A major part of the research process is looking at the literature that is already out there so that one can find where they can fit in the academic discussion. One source that I found seems to be a hidden gem of research for my topic, and I will be providing a summary of their work.

To start off, the research question at hand looks at how different metro networks can be classified by certain characteristics, which are identified as state, form, and structure. [1] The authors claim that graph theory can be used to assign certain values to these characteristics, interpret the results, and group the metro networks. [2] From the claim that graph theory can be used; the definitions provided for state, form, and structure; the various mathematical equations; and the number of cases used in this article; it is fairly clear that the authors are employing a Large–n, Standard Causal Analysis methodology. [3] Many types of data are used, but some of the simpler forms of data are formulated into six basic data categories: complexity, degree of connectivity, average line length, average station spacing, structural connectivity, and directness. [4] This data is then put in the aforementioned graphs to find similarities between the cases examined, resulting in the conclusion that, “graph theory seems to grant the tools to effectively study metro networks”. [5]

1. Derrible, Sybil, and Christopher Kennedy. “Characterizing metro networks: state, form, and structure,” Transportation 37, no. 2 (March 2010), 276.
2. Ibid.
3. Ibid., 282-293.
4. Ibid., 287-289.
5. Ibid., 296.

Bibliography:

Derrible, Sybil, and Christopher Kennedy. “Characterizing metro networks: state, form, and structure,” Transportation 37, no. 2 (March 2010), 275-297.