ESRC UCL, Bloomsbury, East London Doctoral Training Partnership Co-funded PhD studentship at the Consumer Data Research Centre (CDRC) in collaboration with Kantar Worldpanel.
This award is open to applicants with backgrounds in quantitative social science and related disciplines, such as geography, social statistics, political science, economics, applied mathematics, planning or sociology. Students will be expected to work with consumer data as part of an exciting multidisciplinary research centre.
In the UK, Kantar Worldpanel maintains a dataset comprising 30,000 households who record and provide their expenditure on goods purchased for home use. There are three nested panels within this large panel, covering out of home purchasing (OOHP), out of home usage (OOHU), and in-home usage (INHU). Each of these is separately weighted to show the total purchasing, representative of the GB population. Weights reflect socio-demographic and behavioural variables known to influence under-reporting. Current weighting approaches are applied in a similar way to flagship research council funded academic panels (for example the ESRC’s Understanding Society survey, which is also supported by Kantar).
Whilst these data provide a robust basis for consumer research, a key challenge is the limited overlap between in home and out of home expenditure. The proposed PhD will develop solutions to this problem based on the following objectives:
1. The synthetic linkage of the aforementioned panels and cohorts based on combinations of attributes from different people.
2. Data fusion through linking together panels and sub-panels across in/out home and consumption/usage to capture the total market. In addition, a number of associated challenges need to be overcome, particularly the relatively small subset of the panel data appropriate to do this.
3. Calibrating data collected by Shoppix, a new mobile app developed by Kantar.
Additional benefits of synthetic linkage might include mapping external variables (e.g. segments) and loyalty card data where the unique identifier is not known. Any methods developed might support weighting/imputation of data from the mobile data application. Most attention will be given to four methodological approaches: linkage, weighting, imputation and modelling. These approaches require careful consideration and the student will be supported both by the academic supervisory team and Kantar’s in-house researchers.
It is anticipated that the work will be of high impact in a number of ways. Firstly, it offers the chance to generate more accurate measures of consumption – essential information for both commerce and social science research. These measures will be the product of significant methodological developments that can be applied to existing data holdings within the ESRC’s Consumer Data Research Centre and also may be of interest to initiatives spearheaded by the Office of National Statistics to derive official statistics from a broader range of consumer datasets. Finally, the outputs will be of significant interest to retailers and businesses with interests in store location.
For more details on this and our other opportunities, please see here: https://www.cdrc.ac.uk/wp-content/uploads/2018/12/CDRC-Co-Funded-PhDs-Sept-2019-FINAL-advert.pdf
If you are interested in this opportunity, please apply by 9am on Monday 11th February 2019. Please send:
- Max 500 word covering email summarising your interest in pursuing this co-funded PhD studentship with the CDRC.
- Academic CV including marks awarded to date plus details of 2 referees.
Please note that only strong candidates (at least 2.1/Merit with elements of first/distinction level) will be considered.