Q64. We'll use data on early 20th century Scottish industries to investigate interlocking directorates.
(From Pajek data online) This dataset contains the corporate interlocks in Scotland in the beginning of the twentieth century (1904-5). In the nineteenth century, the industrial revolution brought Scotland railways and industrialization, especially heavy industry and textile industry. The amount of capital needed for these large scale undertakings exceeded the means of private families, so joint stock companies were established, which could raise the required capital. Joint stock companies are owned by the shareholders, who are represented by a board of directors. This opens up the possibility of interlocking directorates. By the end of the nineteenth century, joint stock companies had become the predominant form of business enterprise at the expense of private family businesses. Families, however, still exercised control through ownership and directorships.
The data are taken from the book The Anatomy of Scottish Capital by John Scott and Michael Hughes. It lists the (136) multiple directors of the 108 largest joint stock companies in Scotland in 1904-5: 64 non-financial firms, 8 banks, 14 insurance companies, and 22 investment and property companies (Scotland.net). In this dataset, which was compiled from the Appendix of Scott & Hughes' book, note that two multiple directors (W.S. Fraser and C.D. Menzies) are affiliated with just one board so they are not multiple directors in the strict sense.
The companies are classified according to industry type: 1 - oil & mining, 2 - railway, 3 - engineering & steel, 4 - electricity & chemicals, 5 - domestic products, 6 - banks, 7 - insurance, and 8 - investment. In addition, there is a vector specifying the total capital or deposits of the firms in 1,000 pound sterling.
John Scott & Michael Hughes, The anatomy of Scottish capital: Scottish companies and Scottish capital, 1900-1979 (London: Croom Helm, 1980).
W. de Nooy, A. Mrvar, & V. Batagelj, Exploratory Social Network Analysis with Pajek (Cambridge: Cambridge University Press, 2004), Chapter 5.
Original authors: are John Paul Scott (1949) (ku.ca.xesse|jttocs#ku.ca.xesse|jttocs, University of Essex) & Michael Hughes (1947, University of Lancaster in 1980, not listed now).
Data compiled into Pajek data files by W. de Nooy, 2001
Use NodeXL to visualize this data. The data is in three network datasets: a bipartite network of people and companies (edges represent a person being a director of a company); a network of people (the edges are co-membership in companies); and a network of companies (edges are sharing a director).
Task 1: Create a preliminary two mode visualization that shows people as small circles and companies as larger squares. Try different layouts (including manually assisted) and produce the best visualization you can (in a reasonable amount of time). Can you color the companies by industry? Are there individuals who appear to be bridges between industries? Or who appear to be kingpins in a particular industry?
Task 2: Do a quick exploration of the people by people network. Try different visualizations. Calculate graph metrics. It might clarify the visualization if you use dynamic filtering to discard barely connected individuals. Change node size by graph metric. Can you identify a class of apparently important people? Try clustering.
Task 3: Now look at company by company network. Cluster, color, explore. How much do network clusters follow industry? Are there cluster bridging companies? Are you surprised at what they are.
Turn in short paper that shows your explorations.
The data is in the following Excel files.
|File name||File type||Size|
|Scotland-NodeXL-2mode.xlsx||Zip archive data||133.74 kB||Info|
|Scotland-NodeXL-orgs.xlsx||Zip archive data||130.88 kB||Info|
|Scotland-NodeXL-people.xlsx||Zip archive data||135.84 kB||Info|
|scotland.xlsx||Zip archive data||240.31 kB||Info|