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Title: The applications of loyalty card data for social science
Author: Lloyd, Alyson S.
ISNI:       0000 0004 7661 0219
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2018
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Large-scale consumer datasets have become increasingly abundant in recent years and many have turned their attention to harnessing these for insights within the social sciences. Whilst commercial organisations have been quick to recognise the benefits of these data as a source of competitive advantage, their emergence has been met with contention in research due to the epistemological, methodological and ethical challenges they present. These issues have seldom been addressed, primarily due to these data being hard to obtain outside of the commercial settings in which they are often generated. This thesis presents an exploration of a unique loyalty card dataset obtained from one of the most prominent UK high street retailers, and thus an opportunity to study the dynamics, potentialities and limitations when applying such data in a research context. The predominant aims of this work were to firstly, address issues of uncertainty surrounding novel consumer datasets by quantifying their inherent representation and data quality issues and secondly, to explore the extent to which we may enrich our current knowledge of spatiotemporal population processes through the analysis of consumer activity patterns. Our current understanding of such dynamics has been limited by the data-scarce era, yet loyalty card data provide individual level, georeferenced population data that are high in velocity. This provided a framework for understanding more detailed interactions between people and places, and what these might indicate for both consumption behaviours and wider societal phenomena. This work endeavoured to provide a substantive contribution to the integration of consumer datasets in social science research, by outlining pragmatic steps to ensure novel data sources can be fit for purpose, and to population geography research, by exploring the extent to which we may utilise spatiotemporal consumption activities to make broad inferences about the general population.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available