This document summarizes a study that used social network analysis to analyze the network of companies and individuals in London's advertising industry. The study found the industry to be relatively well-connected, with some individuals identified as key connectors between clusters who help spread knowledge. It also found that company size did not necessarily determine how central and important a company was to the network. Geographic proximity seemed to have more influence on network centrality than company size. The study demonstrated social network analysis can be a useful tool for economic geographers to examine industry networks.

1. Negotiated Studies Presentation
on
PREM SANKAR C
M.Tech [T.M]

2. Oli Mould & Sian Joel
* Dept of Geography ,Loughborough University;
** Dept of Computing and creative industries ,Napier
University
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Publisher : Royal Geographical Society
Theme :Knowledge Network in Industry
Topics :Clustering & networking
Sector :Advertising
Key words: Economic Geography, London, Buzz,
Advertising Industry, Social Network Analysis

3. 
Introduction
◦ ‘Buzz’
◦ Social Network Analysis
Data Source
 Methodology
 Key Findings
 Conclusion
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4. 
To highlight how SNA can provide a flow of ‘buzz', on
London's advertising industry.
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This study states that the SNA can be used as a viable
research tool for highlighting networks within a
particular industry and location

6. 
Recent Economic Geography literature concerned with :
‘Firm as complex network of actors ‘(Jones 2007)
‘Tacit knowledge transfer ‘(Gertler and Levitte, 2005) –on
innovation in the Canadian Biotechnology Industry.
 ‘Local Noise in London adv Industry’ (Grabher, 2002)
‘ Communities of knowledge’ (Storper and Venables, 2004)
Importance of Social ,Intra and inter-firm networks in
Advertising/Creative industries (Caves 2000,Cunnningham
2004)
Serendipitous nature of buzz Grabher(2002)

7. “ Buzz refers to the information and communication
knowledge created by face-to-face contacts, co-presence
and co-location of people and firms within the same
industry and place or region”.
(Bathelt et al., 2004: 38)
 Buzz consists of specific information and continuous updates
of this information through organised and accidental meeting
 Buzz is based on network of communication and information
linkage within a industry
 This occurs in negotiations with suppliers ,in phone calls
during office hours ,while talking to neighbors or when having
lunch with other employees and so on

8. 
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Is a network structure that is highly clustered with small path
lengths
Introduced by Milgram(1967) – concluded that “six degree of
separation” in friendship network - Avg 6 intermediaries
between 2 strangers
Same in Scientific Co-authoring Davis and Newman (2003)
Small world network are represented graphically using SNA
tools

9. 
Attempts have been made to quantify/qualify ‘buzz’
◦ Gertler and Levitte (2005) focused on local networks in the
Canadian biotech industry ,suggested that local knowledge
and global circulation for success in innovation.
◦ Watson (2008) described the local buzz/global pipeline
dualism for knowledge exchange in London’s music
industry …

10. 
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Social Network Analysis offers a way to visualize
networks and highlight important characteristics of
those networks .
SNA is under utilized in economic geography
literature.
Connection between firms and particular individuals
shows the path of knowledge flow within the
industry and can highlight the key gate keepers
(individuals sit on many of company board of
directors).

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Historically Alfred Marshall (1920),suggested strong centre of
specialized industry attracts new energy and maintain its
lead(for heavy manufacturing industry of that time but still it
hold true for knowledge economy of today )
Inter-locking board members data can be used as it shows the
connectivity levels within any given industry or locale
(O’Hagan and Green, 2003)
Knowledge shared informally between people and firms
increases with technological connectivity(Jones 2007)

12. 
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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’
How buzz is geographically spread through intra-inter firm
networks -Glucker (2006)
This study use data on on interlocking board members of
advertising companies in London ,and visualize their networks
using sociograms. And highlights the intensity of connections
between companies and particular individuals, showing the
paths of knowledge flow within the industry and the
‘gatekeepers'.

14. 
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The data for the SNA were obtained from the UK Companies
House database.
Data was filtered to remove those companies with less than 4
people on the board
Empty and not valid data also removed
Network maps were visualised as sociograms
Software packages used -UCINET and Netdraw.
Spearman's Rank Correlation Coefficient (SRCC) was used.

15. 
UCINET— is produced by Analytic Technologies. It offers a
very user-friendly, reasonably priced software system for
network analysis
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NetDraw -, a Windows program for visualizing social network
data. The program is free.
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Spearman's rank correlation coefficient or Spearman's rho,
named after Charles Spearman and is measure of statistical
dependence between two variables. It assesses how well the
relationship between two variables can be described using a
function

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Rectangular matrix –shows 2 mode network of
Company to director
Adjacency matrix –shows one mode network of
company to company and director to director
Rank of company by net asset is calculated –
highlights it is not always largest companies are most
connected or most central
Based on the holding of shares ,Company family tree
also obtained
SNA tools are used to find density and centralization
(Degree and Eigen vector)

17. 
Networks that are produced have certain characteristics:
◦ People-centric
◦ Top-heavy
◦ People-centric: Selects people on many boards rather
than boards of directors that have many people. This
was done as the advertising industry (creative
industries) tend to be ‘fluid’ (in other words, high
degree of freelancing, sub-contracting etc) so the
individual is important
◦ Top-heavy: Selects those people who sit on the board
of larger companies (i.e. with more board members)

19. DIRECTOR AND COMPANY NETWORK
PEOPLE
COMPANY
A Well Connected
Industry
Knowledge can
transfer quickly

20. 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

21. PEOPLE
COMPANY

22. KEY CUT POINTS
PEOPLE
COMPANY
Identified ‘cut-points’ or
gate keepers Or Trend
Setters
For knowledge transfer

23. STRATEGIC CUT POINTS
 Companies have their headquarters in same physical
location
 Those board of directors are friends or have worked
together in the past
 Companies may belong to the same holding company
(hypothesis tested by subsidiary company data) then
people who sit on the board of a holding company also sit
on the board of their subsidiaries (company family)
 Cut points can transmit (restrict) knowledge between
company family trees

24. DENSITY
PEOPLE
COMPANY
Some people sit on
similar companies

25. PEOPLE AND COMPANIES
PEOPLE
COMPANY
Does show which
are the people who
sit on the largest
companies

26. COMPANY SIZE BY NET ASSET
PEOPLE
COMPANY
Company size –size
does not equate to
connectivity
importance

27. PERFORMANCE INDICTORS
 Based of net asset variable company was ranked and
compared with centrality rank for that company to check
correlation between ranks
 Shown in scatter diagram
 Findings: Being a certain size company has no guarantee
on that company being centralized
 Firm size is not an indictor of network importance

29. 
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People's importance (the intensity of an individual in
the network), shown by degree centrality measures
and the eigenvector index.
Degree centrality is a simple measure that counts the
number of ties a person has.
Eigenvector index is a mathematical measurement of
the ‘connectedness' of any particular node in a social
network

30. 
Top 10 most connected people in the social network (degree centrality)
Person
A
28
B
27
AL
12
AM
11
AE
11
AG
10
C
6
I
6
AV
5
AU
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Number of company boards
5
Top 10 most connected people in the social network (degree centrality)
Person
Number of company boards
A
28
B
27
AN
16
Q
12
AG
11
R
11
P
8
L
7
AW
5
BJ
5

31. 
Based on the postal address
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5 of the most ‘connected’ companies are located at one address, 121-141
Westbourne Terrace, London, London, W2 6JR
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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
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These 5 companies are not direct subsidiaries of Fitch or WPP, so the
connection between these companies goes beyond a simple ‘company
family ties’ (Incubator)
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May therefore share board members more readily and act as pipelines from
global into local buzz for exchange of tacit knowledge

32. 
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Sociograms showed that that the advertising sector is relatively well
connected.
Highlighted the key individuals /gate keepers who connect between
clusters for spreading knowledge between them
Comparing members according to their net assets, not particularly large
companies are hugely important in providing connection and cohesion to
the network.
finding suggests that being in a certain size company has no bearing on
that company being centralised within London's advertising network.
Small, medium or large companies can play an important part in
connecting companies and groups.
The study showed that there is strong geographical effect on the
networked-centrality of London's advertising companies - more so than
size.

33. 
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The advertising industry is relatively connected via
board of directors .
Advertising is dynamic and is dependent on trends and
so the exchange of knowledge is crucial to economic
viability.
SNA as research tool for Economical geographers
Highlighted well connected and important people in
London advertising Industry