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SNA in London's Advertising Industry
SNA in London's Advertising Industry
SNA in London's Advertising Industry
SNA in London's Advertising Industry
SNA in London's Advertising Industry
SNA in London's Advertising Industry
SNA in London's Advertising Industry
SNA in London's Advertising Industry
SNA in London's Advertising Industry
SNA in London's Advertising Industry
SNA in London's Advertising Industry
SNA in London's Advertising Industry
SNA in London's Advertising Industry
SNA in London's Advertising Industry
SNA in London's Advertising Industry
SNA in London's Advertising Industry
SNA in London's Advertising Industry
SNA in London's Advertising Industry
SNA in London's Advertising Industry
SNA in London's Advertising Industry
SNA in London's Advertising Industry
SNA in London's Advertising Industry
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SNA in London's Advertising Industry

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  • 1. Knowledge networks in London’s Advertising Industry: A Social Network Analysis approach Sian Joel & Oli Mould
  • 2. OUTLINE • Rationale • ‘Buzz’ • Social Network Analysis • Methodology • People and Companies • Size • Location • Conclusion
  • 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. 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. 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. 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. PEOPLE AND COMPANIES People Compa ny
  • 8. PEOPLE AND COMPANIES People Compa ny A well- connected industry
  • 9. PEOPLE AND COMPANIES People Compa ny A well- connected industry
  • 10. PEOPLE AND COMPANIES People Compa ny Some people sit on similar companies
  • 11. PEOPLE AND COMPANIES People Compa ny Some people sit on similar companies
  • 12. PEOPLE AND COMPANIES People Compa ny Identify the ‘cut-points’ or ‘gatekeepers’
  • 13. PEOPLE AND COMPANIES People Compa ny Identify the ‘cut-points’ or ‘gatekeepers’
  • 14. PEOPLE AND COMPANIES People Compa ny Company by size – size does not equate to connectivity importance
  • 15. PEOPLE AND COMPANIES People Compa ny Company by size – size does not equate to connectivity importance
  • 16. PEOPLE AND COMPANIES People Compa ny Does show which are the people who sit on the largest companies
  • 17. PEOPLE AND COMPANIES People Compa ny Does show which are the people who sit on the largest companies
  • 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. CLUSTERING
  • 20. CLUSTERING
  • 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. 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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