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In this chapter we investigate the ownership and control of UK firms using contemporary methods from computational graph theory. Specifically, we analyze a ‘small-world’ model of ownership and control. A small-world is a network whose actors are linked by a short chain of acquaintances (short path lengths), but at the same time have a strongly overlapping circle of friends (high clustering). We simulate a set of corporate worlds using an ensemble of random graphs introduced by Chung and Lu (2002a, 2002b). We find that the corporate governance network structures analyzed here are more clustered (‘clubby’) than would be predicted by the random-graph model. Path lengths, though, are generally not shorter than expected. In addition, we investigate the role of financial institutions: potentially important conduits creating connectivity in corporate networks. We find such institutions give rise to systematically different network topologies.

Is social network analysis just measures and methods with no theory? We attempt to clarify some confusions, address some previous critiques and controversies surrounding the issues of structure, human agency, endogeneity, tie content, network change, and context, and add a few critiques of our own. We use these issues as an opportunity to discuss the fundamental characteristics of network theory and to provide our thoughts on opportunities for future research in social network analysis.

To determine the role of status information conveyance in a negative reward allocation setting.

Using previously published experimental data, we test the relative effects of status information conveyed by expressive and indicative status cues on the allocation of a negative reward. Further, we construct an alternative graph theoretic model of expectation advantage which is also tested to determine its model fit relative to the classic model of Reward Expectations Theory.

Results provide strong support for the conclusion that status information conveyed by expressive status cues influences reward allocations more than information conveyed by indicative cues. We also find evidence that our alternative graph theoretic model of expectation advantage improves model fit.

This research is the first to test the relative impact of expressive versus indicative status cues on the allocation of negative rewards and shows that status characteristics can have differential impacts on these allocations contingent on how characteristics are conveyed. Furthermore, the research suggests a graph theoretic model that allows for this differentiation based on information conveyance and provides empirical support for its structure in a negative reward allocation environment.

Future research is required to validate the results in positive reward situations.

The results show that an individual’s expectations are altered by varying the manner in which status information is presented, thereby influencing the construction and maintenance of status hierarchies and the inequalities those structures generate. Thus, this research has implications for any group or evaluative task where status processes are relevant.

This paper examines social influence in collective task settings using the Berger, Fisek, Norman and Zelditch's graph-theoretic method. The work examines in-group membership in task settings, and models contexts where both status processes and group membership are salient. At the core of these models is a theoretical concept called a group status typification state, defined as an abstract understanding that participants hold of the type of person who would be a good source of information. This paper builds upon recent theory and research and may serve as an initial step toward integration of Status Characteristics Theory and Social Identity Theory.