and about the future balance of the proportion of females to males in employment.
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