The Bow-Tie Model of Ownership Networks
Perhaps the most surprising feature discovered in the empirical network analysis of Chap. 4 is the emergence of a tiny, powerful, tightly-knit and self-controlled group of corporations, see Sect. 4.3.5
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The Bow-Tie Model of Ownership Networks
Indeed, even some of the very simplest programs that I looked at had behavior that was as complex as anything I had ever seen. It took me more than a decade to come to terms with this result, and to realize just how fundamental and far-reaching its consequences are.
(S. Wolfram in Wolfram 2002, p. 2) Perhaps the most surprising feature discovered in the empirical network analysis of Chap. 4 is the emergence of a tiny, powerful, tightly-knit and self-controlled group of corporations, see Sect. 4.3.5. This core can be identified as the strongly connected component (SCC1 ) of an emerging bow-tie structure2 in the global network of TNCs, located in the largest connected component (LCC) of the network, see Sect. 4.2.4. Collectively this core holds close to 40 % of the total control in the network, despite being comprise of only 1347 corporations. Recall that the network size is 600508. The relevance of this structure is discussed in Sect. 6.1.6 and its implications in Sect. 6.2. The emergence of a bow-tie topology in the global ownership network, has, to our knowledge, never been observed before. Recall also that in the crosscountry analysis of Chap. 3 we also uncovered bow-tie structures in various national networks, see Sect. 3.3.1. It is known that technological networks, such as the World-Wide Web (WWW) (Broder et al. 2000) and Wikipedia3 (Capocci et al. 2006), also exhibit bow-tie topologies. In contrast to the ownership networks, their SCCs are large, comprising more than half of all the nodes. What are the organizational principles and the driving forces behind this kind of network organization? In order to understand the mechanisms underlying the formation of different bow-tie structures, we develop a generic Modeling Framework in Sect. 5.2. It is governed by node and link addition, where the network evolution 1 2 3
A list of acronyms can be found in front matter of this book. Recall Figs. 1.2 and 3.1. The Internet encyclopedia, http://wikipedia.org.
J. B. Glattfelder, Decoding Complexity, Springer Theses, DOI: 10.1007/978-3-642-33424-5_5, © Springer-Verlag Berlin Heidelberg 2013
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5 The Bow-Tie Model of Ownership Networks
is determined by a preferential-attachment mechanism defined by a distribution of fitness values amongst the nodes. This fitness measure can either be determined by the network topology (e.g., degree, centrality, network control, etc.) or can be a non-topological state variable (e.g., operating revenue). The network formation is determined by the co-evolution of fitness and topology: at each time step, the distribution of fitness determines the topology of the network, which in turn impacts the distribution of fitness in the next step. Using the Modeling Framework we can address the question of what the simplest mechanisms are that result in the emergence of bow-tie structures. In other words, what interactions are necessary at the micro-level in order to reproduce the observed macro-patterns. In detail, in Sect. 5.3, we present a specific
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