The Relationship betweenFast Food Outlets andLondon’s Ethnic Groups

Page 1

The Relationship between Fast Food Outlets and London’s Ethnic Groups



Contents

Introduction and Research Question

p 04

Research Methods

p 05 – 06

01 Investigation 01-01 Primary Research 01-02 Secondary Research 02 Visualisation 02-01 Primary Research and Experiments 02-02 Secondary Research

Development of the Outcome 01 02

p 07

Data Comparison Details of Typographies, Colours, Grids and Materials

Conclusion

p 08

Footnotes

p 09

Bibliography

p 10

Appendices

p 11 – 27


Introduction and Research Question

This project is based on the question: ‘How can we visualise the relationship between fast food outlets and London’s ethnic groups?’ While cycling, I often noticed different aspects of fast food outlets in each area in London. When I cycled from North to South, for instance, along Holloway Road, there were many chicken or kebab shops, I also noticed that the black community was strong there. Then, moving towards Farringdon, there were mainly creative offices, cafes and bars. In Holborn, I could see many tourists going to the British Museum, and there were several fast food franchises. Arriving at Elephant and Castle, there were again many kebab or chicken shops and a large proportion of African / Caribbeans. It is also widely known that London is a multiracial city. According to the 2001 census 1, the proportion of the non-white ethnic groups was 34.3% in Inner London while in England it was 9.1%. Through these experiences, the hypothesis occurred to me that there was the relationship between areas, fast food outlets and ethnic minorities. In the Research Methods section, processes of 01 Investigation and 02 Visualisation will be discussed. The Development of the Outcome section, it includes the context of studies on information design. Processes of 01 Data Comparison and 02 Details of Typographies, Colours, Grids and Materials will be discussed in this section. In Conclusion, the analysis summary through above processes will be discussed.

04


Research Methods

01 Investigation

01-01 Primary Research Firstly, I attempted to investigate some specific streets as primary research: Kingsland High Street, King’s Road, High Road, and Walworth Road (see appendices 1). While attempting to record outlets and people on each street, I observed that people on Walworth Road tended to be obese, and that there were more black people than on King’s Road. Also, on Walworth Road, there were 12 fast food outlets and on King’s Road there was only 1 (McDonald’s) 2. There appeared to be some relationship between body types, ethnicity and fast food outlets. However, the clear evidence of the relationship could not be firmly established. 01-02 Secondary Research I adopted statistical analysis for impartial observation. This involved researching the proportion of ethnic groups in each borough with the 2001 Census, and the number of fast food outlets with the Yellow Pages 2009 website 3, and received tourist expenditure estimate in London from the London Development Agency 4. The 2001 Census classified ethnic groups into White, Black Caribbean, Black African, Other Black, Indian, Pakistani, Bangladeshi, Chinese and Other Ethnic Groups (see appendices 2). Although this was the most acceptable way to calculate the current distribution of ethnic groups, some data was omitted. Firstly, the proportion of ethnic groups in 2009 has certainly changed since 2001. Secondly, the relationship between the particular area and people was not clearly proved 5 because Other Ethnic Groups, for instance, classified large amounts of groups from Middle East and South / East Asia into just one group. Therefore, the focus of comparison was transferred to inner London boroughs rather than on individual streets. The 5 boroughs mainly located in the West London have less than 60,000 people from ethnic minorities 6 . On the other hand, the 8 boroughs mainly located in the East London have more than 70,000 people of ethnic minorities 7.

In the Yellow Pages 2009 website, I adopted keywords ‘takeaway + fast food’ for classification. Then, I divided the outlets into 14 types 8. They were also divided into two groups: global franchises such as McDonald’s, KFC, Burger King, Subway and independent outlets 9. Finally, the quantity of outlets was drawn into the chart (see appendices 3), and it appeared that the six boroughs in the East London had more than 70,000 people of ethnic minorities, and also had more independent outlets than other boroughs. In terms of tourist expenditure, the borough of Westminster clearly received more than others (see appendices 4), it also it had many more global franchises than others boroughs. In addition, I attempted to compare other statistics such as the proportion of working ages received income support benefit and people diagnosed as obese in each borough (see appendices 5). However, I could not find a clear relation between these factors, ethnic groups and fast food outlets. Through this secondary research, the above mentioned relationship appeared in statistical form. However, it was still difficult to find a connection between each statistical analysis. Thus, I attempted to visualise the relationship in terms of information design.

05


02 Visualisation

02-01 Primary Research and Experiments For my primary research, I focused on the visualisation of data quantity. I attempted to make some collages, illustrations and pictograms. In my collage work, I used flyers, paper bags and boxes from fast food outlets to visualise the tone of these industries (see appendices 6). They tended to use red, yellow and blue colours. For the quantity of fast food outlets, I attempted to apply pictograms. I firstly drew illustrations of each outlet (see appendices 7). However, it looked too decorative. Then, I took photos of takeaway boxes, and traced their shape (see appendices 8). For ethnic groups, I also attempted a pictorial method. I firstly defined that 1 human pictogram indicated 5,000 people, then just copied and pasted them beside each other (see appendices 9). However, it looked chaotic. Then, I expressed the distinction with size differences (see appendices 10). However, it didn’t clearly work in visual impression. In terms of information design, clarification and simplification were significantly required. Further developments will be explained in the section of Development of the Outcome. 02-02 Secondary Research To determine the exact method for data visualisation, I referred to some books of information design 10. Firstly, information design offers communication between audiences and complex messages. According to Pedersen (1988), diagram ‘transcend language barriers, and they are memorable’ 11. For instance, the map designed by John Snow indicates the quantity of cholera deaths (see appendices 11). In this two dimensional spatial comparison can not visualise only the relationship between places and numbers of cholera deaths, but also the factor of cholera infection. Secondly, designers have to consider audiences to avoid misreading with distorted proportions and an overemphasis on unnecessary information. Tufte (1997) explained that ‘it is best to forget about designs involving such icons an symbols (…) data

06

require only a simple scatterplot or an ordered table to reveal’ the relationship 12. Then, I referred to the diagram designed by Tissi, R (see appendices 12). He adopted 3 dimensional blocks indicating a transition of exports from Germany to eight countries, also he divided the overall proportion into nine industries using colour distinctions. This diagram clearly represents the tendency in exportation, and estimation of future development in each industry.


Development of the Outcome

01 Data Comparison

02 Details of Typographies, Colours, Grids and Materials

I firstly attempted to make four different diagrams (see appendices 13). In these diagrams, I adopted simple bar charts with the exception of fast food outlets (I was still adhering to a cute icon of a takeaway box). To compare each other, it was printed on acetate sheets (see appendices 14). If these sheets were laid over each other, audiences could find similar flow between ethnic minorities and independent outlets. However, the proportion of white or other independent outlets still occupied a large space on the charts. After these experiments, I was deeply dedicated to a reduction. I determined to use only bars and colours for visualisation rather than takeaway box icons or human pictograms. I also removed unnecessary proportions 13. Then, all diagrams were summarised into one big poster. It also includes the map of Inner London, the table representing the detail of data and my analysis (see appendices 15).

Although simplification and function were significant for the layout, it still needed something peculiar to catch the eye. Therefore, I adopted a humorous font Chalet 14 which has unique shapes in t and f. Word spacing, type sizes, and contrasts on the different weight were intensely considered. I firstly adopted just gray scales to charts of ethnic groups to avoid a clash of hue with fast food outlets. However, it was difficult to connect gray scales and the type of ethnic group. So, I finally adopted the stripe consisting of gray scales and gray + cyan gradations. It affected easy connection, and still kept fewer colours. To clarify the information, I adopted 10 x 35 modular grids, and all types basically ranged left. Right alignment on the name of boroughs might be suitable to connect to next charts. However, the left alignment still looked stable in the real printing (see appendices 16). I also attempted to print on two sheets of textured paper 15. I finally decided the Extra White colour to emphasise the contrast between information and the background.

 07


Conclusion

Through the process of visualisation, my final outcome is finalised as one sheet of A1 poster (see appendices 17). This poster represents the relationship between fast food outlets and two other indices: London’s local ethnic groups and tourism. This also indicates that there is a clear correlation between the overall proportion of ethnic minorities and the number of independent fast food outlets. Those Boroughs having more ethnic minorities also have more independent fast food outlets. This distinction is clearly displayed on those two boroughs: Newham has the most ethnic minorities and independent outlets, and Kensington and Chelsea has the least ethnic minorities and independent outlets. The borough of Islington, for instance, has even fewer ethnic minorities, but has quite large amount of independent outlets. It is perhaps because this borough is well known as a popular area for dining. There is also a relationship between the proportion of global food franchises and tourism. These franchises are more common where tourist numbers are greater. Westminster is clearly the most popular place for tourists to spend money, there is a dense concentration of franchises such as McDonald’s, KFC, Burger King and Subway in that borough.

 08


Footnotes

1 SASPAC. (2001) 2001 Census. [Internet]. Available from: <http://www.saspac.org/StatPack09/ InstantAtlas/atlas.html> [Accessed 15 November 2009] (Also see appendices 2)

divided into Others. Also, if the outlets identified two types of name e.g. Tasty Chicken and Kebab, they were judged by the first section of the name. In this case, Tasty Chicken and Kebab was divided into Chicken.

2 These calculation were based on my investigation in Major Project Proposal. The investigation on King’s Road was conducted on 2nd June 2009, and on Walworth Road was conducted on 8th June 2009. The quantity of fast food outlets on Walworth Road was 1 McDonald’s, 1 KFC, 1 Subway, 2 GREGGS, and 9 Local outlets: Burger, Chicken, Kebab, Sandwich and Bakery.

10 My main references were: Tufte, E. (1997) Visual Explanations: images and quantities, evidence and narrative. Cheshire, Conn: Graphics Press. Klanten, R. (2008) Data Flow. Berlin: Gestalten. Pedersen, B.M. (1988) Graphis Diagram 1: the graphic visualization of quantitative information, procedures, and data. Zurich: Graphis Press Corp.

3 Yellow Pages. (2009) [Internet]. Available from: <http://www.yell.com/> [Accessed 15 November 2009] (Also see appendices 3) 4 Received tourist expenditure estimate by London Development Agency. (2007) Local Area Tourism Impact Model Methodology 2009. [Internet]. Available from: <http://www.lda.gov.uk/server/show/ConWebDoc.2577> [Accessed 15 November 2009] (Also see appendices 4)

11 Pedersen, B.M. (1988) Graphis Diagram 1: the graphic visualization of quantitative information, procedures, and data. Zurich: Graphis Press Corp. P.7 L. 3–4 12 Tufte, E. (1997) Visual Explanations: images and quantities, evidence and narrative. Cheshire, Conn: Graphics Press. P.49 L.22–25

5 For instance, what could not be proved was the relationship between people faced Middle Eastern and Kebab outlets on Kingsland High Street in my primary research.

13 Unnecessary proportions include White, Other independent outlets and People received income support benefit. There were no clear connections between them and other charts.

6 Ethnic Minorities signify except White. The 5 boroughs include the boroughs of Hammersmith and Fulham, Islington, Kensington and Chelsea, Wandsworth and Westminster.

14 According to House Industries (2009), ‘This collection of ten typefaces in three unique styles is the creative genius of acclaimed clothing designer René Albert Chalet. (…) Chalet appropriately echoes the attitude of its creator: function with flair. House Industries. (2009) Chalet. [Internet]. Available from: <http://www.houseind.com/fonts/chalet> [Accessed 15 November 2009]

7 The 8 boroughs include the boroughs of Camden, Hackney, Haringey, Lambeth, Lewisham, Newham, Southwark and Tower Hamlets. 8 The 14 types include Burger, Caribbean, Chicken, Chinese, Fish & Chips, Indian, Kebab, Pizza, Sandwich / Bakery, McDonald’s, KFC, Burger King, Subway and Others.

15 I chose two types of paper: Mohawk Superfine / 148 gsm / White Eggshell and Mohawk Superfine / 148 gsm / Extra White Eggshell from GF Smith. Available from: <http://www.gfsmith.com/> [Accessed 15 November 2009]

9 However, there were some vague outlets to divide into an exact type. For instance, the outlet named Natty Tatty Food Takeaway could not be judged by the name. So, these kinds of vague outlets were

09


Bibliography

Investigation

Visualisation

• SASPAC. (2001) 2001 Census. [Internet]. Available from: <http://www.saspac.org/StatPack09/ InstantAtlas/atlas.html> [Accessed 15 November 2009] • BBC News. (2005) British immigration map revealed. [Internet]. Available from: <http://news.bbc.co.uk/1/hi/ uk/4218740.stm> [Accessed 18 November 2009] • Hughes, S. (2009) Chicken: Low Art, High Calorie. New York: Mark Batty Publisher. • Schlosser, E. (2002) Fast food nation: what the allAmerican meal is doing to the world. London: Penguin. • London Development Agency. (2007) Local Area Tourism Impact Model Methodology 2009. [Internet]. Available from: <http://www.lda.gov.uk/server/show/ ConWebDoc.2577> [Accessed 15 November 2009] • Kerr, J. Gibson, A. (2003) London from Punk to Blair. London: Reaktion Books Ltd. • Maclnnes, T. Kenway, P. (2009) London’s Poverty Profile. London: New Policy Institute. [Internet]. p.8 – 14. Available from: <http://www.londonspovertyprofile.org. uk/CPF-povertyreport-largeprint.pdf> [Accessed 19 November 2009] • Litzer, G. (2000) The McDonaldization of Society. California: Pine Forge Press. • UK Poverty Indicators. (2008) Monitoring poverty and social exclusion 2008. [Internet]. p.68 Available from: <http://www.poverty.org.uk/> [Accessed 18 November 2009] • Well London. (2001) Safety of Food for Ethnic Minorities. [Internet] Available from: <http://www. london.gov.uk/welllondon/casestudies/safetyfoodethnic. jsp> [Accessed 18 November 2009] • BBC News. (2008) Takeaways near schools face ban. [Internet]. Available from: <http://news.bbc.co.uk/1/hi/ england/london/7683415.stm> [Accessed 18 November 2009] • Yellow Pages. (2009) [Internet]. Available from: <http://www.yell.com/> [Accessed 15 November 2009]

• House Industries. (2009) Chalet. [Internet]. Available from: <http://www.houseind.com/fonts/chalet> [Accessed 15 November 2009] • Klanten, R. (2008) Data Flow. Berlin: Gestalten. • Tufte, E. (1990) Envisioning information. Cheshire, Conn: Graphics Press. • Pedersen, B.M. (1988) Graphis Diagram 1: the graphic visualization of quantitative information, procedures, and data. Zurich: Graphis Press Corp. • Fawcett-Tang, R. (2008) Mapping Graphic Navigational Systems. East Sussex: RotoVision. • Tufte, E. (1997) Visual Explanations: images and quantities, evidence and narrative. Cheshire, Conn: Graphics Press. • Super Contemporary. (2009) London: Design Museum. 3 June – 4 October • Creative Review. Availavle from: <http://www. creativereview.co.uk/> [Accessed 19 November 2009] • Eye magazine. Available from: <http://www. eyemagazine.com/> [Accessed 19 November 2009] • Information Aesthetics. Available from: <http:// infosthetics.com/> [Accessed 19 November 2009] • Information is Beautiful. Available from: <http:// www.informationisbeautiful.net/> [Accessed 19 November 2009]

10


Appendices

1 Photos on individual streets in London. Kingsland High Street A in the borough of Hackney, King’s Road B in the borough of Kensington and Chelsea , High Road C in the borough of Barnet, and Walworth Road D in the borough of Southwark.

A

B

C

D

 11


2 The charts of ethnic groups. ‘White’ includes British, Irish and Other White. ‘Other Black’ includes mixed race such as White and Black Caribbean, White and Black African. ‘Other Ethnic Groups’ includes mixed races such as White and Asian, Other Mixed and Other Asian. The 2001 Census. Available from the SASPAC website. http://www.saspac.org/StatPack09/InstantAtlas/atlas. html

White

Black Carribean

Black African

Other Black

Indian

Pakistani

Bangladeshi

Chinese

Other groups

ENGLAND

44,679,361

561,246

475,938

327,943

1,028,546

706,539

275,394

220,681

787,880

LONDON

5,103,203

343,567

378,933

207,7 75

436,993

142,749

153,893

80,201

367,093

INNER LONDON

1,816,605

189,991

228,691

105,805

85,47 1

43,559

128,314

38,918

14 4,607

Camden

144,896

3,635

11,795

20,933

4,574

1,250

12,569

3,470

12,009

Hackney

120,468

20,879

24,290

7,931

7,624

2,165

5,970

2,37 7

9,537

Hammersmith and Fulham

128,602

8,534

8,072

5,398

2,733

1,7 11

1,011

1,303

8,4 4 4

Haringey

142,082

20,570

19,879

7,166

6,17 1

2,046

2,961

2,4 4 4

12,670

Islington

132,464

8,550

10,500

5,686

2,851

912

4,229

3,074

7,841

Kensington and Chelsea

124,924

4,101

6,013

3,498

3,226

1,203

1,148

2,592

12,398

Lambeth

166,058

32,139

30,836

11,958

5,316

2,634

2,169

3,362

10,595

Lewisham

164,098

30,543

22,57 1

12,065

3,487

1,090

1,229

3,431

10,968

Newham

96,130

17,931

31,982

7,325

29,597

20,64 4

21,458

2,349

16,417

Southwark

154,316

19,555

39,349

9,519

3,655

1,118

3,642

4,492

8,923

Tower Hamlets

100,799

5,225

6,596

4,443

3,001

1,486

65,553

3,573

6,595

Wandsworth

202,978

12,665

10,013

6,070

7,412

5,4 49

1,099

2,227

12,004

Westminster

132,7 15

5,613

6,678

3,824

5,665

1,828

5,000

4,07 7

15,934

12


3 The Chart of the number of fast food outlets. Available from the Yellow Pages 2009 website. http://www.yell.com/

McDonalds

KFC

Burger King

Subway

Total franchises

Burger

Caribbean Chicken

Chinese

Fish & Chips

Indian

Kebab

Pizza

Sandwich/ Bakery

Others

Total independent outlets

Total fast food outlets in each borough

Camden

6

5

1

11

23

4

2

8

8

10

7

1

3

7

34

84

107

Hackney

3

4

2

2

11

0

2

20

7

8

7

17

1

2

31

95

106

Hammarsmith and Fulham

3

3

1

1

8

1

2

5

2

9

4

4

0

0

15

42

50

Haringey

1

5

1

2

9

1

0

21

1

6

6

11

3

1

27

77

86

Islington

5

2

2

3

12

0

1

13

9

12

3

13

1

2

19

73

85

Kensington and Chelsea

5

3

1

4

13

0

0

2

0

6

1

2

0

2

11

24

37

Lambeth

4

5

2

2

13

0

0

22

7

16

10

11

0

2

43

111

124

Lewisham

3

3

1

0

7

0

2

13

11

16

10

16

0

0

61

129

136

Newham

6

4

2

0

12

0

0

35

10

21

4

7

2

0

33

112

124

Southwark

4

3

2

1

10

3

1

14

13

25

11

10

2

0

24

103

113

Tower Hamlets

6

3

2

1

12

0

0

31

7

13

9

8

0

0

30

98

110

Wandsworth

5

4

1

4

14

2

1

12

11

16

5

6

0

0

35

88

102

Westminster

19

8

9

16

52

2

2

7

0

8

0

1

2

7

39

68

120

 13


4 The chart of received tourist expenditure estimate 2007. Available from the London Development Agency website. http://www.lda.gov.uk/server/show/ConWebDoc.2577

Received tourist expenditure estimate (ÂŁ millions)

Camden

1,083

Hackney

118

Hammersmith and Fulham

494

Haringey

159

Islington

323

Kensington and Chelsea

1,461

Lambeth

429

Lewisham

120

Newham

201

Southwark

433

Tower Hamlets

454

Wandsworth

283

Westminster

4,7 76

 14


5 The chart of proportions: people received income support benefit (2007) and people diagnosed as obese (2009). Available from the SASPAC website. http://www.saspac.org/StatPack09/InstantAtlas/atlas. html

Working age (16 to 65) claiming Income Support (%) (2008)

Estimate for Obesity (%) (2009)

Camden

13.4

13.3

Hackney

22.0

17.5

Hammersmith and Fulham

14.0

15.4

Haringey

18.4

17.9

Islington

19.3

16.0

Kensington and Chelsea

9.6

13.1

Lambeth

16.7

18.6

Lewisham

16.6

19.2

Newham

20.0

21.2

Southwark

16.2

19.7

Tower Hamlets

19.7

11.9

Wandsworth

10.1

14.2

Westminster

11.4

14.7

 15


6

 16

Collages using images from fast food outlets.


7

Illustrations of each fast food.

McDonald’ McDonald’ss

Burger Burger

KFC KFC

Caribbean Caribbean

Burger BurgerKing King

Chicken Chicken

Subway Subway

Chinese Chinese

Fish Fish&&Chips Chips

Indian Indian

Kebab Kebab

Pizza Pizza

Sandwich Sandwich/ /Bakery Bakery

17


8

 18

Photos of takeaway boxes, and icons.


9

White Camden

Camden

Hackney

Hackney

Black White Carribean

Hammarsmith & Fulham

Hammarsmith & Fulham

Haringey

Haringey

Islington

Kensington & Chelsea

Lambeth

Black Black African Carribean

Other Black Black African

Indian Other Black

Pakistani Indian

Bangladishi Pakistani

Chinese Bangladishi Other Chinese Ethnics

Pictograms copied and pasted beside each other.

Other Ethnics

White

White Black Carribean

Lewisham

Lewisham

Newham

Newham

Southwark

Southwark

Tower Hamlets

Tower Hamlets

Wandsworth

Wandsworth

Westminster

Westminster

Black Black African Carribean

Other Black Black African

Indian Other Black

Pakistani Indian

Bangladishi Pakistani

Chinese Bangladishi Other Chinese Ethnics

Other Ethnics

Islington

Kensington & Chelsea

Lambeth

= 5,000 people

 19

= 5,000 people


10 Pictograms with size differences. For instance, I decided the exact size indicating 5,000 people. Then, if the ethnic group was 10,000, the pictogram would be expanded to 200%.

White Camden

Camden

Hackney

Hackney

HammarsmithHammarsmith & & Fulham Fulham

Haringey

White Black Carribean

Black Black Carribean African

Black Other African Black

Other Indian Black

IndianPakistani

Pakistani Bangladishi Bangladishi Chinese

Chinese Other EthnicsOther Ethnics

White Lewisham

Lewisham

Newham

Newham

Southwark

Southwark

White Black Carribean

Black Black Carribean African

Black Other African Black

Other Indian Black

IndianPakistani

Pakistani Bangladishi Bangladishi Chinese

Chinese Other EthnicsOther Ethnics

Haringey

Tower Hamlets Tower Hamlets

Islington

Islington Wandsworth Wandsworth

Kensington &Kensington & Chelsea Chelsea

Westminster Westminster

Lambeth

Lambeth

= 5,000 people = 5,000 people

 20


11 The Map designed by John Snow indicates the quantity of cholera deaths. Tufte, E. (1997) Visual Explanations: images and quantities, evidence and narrative. Cheshire, Conn: Graphics Press. P.30

 21


12 The map designed by Tissi, R indicates a transition of exports from Germany to eight countries. Pedersen, B.M. (1988) Graphis Diagram 1: the graphic visualization of quantitative information, procedures, and data. Zurich: Graphis Press Corp. P.70

 22


13 The diagrams of fast food outlets, ethnicity, received tourist expenditure and people received income support benefit.

Proportions: Inner London Boroughs

Others Burger

Black Carribbean

Caribbean

Black African

Chicken

Other Black

Chinese

Indian

Fish & Chips

Pakistani

Indian

Bangladishi

Kebab

Chinese

Pizza

Other Ethnic Group

Sandwich / Bakery

5,000 people

Local Fast Food Services

Camden

Hackney

Hammarsmith and Fulham

Haringey

Islington

Kensington and Chelsea

Lambeth

Lewisham

Newham

Southwark

Tower Hamlets

Wandsworth

Westminster

Camden

Hackney

Hammarsmith and Fulham

Haringey

Islington

Kensington and Chelsea

Lambeth

Lewisham

Newham

Southwark

Tower Hamlets

Wandsworth

Westminster

Main Franchise Services

5,000 people

McDonald’s

White

KFC Burger King Subway

Fast Food Industry

Ethnic Groups

5,000 people

Camden

Hackney

Hammarsmith and Fulham

Haringey

Islington

Kensington and Chelsea

Lambeth

Lewisham

Newham

Southwark

Tower Hamlets

Wandsworth

Westminster

Camden

Hackney

Hammarsmith and Fulham

Haringey

Islington

Kensington and Chelsea

Lambeth

Lewisham

Newham

Southwark

Tower Hamlets

Wandsworth

Westminster

£100,000,000

Working Ages Claiming Income Support

Received Tourism Expenditure (Estimate)

23


14 Diagrams on acetate sheets.

 24


15 The prototype of the outcome.

 25


16 The development of the outcome. Full consideration to gray scales A , modular grids B, left or right alignment C and typefaces D.

A-1

A-2

B

D-1

 26

A-3

C

D-2

D-3


A-2

D-2

16 The development of the outcome. Full consideration to gray scales A , modular grids B, left or right alignment C and typefaces D.

A-1

B

D-1

26

C A-3

D-3

Camden

1 2 3 4

Hackney

1 2 3 4

Hammersmith and Fulham

1 2 3 4

Haringey

1 2 3 4

Islington

1 2 3 4

Kensington and Chelsea

1 2 3 4

Lambeth

1 2 3 4

Lewisham

1 2 3 4

Newham

1 2 3 4

Southwark

1 2 3 4

Tower Hamlets

1 2 3 4

Wandsworth

1 2 3 4

Westminster

1 2 3 4

Each vertical line indicates a total of 5 outlets, 10,000 people and £ 500 million.

The Relationship between Fast Food Outlets and London’s Ethnic Groups Inner London Boroughs

1 Independent fast food outlets

Haringey

Camden

Islington

Westminster

City

Hackney

Tower Hamlets

Newham

Kensington* Hammersmith*

2 Ethnic minorities

3 Global fast food franchises

4 Received tourism expenditure (estimate)

2

2 ( people ) 8

8

10

7

1

3

7

3,635

11,795

3 ( shops ) 20,933 4,5 74

4 ( £ million )

1,250

12,569 3,470

12,009 6

5

1

11

1,083 118

Hackney

0

2

20

7

8

7

17

1

2

20,879 24,290 7,93 1

7,624

2,165

5,970

2,37 7

9,5 37

3

4

2

2

1

2

5

2

9

4

4

0

0

8 ,5 3 4

5,398

2,7 33

1,7 11

1,0 11

1,303

8,4 4 4

3

3

1

1

49 4

KFC

Haringey

1

0

21

1

6

6

11

3

1

20,5 70 19,879 7,166

6,17 1

2,046

2,961

2,4 4 4

12,670 1

5

1

2

159

Other Black

Burger King

Islington

0

1

13

9

12

3

13

1

2

8,550

10,500 5,686

2,851

9 12

4,229

3,074

7,8 41

5

2

2

3

323

Indian

Subway

Kensington*

0

0

2

0

6

1

2

0

2

4,10 1

6,013

3,498

3,226

1,203

1,14 8

2,592

12,398 5

3

1

4

1,461

Pakistani

Lambeth

0

0

22

7

16

10

11

0

2

32,139 30,836 11,958

5,316

2,63 4

2,169

3,362

10,595 4

5

2

2

4 29

Bangladeshi

Lewisham

0

2

13

11

16

10

16

0

0

30,5 4 3 2 2,57 1 12,065 3,487

1,090

1,2 29

3, 4 3 1

10,968 3

3

1

0

120

Kebab

Chinese

Newham

0

0

35

10

21

4

7

2

0

17,93 1

16,417

4

2

0

20 1

Pizza

Other Ethnic Groups

Black Carribean

McDonald’s

Caribbean

Black African

Chicken Chinese Fish & Chips Indian

Tourism

Southwark

Wandsworth

4

Hammersmith*

Burger

Sandwich / Bakery

Lambeth

1 ( shops ) Camden

8,072

3 1,982 7,325

29,597 20,64 4 2 1,458 2,3 49

6

Southwark

3

1

14

13

25

11

10

2

0

19,5 5 5 39,349 9,519

3,65 5

1,118

3,64 2

4,492

8,923

4

3

2

1

4 33

Tower Hamlets

0

0

31

7

13

9

8

0

0

5,225

4,4 4 3

3,001

1,486

65,553 3,5 7 3

6,595

6

3

2

1

454

6,596

Wandsworth

2

1

12

11

16

5

6

0

0

12,665 10,0 13

6,070

7,412

5,4 49

1,099

2,227

12,004 5

4

1

4

283

Westminster

2

2

7

0

8

0

1

2

7

5,613

3,824

5,665

1,828

5,000

4,07 7

15,934 19

8

9

16

4,7 76

6,678

Lewisham

Hammersmith* = Hammersmith and Fulham Kensington* = Kensington and Chelsea

1 Independent fast food outlets

3 Global fast food franchises

What does this poster represent?

Data drawn from the Yellow Pages 2009 website. Keywords used were: ‘takeaway + fast food + type of outlet e.g. Burger, Caribbean, Chicken’.

Data drawn from the Yellow Pages 2009 website. The keyword used was: ‘the name of the outlet e.g. McDonald’s, KFC, Burger King, Subway’.

2 Ethnic minorities

4 Received tourism expenditure

This poster represents the relationship between fast food outlets ( independent outlets and global franchises) and two other indices: London’s local ethnic groups and tourism.

Ethnic categories were those used in the 2001 Census. ‘Other Black’ includes mixed races such as White and Black Caribbean, White and Black African. ‘Other Ethnic Groups’ includes mixed races such as White and Asian, Other Mixed, Other Asian.

Data drawn from the 2007 Tourism Expenditure Estimate. Available from the London Development Agency website.

Looking at inner London boroughs, there is a clear correlation between the number of independent fast food outlets (Graph 1) and the overall proportion of ethnic minorities (Graph 2). Those Boroughs having more ethnic minorities also have more independent fast food outlets. There is also a relationship between the proportion of

global fast food franchises (Graph 3) and tourism (Graph 4). These franchises are more common where tourist numbers are greater. Westminster is clearly the most popular place for tourists to spend money, there is a dense concentration of franchises such as McDonald’s, KFC, Burger King and Subway. Hammersmith* = Hammersmith and Fulham Kensington* = Kensington and Chelsea


17 The final version of the outcome.



Takuya Furukawa Graduate Diploma in Design for Visual Communication 2009 London College of Communication taqyafurukawa@gmail.com


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