Housing, Location Choice and Travel

As the specific questions around moving to carfree developments have not been addressed in the literature, it may be asked: how do households make their location decisions in general, what role does transport play in this process, and does the literature shed any light on the questions of preferences for (or against) high density urban living?

Studies from a range of disciplines have sought to answer the first of these questions in different ways. Sociological studies have drawn on theories of class, status and social capital to explain household location decisions usually at a neighbourhood or city-wide level (e.g. Butler 2003, Brun, Fagnani 1994) but have not tended to focus on the relationship between location and travel.

The economically-derived studies are generally based explicitly or implicitly on some variety of utility theory where price or willingness to pay is used as a measure of the relative value which households attach to attributes (e.g. of the housing itself, the location and its travel implications) which they are hypothesised to trade off against each other. Some of these studies use hedonic pricing methods (e.g. Arsenio, Bristow 2000) to estimate the utility attached to particular attributes of housing (e.g. size of house, accessibility to services etc.) from variations in market prices.

Other studies (e.g. Kim et al. 2005, Walker et al. 2002) use stated preference experiments which enable the researcher to analyse policy options or housing markets that do not currently exist.

Stated preference experiments have some important disadvantages, however. As Kim et al point out, they are vulnerable to two forms of bias: commitment bias, where willingness to pay is

overstated, and policy bias where respondents seek to influence policy. The concept of commitment bias could be extended, where hypothetical trade-offs are proposed, to a more general problem of ‘wishful thinking’. In a context relevant to this study, Jarvis (2003) found considerable difference between stated preferences and revealed behaviour amongst two-wage

households in the US with pro-urban and low-car preferences, who found their ideals difficult to implement in practice.

The more sophisticated economic studies recognise that social factors such as class and status may play an important role in household location decisions, but these factors are generally treated as exogenous to their models. Thus, as in the debate about transport and the built environment, these models may help to analyse the factors influencing households’ decisions, but without shedding much light on the decision-making process itself.

After reviewing the literature on travel and location choice, Stanbridge (2007) concluded that it “has raised more questions than have been answered”. Amongst these questions is the derivation of the attributes used to model housing and location choices. In some cases attributes are introduced in order to test specific hypotheses. But the rationale for the other independent variables is often absent from the published papers. In some cases it appears constrained by data availability, so Clark and Huang (2003), who use the British Household Panel survey, include marital status but treat cohabiting couples by default with other non-married adults living in the same household, for example.

Measures of ‘goodness of fit’, R² and ρ² of between 0.09 and 0.28 (Kim et al. 2005, Walker et al.

2002, Clark, Huang 2003), suggest the models are only capturing a small proportion of the reasons why people move. One exception to this (Bina et al. 2006) achieved an adjusted R² of 0.83 from a model which included 44 independent variables, with multicollinearity between many of them.

Stanbridge (2007, 2006) approached this challenge in a different way, beginning with semi-structured interviews, followed by a questionnaire. Responses from a sample of 229 recent movers in Bristol produced 67 prompts for moving and 96 search criteria. These were grouped, with some difficulty into 18 general prompts and 19 general criteria. This diversity of responses would indicate part of the problem for quantitative models of location choice.

Stanbridge found that 86% of respondents considered travel at some point in the process, mainly at the search stages. Housing-related prompts (e.g. seeking a bigger or smaller home) were the most frequently cited reasons for moving, by 72.5% of respondents compared to 26.4% for travel-related prompts (respondents could cite more than one reason). Similarly, housing search criteria (particularly property size and price) were cited twice as often as travel-related search criteria.

This is consistent with Clark and Huang’s (2003) national findings that most moves are short in distance, and are most likely to be prompted by life stage changes and/or housing size issues.

Following their move 57% of Stanbridge’s respondents indicated some change to their mode of travel for least one regular journey. She concluded that moving house (possibly along with other life stage changes) weakens travel habits. Any change will happen after the move, but the individual is likely to consider the change at some earlier point in the process. These findings are consistent with the observations from German carfree areas of people giving up cars after moving there.

As nearly all the European carfree areas, and all carfree areas proposed in Britain have been new (as opposed to retrofitted) developments, another issue for this study is that newly built properties have historically only appealed to a minority of potential buyers: 36% might consider one according to an ODPM survey (2003 cited in Leishman et al. 2004). Leishman et al found a general

preference for lower density suburban locations amongst most new-build buyers in Glasgow and Edinburgh. One group, however, preferred flats and inner urban (but not specifically city centre) locations. This group included predominantly younger single households and couples 54% of whom had one car: the published information did not permit an overall comparison of car ownership between the groups, unfortunately.

Respondents with children tended to prefer suburban or out of town locations and houses to flats.

The authors did not attempt to draw any conclusions about the relative sizes of the different groups, but it is worth noting that, contrary to the assumptions behind much of recent discourse in the professional literature (e.g. Williams 2008 and even some academic studies such as Lopez 2008), one and two person households make up 64% of all households in England, compared to just 21% for couples with dependent children (ONS 2009).

One problem sometimes acknowledged (e.g. in the context of different development options Platt et al. 2004) but rarely addressed, is to what extent expressed preferences may reflect other perceived associations. One example relevant to this study might be the influence of traffic noise, pollution and congestion on the relative perceptions of urban and suburban, higher and lower density areas.

Changes in British cities over the recent years have brought new populations into some

regenerated inner city areas. Much of the research in this area has focussed on London, guided by gentrification theory (e.g. Butler 2003). As Tallon and Bromley (2004) point out, London may be something of a special case as a ‘global city’. Their study of central areas in Bristol and Swansea found populations more diverse than the stereotype of young professionals associated with areas such as London’s Docklands. ‘Mundane’ attractions such as proximity to shops and facilities were more important than ‘lifestyle’ factors (although their definitions overlapped somewhat). Noise, traffic and pollution rated highly amongst the residents’ negative perceptions, with reducing traffic

selected by 57% of the Bristol respondents as the most favoured measure to improve their neighbourhood (this question did not appear to have been put to the Swansea sample for some unexplained reason). Most of the respondents in both cities were living in flats, and levels of car ownership (60% in Bristol, 42% in Swansea) were lower than the national and city-wide averages.

Carfree and Urban Living – Contiguity of Aspirations?

The evidence from this and previous sections suggest that for ‘European style’ carfree development to succeed in the UK, sufficient demand would need to exist (or emerge, or be created) amongst people who sought to live:

 Without a car

 In inner urban areas

 In high density housing

 In newly built housing

A minority of people can be identified in each of these categories and it can be demonstrated that people currently living in each of the first three circumstances also tend to exhibit the two others.

There is evidence of contiguity of aspirations towards the last three circumstances amongst a minority of home buyers, although whether these people would also be attracted to carfree living has not yet been established. Whether different styles of carfree developments could also succeed in other circumstances, such as lower density suburban or ex-urban areas, has not yet been studied in a UK context, although the evidence suggests this would be more challenging from a design and possibly a demand perspective.