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The OCR Glossary

Network Theory

Jon MacKay

Within the social sciences, a network is defined as a series of relations (or ties) between multiple actors (or nodes). Network theory is concerned with the implications of occupying a position within a network. Research has found that people’s positions in social networks—defined broadly as any network that involves people—can yield advantages in the kind of information people receive and how rapidly they receive it relative to their peers. Although interest in networks spans traditional disciplinary boundaries, network theory is important for the study of corporate reputation because reputations are generated, sustained, and conveyed within networks. This entry covers the development of network theory, various theories of networks and network theory, the key concepts within network theories, existing criticisms of network theory, and implications for corporate reputation.

Development of Network Theory

Social psychologists and sociologists pioneered much of the work dealing with networks in the social sciences. These researchers were interested in the effects social connections have on a person’s life. Rather than focusing only on the attributes of an individual—a person’s human capital—these researchers explored the structure of individuals’ social connections. In 1950, social psychologist Alex Bavelas performed experiments in which groups of volunteers had to perform concrete tasks. He found that the structure of participants’ communication networks determined how well they completed the tasks and how much they enjoyed working with others. Since then, many researchers have found that the structure of network ties—individuals’ social capital—explains social outcomes with greater accuracy than examining individuals’ characteristics in isolation.

The early successes of network theory in small networks were soon repeated on larger scales. Sociologists applied early insights about the importance of network position to the social networks that exist between corporations. In the 1970s, studies of the elites that ran corporate America focused on corporate interlocks, which occur when directors sit on the boards of more than one corporation. These studies grappled with understanding the social ties that connect large American public companies. Some thought that interlocks act as conduits for information to flow between corporations. Others argued that the interlocking could be used to improve the reputation of a corporation by linking a firm’s management to other important organizations. Additional insights from this field of work were that common directors were found to be responsible for diffusing information about corporate strategies across companies.

The latter part of the 20th century was a period in which network measurement increased in sophistication to better test competing hypotheses. Economic sociologists concerned with the workings of the economy later extended their work to examining exchange networks where social relationships were assumed to be embedded within repeated economic transactions. More recent work has also examined the implications of individual and organizational status.

Theories of Networks and Network Theory

The complex architecture of networks has always engaged scholars from numerous fields, including mathematics, engineering, and the sciences. Often researchers from these disciplines focus on a branch of research called theory of networks. In contrast, network theory in the social sciences is concerned with the social implications of network position. It is important to stress that the boundaries between these fields are not always clear and inspiration and insights are frequently shared.

Mathematicians tend to focus on random networks because of the elegant mathematical properties these networks display. However, sociologists know that the social world people inhabit is not random at all. With this intuition, Stanley Milgram devised his famous “small-world” experiment in 1967. Milgram sent packages to 160 people in Omaha and asked them to deliver the parcel only through their personal acquaintances until the package reached a particular stockbroker in Boston. Milgram’s findings are the basis for the popular (although erroneous) belief that there are just six degrees of separation between everyone. Although the experiment had significant shortcomings, it illustrated that most people are well connected to others within tightly interconnected communities.

Some people, however, maintain connections that bridge different communities. Small-world networks tend to be composed of clusters of interconnected nodes, with a few linking to other clusters. Most social networks—be they between people or organizations—are small-world networks.

Not until the 1970s and 1980s did researchers start to appreciate the implications of the small-world structure of most social networks. While studying how people find a job, sociologist Mark Granovetter, like many others, assumed that people rely on their close connections, such as their neighbors, friends, and relatives, to find suitable jobs. Granovetter’s fieldwork brought him to the conclusion that it was not the numerous dense ties that individuals maintain that bring news of a job. Instead, it tended to be acquaintances who brought useful leads. Granovetter argued that the strength of these weak ties was that they brought novel information from outside. Inside highly connected groups, most information was already known.

Ronald Burt formalized this argument and developed a concise measure to capture which actors in a network had access to multiple different communities. Burt termed those individuals who occupied this position in a network brokers. Communities of tightly connected individuals—closed networks—tend to trust one another and share information. Within these communities, there is a large reputation cost for bad behavior because word of a transgression will spread quickly. The trust and shared information closed networks engender mean that groups tend to reach a consensus on issues. At an extreme, this same process can lead to groupthink, where individuals uncritically submit to group norms.

In contrast, brokers have access to a wider set of ideas from different communities and bring news from one community to another. Thus, brokers can gain advantages both from access to a greater breadth of information and from acting as arbiters of that information.

Another important part of network theory considers individuals’ positions relative to others in terms of status. Status research considers individuals who are well connected to others who themselves are also well connected. This stream of research considers how high-status people or organizations operate compared with others and the benefits that accrue to high-status actors. Those considered to be high status can often do things that others cannot. While this is not the same concept as reputation, there is frequently an overlap. Reputation is an audience’s estimation of future behavior based on past actions. People and organizations with high status (i.e., those who are affiliated with similarly well-connected others) are more likely to be considered reputable.

Capturing Key Concepts

Network theorists analyze social networks through precise measurements that describe the different positions in a network. The focal actors in a network are called nodes, and their connections to others are called ties. Social networks can be of many different types. Nodes are often people or organizations, and ties can be friendships, professional relationships, or business deals. To focus on one particular node, analysts call the node ego. Ego’s network of immediate contacts are collectively called alters. Although this terminology may seem cumbersome, it allows researchers to abstract away from individual characteristics and focus instead on the structure of the network that surrounds a given node.

To understand the implications of a node’s network position, a few key measures are used. Degree is a measure of how connected an individual is to others in a network. It refers simply to the number of ties a node has to other nodes. Nodes that have a higher degree are more central or closely tied to others in the network. Those with a low degree are more peripheral. This is also called degree centrality.

However, the degree centrality measurement does not yield much information about a node’s context within the broader network. There are various centrality measures that capture different aspects of the network. One important centrality measure, eigenvector centrality, captures the status of a node. This measurement takes into account how connected one is to others who are also well connected. This makes sense because we intuitively know that high-status individuals tend to be connected to other high-status individuals.

Some people in a network act as bridges between otherwise densely connected groups. To measure to what extent individuals act as brokers, Burt developed the measure of constraint. The measure takes into account not only the ego node’s connections but also the connections of each node connected to ego. When a node is connected to other nodes that are also interconnected, they are more constrained. Individuals who are connected to different communities in the network are less constrained—they are brokers.

Criticisms of Network Theory

The main criticisms leveled against network theory essentially argue that it is not a theory at all but simply an assemblage of network measurements. However, the “Development of Network Theory” section above emphasizes the substantive issues underlying some key works by network theorists. In part, this is to emphasize the primary role that theory has had in the development of measures for social networks. Researchers who are concerned with network theory focus on measures precisely because these measures are designed to be closely tied to the underlying theory.

Implications for Corporate Reputation

As noted above, social networks tend to be composed of clusters of highly interconnected individuals with a few connections that span groups. Closed networks of tight connections facilitate communication and trust building. Research indicates that closed networks are necessary for the formation and maintenance of reputation. Reputation is developed within closed, interconnected groups where people talk and come to a consensus. Thus, some individuals and organizations have strong reputations within their own communities but are virtually unknown outside them. Brokers, who span multiple different groups and have deep roots in each, can develop multiple reputations within different closed communities.

Reputation and status are important elements of successful brokerage. Burt has found that higher-status or -reputation individuals are more likely to be successful brokers. People who attempt to bring new ideas from one group to another often fail. To be successful brokers, individuals need to have developed solid reputations within each community, or they will not be taken seriously. Reputation and status are therefore important contingent variables. While reputation is often difficult to measure directly, its indirect effects can be captured.

Network theory has important implications for corporate reputation researchers and offers useful ideas to complement existing theoretical approaches. Although network theory can be initially daunting because of the sheer breadth of network studies, this entry has focused on a few key concepts applicable to corporate reputation researchers.

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Burt, R. S. (1992). Structural holes: The social structure of competition. Cambridge, MA: Harvard University Press.

Burt, R. S. (2007). Closure and stability: Persistent reputation and enduring relations among bankers and analysts. In J. E. Rauch (Ed.), The missing links: Formation and decay of economic networks (pp. 100–141). New York: Russell Sage Foundation.

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Granovetter, M. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360–1380.

Granovetter, M. (1985). Economic action and social structure: The problem of embeddedness. American Journal of Sociology, 91(3), 481–510.

Mizruchi, M. S. (1996). What do interlocks do? An analysis, critique, and assessment of research on interlocking directorates. Annual Review of Sociology, 22(1), 271–298.

Podolny, J. M. (2008). Status signals: A sociological study of market competition. Princeton, NJ: Princeton University Press.

See Also

Complexity Theory; Network Analysis; Reputation Formation; Research Methods in Corporate Reputation; Rumor and Gossip; Social Capital Theory; Status

See Also

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