Assessing baseline demographics

In a 2013 study, the Greater London Authority (GLA) applied Simpson Diversity Index, normally used in biology, to determine the diversity of people living in the London Boroughs (GLA, 2013).

The process considered several indicators for diversity identified in Census data collected between 1991 and 2011, where the following formula – Simpson’s D – was applied:

(GLA, 2005, p. 5)

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In this instance, D is the SDI value, where S is the total number of ethnic

groups, with P(i) being the portion of S being made of the number of species ‘i’.

Essentially, the GLA have taken the original 10 ethnic minority bands appearing in the 1991 census and aggregated further categories appearing in subsequent 2001 and 2011 census surveys. The minimum value of the index is therefore 1 with a maximum value of 10 (GLA, 2013, pp. 2, 6).

The results of this exercise result in a ranking index for diversity in London’s boroughs, as summarised in Figure 38.

Figure 38. London Borough SDI Scores

In Figure 38, Kensington and Chelsea, the borough containing Portobello Road, is denoted with a green vertical line; Camden, the location for Camden High Street is blue; Tower Hamlets, the borough hosting Petticoat Lane, is shaded red. Each borough has a unique score indicating that the baseline

demographics marginally differ (see Table 11 overleaf). The black dashed line represents the Mean SDI scores taken from the 50 most diverse boroughs in the UK.

0 2 4

Newham Brent Redbridge Harrow WalthamForest Croydon Ealing Lewisham Hackney Southwark TowerHamlets Hounslow Lambeth BarkingandDagenham Haringey Hillingdon Enfiel Westminster Merton Barnet Greenwich Camden HammersmithandFulham Islington Wandsworth KensingtonandChelsea KingstonuponThames Sutton CityofLondon Bexley Bromley RichmonduponThames Havering

Borough Name

GLASDIScore

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Table 11. SDI Statistics for Kensington and Chelsea, Camden, and Tower Hamlets

Borough Name SDI Score Rank out of 33 (including

the City of London)

Across the 50 top diverse boroughs in the UK, 30 are in London. The average SDI score is 4.49; only Tower Hamlets is above this average, where interactions with customisation are more likely to represent broad responses. The distinction between these sites is made clearer when borough rankings are based on 2011 census data aggregated into the 10 ethnic groups noted in the 1991 census (Table 12).

Table 12: Selected borough rankings based on 2011 census data ward averages aggregated into the 10 ethnic groups of the 1991 census

For spatial contextualising, a map displaying the geographic locations of the case studies and their relative diversity scores, based on the GLA’s diversity exercises, can be viewed in Figure 39.

Based on previous discussions covered in Chapter 4, the hypothetical

assumption is that responses to customisation will be similar across the case study sites despite marked differences in their baseline demographics.

Responses are expected to be based on the quality of the composition of an environment including its perceptive complexity and ability to connect to the individuality of an urban spaces end-users.

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Figure 39. Case locations in a pan-London context. Boroughs are coloured according to GLA SDI scores (Data source: Greater London Authority, 2013)

N

185 5.4.2 Tourist Traffic

Another characteristic which can potentially distinguish responses to customisation is whether high proportions of users are tourists. If a notable section of street users are tourists, this indicates that static pedestrian activities are most likely to occur in connection with the presence of tourist attractions which may override the impact of customisation as an independent influencer.

There is not a survey that takes stock of the numbers of tourist along a high street setting, so calculated estimates will be used instead. There are two ways that this can be achieved:

1. Assessing the overall popularity of a location 2. Assessing the oyster card usage

The popularity of a location can be deduced from public social media statistics such as the number of Facebook, Twitter, or Google ratings. However, these measures are location based and miscommunicate the popularity or

unpopularity of a location. For example, it is difficult to be sure whether the 171K Facebook Likes for Camden Market, as of February 2018, refer to the actual Camden Market, or the high street between the market and Camden Town Station. Furthermore, it is difficult to discern whether the majority of likes are from non-UK based Facebook users. However, it’s worth noting that

Petticoat Lane only has 6.6K likes and no official page; Portobello Road has 50K likes, although these mainly seem to orientate around the antiques market.

A more reliable measure can be calculated using Rolling Origin and Destination Survey (RODS) data provided by TfL. This survey considers journey types and demographics of Oyster Card users, where the number of tourists arriving at London underground stations close to the case study areas can be used as a measure of how popular a site is with tourists.

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Figure 40. Net daily numbers of tourists exiting case study stations

Subtracting the number of tourist oyster- user tap-outs from touch-ins gives an estimated net of tourists exiting a station instead of interchanging within the station. It is not clear how many of these tourists will actually go on to visit the case study regions – they may exit the station to switch their mode of transport – however, it gives an indication as to the traffic that potentially passes through the case study area, thus indicating its popularity with tourists. From Figure 40, Camden Town is clearly the case study that is most likely to be frequented by tourists; this is followed by Petticoat Lane, and then by Portobello Road – a location more likely to accommodate local interests than the other two case studies. Although Ladbroke Grove station is also close to Portobello Road, RODS data returns do not record any tourist tap-ins/tap-outs from this station.