Can geodemographics be used effectively to improve public service delivery using an example of road traffic safety in London?

Propensity to be involved in a road traffic collision in Greater London depends on many factors, including personal mobility, lifestyle, behaviour, neighbourhood characteristics and environment. This paper addresses the merits of using a spatio temporal approach to the analysis of road traffic collision casualties using post code data of home addresses for drivers and casualties involved. Recently geo-demographic classification has begun to be used with GIS and as a socio-economic tool for both the public and private sector. This research will be using ‘MOSAIC’, geodemographic software from Experian. This study seeks to analyse driver and casualty post code data for road collision in London, over a period of five years from 1998 to March. Results suggest distinct spatial and temporal patterns of geodemographic populations that are more likely to have a high propensity to be involved in a collision either as a casualty or a driver. The results also highlight that certain geodemographic groups have a higher collision involvement propensity at different times of the day. Overall, the study depicts that geodemographics can assist in determining a better understanding of the risks of collision involvement on London’s population.