Abstract for presentation at RGS-IBG Annual International Conference, London, 27-29 August 2014
Shopping is the most frequent reason for travel in the UK, accounting for 20% of all trips (12% of distance) by all transport modes in 2011, with another 10% of trips(7% distance) for personal business such as banking. Taken together, these activities account for 30% of all car journeys and just under a third of CO2 from transport compared with 20% (24% CO2) of journeys for commuting and business travel. In addition, total road traffic volumes are now virtually the same on both days of the weekend as they are during the week, with the hours of 11.00 and 11.59 on a Saturday witnessing virtually the same volumes seen in the peak weekday periods. Yet, very little research or policy attention is paid explicitly to this journey purpose, concentrating instead on the commute and the journey to school. Moreover, the implications of the scheduling and timing of personal travel for energy demand has been generally overlooked in transport and energy policy.
We contend that shopping travel requires more focus than it currently receives not only because it accounts for a significant proportion of everyday travel, but also because of the way that this activity is incorporated into people’s daily and weekly schedule and the role that the scheduling of these activities may currently have on entrenched patterns of car use. For instance, car use allows households to combine journeys and/or concentrate activities over time and may explain the convenience of one-stop shopping in larger and more distant supermarkets. And whilst it would be reasonable to assume that non-car users do smaller and more frequent runs to nearby shops, figures show that even those without a car travel by car for one third of their shopping trips by getting lifts or taxis.
This paper will present analysis of the latest release of the National Travel Survey (NTS) one-week travel diary data to understand the temporal and spatial (distance) patterns of shopping trips across the week and related energy demands. We use various data analysis techniques to assess the relationship between mode use, frequency of shopping trips, timing and distance travelled. Patterns of synchronisation and the relationship to other journey purposes and mode use will be investigated.
We conclude by reflecting on how a more nuanced understanding of the temporal rhythms of energy use from personal travel would benefit the design of sustainable transport policies aiming to influence a variety of outcomes including modal shift, the location of charging infrastructure for plug-in vehicles, parking policy and the regeneration of the high street.
University of Aberdeen