Multitheoretical, Multilevel Models of Communication and Other Organizational Networks

In this book we have argued for a multitheoretical, multilevel approach to the study of communication and other forms of organizational and social networks. We began by exploring several problems within the existing corpus of network research. We then showed how the MTML model provides a network research strategy that resolves most of these problems. (For ease of presentation, this review of the essential arguments and social theories includes citations only to references that have not been cited in earlier chapters of this book.) The first problem is the fact that the vast majority of network research is atheoretical. One reason for this is that there are very few explicit theories of social networks. Another reason is that researchers are generally not cognizant of the relational and structural implications inherent in various social theories. Even research that does employ theory typically does so without much attention to the network mechanisms implicit in the theories. A second problem with network research is that most scholars approach networks from a rather myopic, single-level perspective, which is reflected in the fact that almost all published research operates at a single level of analysis. Thus, they tend to focus on individual features of the network such as density. For the most part, researchers tend to ignore the multiple other components out of which most network configurations are composed, structural components from multiple levels of analysis such as mutuality, transitivity, and network centralization. Employing single levels of analysis is not inherently wrong; it is simply incomplete. Importantly, these components suggest different theoretical mechanisms in the formation, continuation, and eventual reconfiguration of networks. Typically, better explanations come from research that utilizes multiple levels of analysis. The third problem centers on the fact that most network research focuses on the relatively obvious elementary features of networks such as link density and fails to explore other, more complex properties of networks such as attributes of nodes or multiplex relations. But the members of networks often possess interesting theoretical properties, which help to shape the configurations in which they are embedded, and networks are themselves often tied to other networks.