Understanding the new digital retail landscape
Lead Research Organisation:
University College London
Department Name: Geography
Abstract
Specifically, I discern three major areas for research during my PhD:
First, the provenance of retail data remains largely unknown. Although a major player in British retailing, Boots data inevitably have only partial market coverage and the source and operation Nof resultant bias is not fully understood. This research avenue begins by creating metadata for a large assemblage of retail data and addressing challenges to effective concatenation and conflation with framework sources such as the 2011 Census (see e.g. Goodchild and Longley, 1999). In line with the project outline, this analysis extends the experiences of the ESRC Consumer Data Research Centre (CDRC) in adapting the use of such data to applications of
wider concern. Given the research centre's broader agenda of facilitating the future sustainability of UK research using consumer data, the research will consider how the data could be appropriate for population analytics and what challenges need to be addressed and overcome.
Second, 'omni-retailing', today occurs at the confluence of the digital and offline economies, and encompasses a number of hybrid forms such as click-and-collect. This research will develop to seek a better understanding of the new retail economy through spatial analysis of Advantage Card data triangulated with a range of administrative and conventional survey sources. Evaluating data pertaining to online, in store and click and collect sales in relation to the CDRC 'Areas and activities' Service Linked Research Project, this research can identify population dynamics at a range of spatial and temporal scales. This work will be related to research within the CDRC that has sought to estimate the e-resilience of British town centres by modelling the local population's engagement with the Internet (see e.g. Singleton et al, 2016). Local indicators of Internet engagement have been built from linking demographic statistics, surveys and internet connectivity data. The research student will seek to understand the implications of Internet use for retailing purposes. By considering data from retailers with both online and offline offerings, it is possible to understand how the population negotiates spending between channels. Crucially, this research also offers insight into why these patterns will vary between households and also retail centres. The importance of the Internet to everyday activities is profound and access to the Internet is now considered a legal right within the UK.
However, open data are yet to catch up and there is insufficient geographic information on Internet usage and behaviour. Consumer data could present exclusive insights into how neighbourhoods engage with online channels.
Third, consumer data have the potential to be of considerable use beyond the retail industry. The data offers the prospect of supplementing official data sources such as the Census of Population. The data could present a unique opportunity to create small area-level indicators on a range of variables which have previously not been available in the public domain. Consumer data have already been found to be useful indicators of local and regional population growth, lifestyle choices and vulnerability to adverse socio-economic conditions. Finally, the work can also link to the current Office for National Statistics Data Science agenda for refining and extending the range of retail relevant official statistics.
First, the provenance of retail data remains largely unknown. Although a major player in British retailing, Boots data inevitably have only partial market coverage and the source and operation Nof resultant bias is not fully understood. This research avenue begins by creating metadata for a large assemblage of retail data and addressing challenges to effective concatenation and conflation with framework sources such as the 2011 Census (see e.g. Goodchild and Longley, 1999). In line with the project outline, this analysis extends the experiences of the ESRC Consumer Data Research Centre (CDRC) in adapting the use of such data to applications of
wider concern. Given the research centre's broader agenda of facilitating the future sustainability of UK research using consumer data, the research will consider how the data could be appropriate for population analytics and what challenges need to be addressed and overcome.
Second, 'omni-retailing', today occurs at the confluence of the digital and offline economies, and encompasses a number of hybrid forms such as click-and-collect. This research will develop to seek a better understanding of the new retail economy through spatial analysis of Advantage Card data triangulated with a range of administrative and conventional survey sources. Evaluating data pertaining to online, in store and click and collect sales in relation to the CDRC 'Areas and activities' Service Linked Research Project, this research can identify population dynamics at a range of spatial and temporal scales. This work will be related to research within the CDRC that has sought to estimate the e-resilience of British town centres by modelling the local population's engagement with the Internet (see e.g. Singleton et al, 2016). Local indicators of Internet engagement have been built from linking demographic statistics, surveys and internet connectivity data. The research student will seek to understand the implications of Internet use for retailing purposes. By considering data from retailers with both online and offline offerings, it is possible to understand how the population negotiates spending between channels. Crucially, this research also offers insight into why these patterns will vary between households and also retail centres. The importance of the Internet to everyday activities is profound and access to the Internet is now considered a legal right within the UK.
However, open data are yet to catch up and there is insufficient geographic information on Internet usage and behaviour. Consumer data could present exclusive insights into how neighbourhoods engage with online channels.
Third, consumer data have the potential to be of considerable use beyond the retail industry. The data offers the prospect of supplementing official data sources such as the Census of Population. The data could present a unique opportunity to create small area-level indicators on a range of variables which have previously not been available in the public domain. Consumer data have already been found to be useful indicators of local and regional population growth, lifestyle choices and vulnerability to adverse socio-economic conditions. Finally, the work can also link to the current Office for National Statistics Data Science agenda for refining and extending the range of retail relevant official statistics.
People |
ORCID iD |
James Cheshire (Primary Supervisor) | |
Markus Loning (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
ES/P000592/1 | 30/09/2017 | 29/09/2027 | |||
1936219 | Studentship | ES/P000592/1 | 30/09/2017 | 30/12/2020 | Markus Loning |