A part of the project we carried out a number of workshops in Manchester and Cardiff to test our methodology and introduces the commute-flow classification.
Numerous research studies use commuting data, collected through the Census of Population, to understand social, economic and environmental challenges in the UK. This commuting data has been used to understand patterns; answer questions regarding the relationship between housing and labour markets; and to see if travel behaviour is becoming more or less sustainable over time. However, there is lots of untapped potential for such data to be used to evaluate transport policy and investment decisions so resources are more effectively and efficiently targeted to places of need. In applied public policy a major shortcoming has been a lack of use of this data to support investment in transport which has major implications for economic growth. If transport investments are inefficiently targeted, this restricts the capacity of places to grow economies to their full potential. This wastes their resources by over investing in transport capacity in areas where it is not needed. Equally, it has long been argued that efficient investment in transport is crucial if labour market exclusion, particularly the case of deprived communities, is to be tackled. The aim of the research is to inform community transportation policy and investment and the socio-spatial dimensions of travel to work flows over time (2001-2011).
Our research develops a toolkit to help decision-makers better target investment in transport capacity and infrastructure. The toolkit includes a series of new classifications of commuting flows from the 2001 and 2011 Censuses. It will include a classification of newly developed official Workplace Zones for England and Wales to complement official residential population-based classifications alongside various population, deprivation, investment and infrastructure data. The toolkit will bring these classifications and datasets together online through various mapping and analysis tools to understand the dynamics of commuting between different types of residential and workplace locations over time and combine these datasets and analyses with locally-specific transport investment data. The methodology developed will be applied to England and Wales as a whole but we will use the Manchester as a test-case for our analysis and for development of the toolkit. The use of open source approaches to build the toolkit means that other locations will have the framework to develop their own toolkit. The flow and area-based (Workplace Zones) classifications for England and Wales will complement official ONS residential-based output area classification and existing indices of deprivation. This will be mapped in relation to key transport investments made in Manchester, using local administrative data and overlay these with the results of commuting analysis to support decision-making regarding future targeted public transport infrastructure investment.
The toolkit will be interactive so users can pose policy questions to explore commuting relationships between different places. The strength of this approach is that it will enable policy and decision-makers to test various scenarios for future transport investment depending on problems they have posed. In a hypothetical situation, a policymaker in might ask the question of whether a specific deprived community in their city is more or less connected into a major employment centre than another equally deprived community. The evidence can be used to target funding for an 'into-work-scheme' to help the most disconnected community. The toolkit allows the policymaker to explore levels of commuting and compare the level of connectivity of each neighbourhood to major employment centres. The underlying rationale for the research is that the toolkit will help deliver efficiencies in public and private sector investment. This is crucial at a time when the government is promoting the need for smarter economic growth but doing so in a challenging context in which public sector resources are scarce and the private sector is risk averse.