Paper
2. Experimental procedure
4.1.1 Urban Dimensions and Linked Indicators
There are a great many possible empirical measures of urban structure, and we need to specify which are the key measures required to answer the main
research question of the empirical relationships between employment geography and travel sustainability at an intra-metropolitan scale. These measures follow on from the conclusions of the previous three review chapters. We have advocated a comprehensive approach of including socio-economic, built-environment, accessibility and travel pattern measures. These urban dimensions are closely interlinked through the land use transport interactions and the urban market processes specified in Chapter 2. There are therefore typically multiple empirical perspectives on the same urban phenomena. Analysis can be
simplified by grouping measures into linked processes and concepts as shown in Table 4.1. Table 4.1 details the key indicators selected for the analysis of employment geography, urban form and travel sustainability. These indicators are revisited in Section 4.5 after the urban data review sections to summarise how closely the data available fulfils these requirements.
First of all to analyse employment geography we clearly need measures of employment, with the location and volume of jobs. The dynamics of
employment are particularly important, as this measure can be used to identify the degree to which processes of centralisation and decentralisation are occurring. Furthermore the polycentric urban forms and agglomeration discussion in Chapters 1 and 2 highlighted the importance of understanding particular employment types and their geography. We wish to identify agglomerations of productive knowledge economy industries that are driving
changes in urban form. The geography of economic activities can be explored through the concept of employment specialisation. This is a multi-faceted phenomenon connected to a range of empirical measures including industrial classifications, occupational classes, wages and rents (Table 4.1). The incorporation of wages and rents data relates to the agglomeration and urban markets discussion from Chapter 2, with specialist jobs and firms affecting labour and property markets. The intra-metropolitan study of employment specialisation is a novel research direction in this thesis, and at this stage we do not wish to be overly prescriptive regarding the most suitable empirical
indicators. Various measures will be explored and tested in the analysis. Data sources to analyse employment geography are discussed in Section 4.3.
Table 4.1: Key Indicators for the Analysis of Employment Geography and Travel Sustainability
Indicator Concept Empirical Measures
Socio-Economic Geography Employment Workplace jobs
Employment growth and decline
Floorspace growth / urban development Residential population & Workplace jobs Diversity Real estate function
Business mix
Travel Pattern Accessibility Regional accessibility by public transport
Regional accessibility by car
Travel Sustainability
Journey-to-work mode choice Journey-to-work distance Journey-to-work carbon emissions
Whilst employment geography measures are generally overlooked in
sustainable travel research, related urban form measures of density and diversity are common (see Chapter 3). These measures can either be based on socio-economic geographies, or on built-environment geographies using real-estate
research, but is significant as built-environment measures provide a supply-side perspective on where space for economic activities is located, and how property markets and planning policy are interacting. Real-estate data sources are discussed in Section 4.4, and the spatial analysis techniques to measure density and diversity are detailed in Section 4.6. Although the focus of this research is on the influence of employment geography on travel patterns, it is also necessary to include residential geography measures as these have strong connections to travel behaviour. The key influences identified earlier in Chapter 3 include car ownership, income and family structure, as shown in Table 4.1. A number of measures can be considered from both residential and employment geography perspectives, such as occupational class and wages/income. Data sources for demographic variables are discussed in Section 4.3.
The last group of indicators in Table 4.1 are the critical travel pattern indicators.
There are two related but distinct indicator concepts: accessibility and travel sustainability. Accessibility is concerned with potential travel interactions, whilst the travel sustainability measures analyse actual travel interaction data.
The importance of accessibility has already been highlighted in the earlier review chapters. In terms of the empirical measurement of accessibility we advocating in Chapter 3 the need for a regional perspective, disaggregation by mode, and accurate network analysis measures. Spatial analysis techniques and issues regarding accessibility are discussed in Section 4.7. An important issue is the measure of travel cost used, with travel time modelled here rather than a more comprehensive generalised cost approach. Note that the opportunities in accessibility measures (the things urban actors are trying to access) are derived from the above socio-economic and urban form measures in Table 4.1. In Chapter 3 we discussed that local accessibility measures can be calculated in addition to regional measures. Local measures have not been included in this research due to their close correlations with the density and diversity measures and the likely duplication of indicators.
The final indicator concept is travel sustainability. This is based on the mode-choice and travel distance factors identified previously in Chapter 3. The trip pattern data used to calculate mode-choice and travel distances is discussed in
Sub-Section 4.3.3. The major issue with this data is what trip types are covered, and this research is restricted to journey-to-work. The problems with this restriction have been discussed earlier in Sub-Section 3.2.4. The mode-choice and travel distance measures can be combined into composite indicators, with carbon emissions being the focus here, as discussed in Section 4.7.
4.1.2 Indicator Data Requirements
Now that the empirical measures for the research have been specified, we need to consider what are the basic characteristics and qualities of the data sources needed for their inclusion in the research study. These requirements relate to the core data qualities of scale, temporal resolution, availability, and coverage in terms of the UK and other international contexts.
Whilst this research focuses on London and the South East, the aim is to develop a methodology that is widely applicable in many urban contexts. The issues of urban structural change and transport sustainability are universal across all cities, and there are many advantages to having methods that are transferable and allow the kind of comparative studies discussed in the Chapter 3 international city review. To facilitate transferability, national UK datasets are used as the basis of analysis rather than data specific to London. As a result of this approach, the methodology is directly applicable to other UK cities, and also can (with a degree of translation) be applied in other international contexts where similar business survey, census and property valuation data is available.
To allow the intra-metropolitan scale of analysis sought, we need data of sufficient resolution and extent. Issues of scale are discussed in more detail in Section 4.2, and in relation to specific datasets in Sections 4.3 and 4.4. The study area (defined in the next Chapter, Section 5.1) extends beyond the London government boundary, and therefore datasets need to cover the wider South East region. Another important issue is that of temporal resolution. Urban dynamics are critical to understanding how cities are changing and evolving, and to study urban dynamics we require datasets with multiple survey years. This issue is highlighted throughout the Section 4.3 and 4.4 datasets discussion.