Knowledge networks in
London’s Advertising
Industry: A Social Network
Analysis approach
Sian Joel & Oli Mould
OUTLINE
• Rationale
• ‘Buzz’
• Social Network
Analysis
• Methodology
• People and
Companies
• Size
• Location
• Conclusion
RATIONALE
• Recent Economic Geography literature
concerned with:
•Tacit knowledge transfer (Gertler and Levitte,
2005)
•‘P...
RATIONALE
• Grabher (2002) looked at London’s advertising
industry from a project-based perspective:
“Rather than equating...
RATIONALE
• Social Network Analysis offers a way to visualise
networks and highlight important characteristics
of those ne...
METHODOLOGY
• Company data downloaded from a companies
house population and then cleaned
• SIC code(s) and address were us...
PEOPLE AND
COMPANIES
People
Compa
ny
PEOPLE AND
COMPANIES
People
Compa
ny
A well-
connected
industry
PEOPLE AND
COMPANIES
People
Compa
ny
A well-
connected
industry
PEOPLE AND
COMPANIES
People
Compa
ny
Some people
sit on similar
companies
PEOPLE AND
COMPANIES
People
Compa
ny
Some people
sit on similar
companies
PEOPLE AND
COMPANIES
People
Compa
ny
Identify the
‘cut-points’ or
‘gatekeepers’
PEOPLE AND
COMPANIES
People
Compa
ny
Identify the
‘cut-points’ or
‘gatekeepers’
PEOPLE AND
COMPANIES
People
Compa
ny
Company by
size – size does
not equate to
connectivity
importance
PEOPLE AND
COMPANIES
People
Compa
ny
Company by
size – size does
not equate to
connectivity
importance
PEOPLE AND
COMPANIES
People
Compa
ny
Does show
which are the
people who sit
on the largest
companies
PEOPLE AND
COMPANIES
People
Compa
ny
Does show
which are the
people who sit
on the largest
companies
THE NETWORK
• In this network;
• 64 people sit on 286 company boards of directors
• From all the possible company connecti...
CLUSTERING
CLUSTERING
CLUSTERING
• 5 of the most ‘connected’ companies are located
at one address, 121-141 Westbourne Terrace,
London, London, W...
UNPACKING ‘BUZZ’?
• In this small example, using existing information,
we have been able to identify 5 out of the 10 most
...
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SNA in London's Advertising Industry

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SNA in London's Advertising Industry

  1. 1. Knowledge networks in London’s Advertising Industry: A Social Network Analysis approach Sian Joel & Oli Mould
  2. 2. OUTLINE • Rationale • ‘Buzz’ • Social Network Analysis • Methodology • People and Companies • Size • Location • Conclusion
  3. 3. RATIONALE • Recent Economic Geography literature concerned with: •Tacit knowledge transfer (Gertler and Levitte, 2005) •‘Project ecologies’ (Grabher, 2004) •‘Noise’ (Grabher, 2002) •‘Communities of knowledge’ and F2F (Storper and Venables, 2004) •‘Buzz’ (Bathelt et al., 2004) •Echoes of Marshall’s (1920) ‘industrial atmosphere’ “Buzz refers to the information and communication ecology created by face-to-face contacts, co-presence and co-location of people and firms within the same industry and place or region”.
  4. 4. RATIONALE • Grabher (2002) looked at London’s advertising industry from a project-based perspective: “Rather than equating the agglomeration of creative projects in Soho simply with reduced costs of transaction, it provides a vibrant site for ‘hanging out’, training and thus, gaining access to networks at the peripheries of projects… Through processes of negotiating meaning, these networks act as local interpretive communities which filter noise into signals”. (Grabher, 2002: 258) • Grabher noted that a key skill of (the most successful) advertisers is converting the ‘noise’ into ‘signals’, or what can be roughly translated as ‘tacit’ into ‘codified’ •Could additional methodologies be utilised in tandem to develop the measurement or
  5. 5. RATIONALE • Social Network Analysis offers a way to visualise networks and highlight important characteristics of those networks • Emanates from IT studies, but the ease of use of software application (through open-sourcing and Web 2.0 techniques) has increased • Inter-locking board data can be used as it shows the connectivity levels within any given industry or locale (O’Hagan and Green, 2003), and also is an increasingly popular trait in modern capitalist tendencies (Kono et al., 1998).
  6. 6. METHODOLOGY • Company data downloaded from a companies house population and then cleaned • SIC code(s) and address were used to identify relevant companies and then each entry was tested for relevance • Resulting data was filtered to remove those companies with less than 4 people on the board – which means the networks that are produced have certain characteristics: • People-centric: Selects people on many boards rather than boards of directors that have many people. This was done as the advertising industry (and wider creative industries) tend to be ‘fluid’ (in other words, high degree of freelancing, sub- contracting etc) so the individual is important
  7. 7. PEOPLE AND COMPANIES People Compa ny
  8. 8. PEOPLE AND COMPANIES People Compa ny A well- connected industry
  9. 9. PEOPLE AND COMPANIES People Compa ny A well- connected industry
  10. 10. PEOPLE AND COMPANIES People Compa ny Some people sit on similar companies
  11. 11. PEOPLE AND COMPANIES People Compa ny Some people sit on similar companies
  12. 12. PEOPLE AND COMPANIES People Compa ny Identify the ‘cut-points’ or ‘gatekeepers’
  13. 13. PEOPLE AND COMPANIES People Compa ny Identify the ‘cut-points’ or ‘gatekeepers’
  14. 14. PEOPLE AND COMPANIES People Compa ny Company by size – size does not equate to connectivity importance
  15. 15. PEOPLE AND COMPANIES People Compa ny Company by size – size does not equate to connectivity importance
  16. 16. PEOPLE AND COMPANIES People Compa ny Does show which are the people who sit on the largest companies
  17. 17. PEOPLE AND COMPANIES People Compa ny Does show which are the people who sit on the largest companies
  18. 18. THE NETWORK • In this network; • 64 people sit on 286 company boards of directors • From all the possible company connections, there exists 5.32% of ties • From the possible individual connections there is 1.15% of ties • Therefore connections could be considered strategic – quality not quantity • We can rank the companies by ‘degree centrality’ and map them to see clusters…
  19. 19. CLUSTERING
  20. 20. CLUSTERING
  21. 21. CLUSTERING • 5 of the most ‘connected’ companies are located at one address, 121-141 Westbourne Terrace, London, London, W2 6JR • Those 5 companies are not large, but reside in the same building as Fitch, who are owned by the WPP Group, one of the largest advertisers in the world • These 5 companies are not direct subsidiaries of Fitch or WPP, so the connection between these companies goes beyond a simple ‘company family ties’ • Often spinout companies form from larger ones, but will still be housed in the original space to
  22. 22. UNPACKING ‘BUZZ’? • In this small example, using existing information, we have been able to identify 5 out of the 10 most connected companies to one building • Further research could corroborate this evidence • Then, qualitative information could be targeted to gather more specific data as to these connections • Inter-board connectivity is only one form of connectivity that can be measured this way • SNA allows a ‘calibration’ (i.e. a range-finder) of the network for more targeted, descriptive data that can elaborate on the collaborative practices

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