Using Network Analysis for Understanding How Decisions are Made

Using Network Analysis for Understanding How Decisions are Made

Frédéric Adam (University College Cork, Ireland)
DOI: 10.4018/978-1-59904-843-7.ch107
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Abstract

Network analysis, a body of research that concentrates on the social networks that connect actors in society, has been found to have many applications in areas where researchers struggle to understand the complex workings of organisations (Nohria, 1992). Social network analysis (SNA) acknowledges that individuals are characterised just as much by their relationships with one another (which is often neglected in traditional research) as by their specific attributes (Knoke & Kuklinski, 1982) and that, beyond individuals, society itself is made of networks (Kilduff & Tsai, 2003). It is the study of the relationships between actors and between clusters of actors in organisations and in society that has been labeled network analysis. These high level observations about network analysis indicate that this orientation has great potential for the study of how managers, groups of managers, and organisations make decisions, following processes that unfold over long periods of time and that are sometimes very hard to fully comprehend without reference to a network approach. This article proposes to investigate the potential application of network analysis to the study of individual and organizational decision making and to leverage its strengths for the design and development of better decision aids.

Key Terms in this Chapter

Centrality: Characteristic of a node which is well connected to many other nodes in the network.

Weak Tie: Characteristic of a relationship (as described by Granovetter, 1973) which connects nodes belonging to clusters weakly connected to one another (or even unconnected). Individuals involved in these relationships derive great power from having access to information no one else has in their cluster.

Structural Hole: Portion of a network where discontinuities exist in the circulation of information.

Social Network: Set of nodes (e.g., persons, organizations) linked by a set of social relationships (e.g., friendship, transfer of funds, overlapping membership) of a specified type (Lauman, Galskeiwicz, & Marsden, 1978, p. 458).

Social Cohesion: Characteristic of a portion of a network, for example, a cluster, where nodes are very strongly connected to one another. A consequence of cohesion is that little informational advantages can be derived from adding further linkages within the cluster.

Cluster: Area of a network where actors are densely connected.

Structural Equivalence: Characteristic of nodes that occupy similar positions and roles in a network. A consequence of structural equivalence is that equivalent nodes often share the same set of relationship and pursue the same objectives.

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