Current transport facilities are often built around efficiency and meeting the needs of the commuting population. These can therefore struggle to provide services suited to some of the most vulnerable members of society. In order to achieve an inclusive transport system, it is vital that transport authorities have access to detailed insights into the mobility needs and demands of different groups of the population. Increasingly, these transport authorities are making use of smart technologies and the resulting data to gain greater insight into transport users, and in turn inform decision making and policy planning. These smart technologies include automated fare collection (AFC) systems, which produce large volumes of detailed transport and mobility data from smart card transactions. To a lesser extent, retail datasets, such as loyalty card transaction data, have also been utilised. The spatiotemporal components of these data can provide valuable insight into the activity patterns of cardholders that may not be captured in traditional transport data. This thesis presents an exploration of these two forms of consumer data, with a focus on the older population in the West Midlands. Firstly, this thesis demonstrates how smart card data can be processed and analysed to provide detailed insights into the mobility patterns of concessionary bus users and how these relate to long-term changes in bus patronage recorded in the study area. Secondly, the extent to which loyalty card transaction data can be employed to understand retail behaviours and activity patterns is explored, with a focus on how these insights can be used to supplement and enhance the understanding of mobility gained from the smart card data. Finally, these insights are discussed in terms of the capacity of the current transport network to meet the mobility needs of the older population and the potential of consumer data for future transport-related research
