This sub-section introduces the data on the AASR and FGR outlets utilised for this research.
It further seeks to explain the sources of the data, as well as the steps involved in sorting and coding the data into applicable format. The software used in sorting the data are IBM SPSS 24 and Microsoft Excel 2016. The data collection, sorting and coding exercise started in September 2016 and lasted for six months.
76 3.5.4.1 Data: AASR locations in England
AASRs location data includes gambling, payday loan outlets, pawnshop outlets and RTO outlets in England. The data on all gambling locations was obtained from the UK Gambling Commission (GC), which contained all registered and licensed gambling locations in the UK as at April 2015. Only the addresses in England were selected. The Commission provides a comprehensive list of addresses of all gambling establishments (betting shops, family entertainment centres, and casinos) which contained retailers’ names, addresses and postcodes for all outlets in the UK. Therefore, all gambling shop establishment addresses, and postcodes were extracted, with the exception of casinos and family entertainment centres.
From the dataset, some of the addresses and postcodes were incorrect, but these were then largely corrected
Table 3.1 The final number of gambling and financial outlets in England
Retailer Total Outlets
Gambling 10,813
Financial (Fringe Banking and RTO) 1,334
Total 12,147
The locations (addresses) of all financial outlets (payday loans, pawnbrokers and high yield interest loans and RTO establishments) were also collected. For this set of retailers, effort was made to obtain the shop addresses from the respective retailers or regulatory bodies but yielded no results. Therefore, the addresses were obtained manually from the website of each of the retailers and for those retailers that did not have their shop addresses on their websites an online directory1 was used. This task was time-consuming but was painstakingly carried out to ensure that the all known shop addresses were collected. For the RTOs, only two retailers (BrightHouse and PerfectHomes) have physical shop locations in England.
BrightHouse and PerfectHomes have a list of all their locations on their websites. The list of postcodes was extracted manually from their websites. (table 3.1 above shows the total number of gambling and financial outlets finally extracted and corrected in England).
1 The National Pawnbrokers Association has an online directory found at https://www.thenpa.com/
77 3.5.4.2 Data: FGR locations in England
Shop addresses of all major FGRs were also collected. A UK company called Geolytix Ltd has comprehensive open source data on all major food and grocery retailers and so the data was downloaded from their company website. Like the gambling data, the data contained information on the name of the retailers, shop addresses and postcodes in the UK. All England postcodes were extracted. The extracted file contained addresses of 22 chains of grocery retailers including all big multiples (Asda, Sainsbury and so on.) as well as some independent retailers (see table 3.2). Geolytix constantly updates the file, but the available version utilised for this research is the April 2016 version. The file had 26 incorrect postcodes, all of which were corrected by doing a search with each shop address and respective retailer name on google map.
Table 3.2 Major food and grocery retailers in England
3.5.4.3 Sorting, Coding and Processing the location and deprivation data
Sorting and coding the data involved several processes in order to enable linking each retail outlet to its corresponding indices of multiple deprivation data. For the retail location data file, each outlet represented a case. Therefore, there were numerous postcodes which had more than one retail outlet. Therefore, all the multiple postcodes were consolidated, and each group of retailer outlets was aggregated for each corresponding postcode using the consolidate function in Microsoft Excel. In addition, as the Indices of Deprivation data is at LSOA geography, each postcode and its corresponding outlets was then linked to its corresponding LSOA. This was done using a look-up table provided by UK Data Service and an IMD to postcode look-up developed by the Ministry of Housing, Communities and Local Government2.This process was undertaken both groups of retailers’ location data. In addition, for the AASRs, which consist of betting shops, fringe banks and RTOs, the data was further grouped into two sub-sets: betting and financial retailers. The betting retailers
2 http://imd-by-postcode.opendatacommunities.org/
FGR Outlets
England 11,034
78 consist of all gambling locations, while the financial retailers consist of all fringe banks and RTOs. The RTOs and fringe banking outlets were grouped together because of their smaller numbers as well as the similarities in their services. Thereafter, the Geo-convert and Communities and Local Government look-up tables were used to link each LSOA to its corresponding indices of deprivation estimates.
3.5.4.4 Geocoding retailers’ outlets
The above process consolidated all retail outlets per LSOA. Therefore, to display the data in a GIS, the LSOA location was geocoded to represent the location of its corresponding retail outlet(s). “Geocoding” refers to the process of converting physical addresses into geographic coordinates (Boscoe, 2008). At this point, since all the addresses had been consolidated into LSOAs, each LSOA location represented the shop address(es). To achieve this, consideration needed to be given to the actual population distribution and geographical boundaries of each LSOA. Using the centroid of each LSOA assumes that the population is evenly distributed in each LSOA. However, this assumption is incorrect because population is not evenly distributed across space (Moon and Farmer, 2001). Therefore, a method which creates a geo-referenced population centroid was developed by the Office for National Statistics (ONS, 2011) at Output Area (OA), LSOA and Middle Super Output Area (MSOA) levels. This method created a single geographic reference point for each geographical unit (LSOA).
The Excel file, which contains the population weighted centroid geographic co-ordinates (ground reference point) for each LSOA, was downloaded from the ONS website. The ground reference points are in two different projections, namely “longitude and latitude”, and “easting and northing”. It should be noted that either of the two projections can be used, but final choice depends on the coordinate system used for the boundary data (as explained in later sections). Subsequently, the population centroid file was merged with the retailers’
data using the LSOA (present in both files) as the reference point in Excel. The final file therefore contained FGRs, AASRs and gambling and financial outlets, as well as the indices of deprivation estimates (rank and deciles) for income, employment and education, skills and training domains for each LSOA.
79 3.5.4.5 Data: Collection, sorting and coding challenges
Challenges were encountered during the collection, sorting and coding of the retailers’
location data. The GC’s Excel sheet had several errors with the postcodes and some addresses. Some of the postcodes were wrongly inputted, for example, the number ‘0’ was written as a letter ‘O’, ‘I’ was written as one ‘1’ and vice versa, while some addresses were not present and some of the available ones incorrect. This created some initial problems.
Fortunately, the list also contained the majority of the retailers’ addresses. Therefore, to correct the errors, the physical addresses were entered into Google Map and Royal Mail online directory, which produced accurate postcodes. For those which had incorrect addresses, their postcode and name of retailer were used to narrow down the search locations, which aided finding the correct locations. Furthermore, some of the retailers’ websites failed to include complete addresses for some shop locations. For example, Belle Vale, Liverpool store address was not displayed on the Brighthouse website. Google map was also used to resolve these problems.
Difficulties arose during the process of linking up the retailers’ location data to the indices of deprivation estimates. The fringe banking, RTO and grocery retailer location data had only very minor problems (as explained previously), that were corrected using google map services. The major challenges, however, occurred with the gambling data provided by the GC. The geo-convert website failed to match a substantial portion of the gambling retailers’
postcodes to their corresponding area deprivation estimates, and they returned as un-matched.
Further investigations on the website revealed that “genuine codes may remain unmatched where the centroids of the postcodes that cover them all fall outside their boundaries”
(GeoConvert, nd). Some of the issues arose due to re-development or planning reasons, as well as the termination of some postcodes. After a series of troubleshooting and fact finding, a look-up table created by the Ministry of Housing, Communities and Local Government assisted in solving the majority of these challenges. Unfortunately, seven of the gambling outlets could not be matched so these outlets were eventually removed from the final data (see tables 3.1 and 3.2 for the final list).