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In this paper, we propose a mixed methods quantitative and qualitative approach to capture fully the measurable and less tangible social impacts of transport projects on local people and communities. The approach was used to assess the potential social impacts of a strategic road by-pass project case study in a deprived region of Wales in the UK. The project specifically aimed to stimulate local economic growth and regeneration in the local areas it serves. In a ‘before and after’ case study, we combined fine-grained, GIS-based spatial analysis of secondary datasets with qualitative participative exercises with the local residents of the five communities living adjacent to the road, and interviews with professional local stakeholders. This mixed methods approach significantly enhanced understanding of both the social benefits and disbenefits of the road project. It helped to reveal local concerns that would not otherwise have been apparent from secondary dataset analysis alone. The qualitative studies were also successful in bringing to the table new ‘hard to reach’ voices that had not been heard through the formal consultation and public engagement process. The study revealed that the social benefits accruing to local people from the project could have been significantly enhanced, whilst a number of its locally occurring negative social impacts could have been avoided had social assessment been employed earlier in the decision processes concerning its routing and design. Recommendations to improve the practice and uptake of social assessments at the option appraisal, project design mitigation and post evaluation stages of transport projects are included in the paper.

Motorised transport infrastructure and increasingly specialised labour markets have resulted in energy intensive commuter patterns in many parts of the world. This is cause for concern due to the possibility of oil price shocks and the need to restrict the combustion of fossil fuels to minimise the chances of runaway climate change. The paper investigates methods to identify the spatial distribution and socio-demographic profiles of those who are vulnerable to high oil prices. It does this by use of four metrics of oil vulnerability which were developed using a spatial microsimulation model and applied to the case study region of Yorkshire and the Humber, UK. The metrics capture different aspects of vulnerability and highlight the importance of translating conceptual definitions into practical metrics. The geographically aggregated results coincide with the literature: rural areas are associated with the highest levels of vulnerability. The individual level results indicate that vulnerability can be prevalent even in seemingly resilient areas. Ultimately, we conclude that the social and spatial distribution of oil vulnerability depends on how an energy-constrained future is envisioned. Creating localised metrics about the future is a challenging task fraught with danger but could, provided that these metrics are interpreted with sufficient humility, aid the development of equitable policies to encourage resilience, as part of a worldwide transition away from fossil fuels.

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