The metaphor of organization-as-networks directs attention to the dynamic nature of the process of organization as an emergent, evolving, and dynamic. At a global level, theorists have engaged with different forms of interdependencies, whether social, political or economic, as exemplified by Castellsâ€™ (2000) sweeping cross-cultural argument for the Information Age examining its â€œobject of analysis (informationalism) throughout social domains and cultural expressionsâ€ (pg. 26). CMC researchers have advocated a social networks approach â€œfor understanding the interplay between computer networks, CMC, and social processesâ€ (Garton, Haythornwaite, & Wellman, 1999, pg. 76). On the other hand, researchers such as Watts and Strogatz (1998) describe the â€œsmall-world phenomenonâ€ to demonstrate the common logic underlying â€œneural networks of the worm Caenorhabditis elegans, the power grid of the western United States and the collaboration graph of film actors are shown to be small-world networksâ€ (pg. 440) whose connection typology vacillates between the two extremes of complete randomness to completely ordered. And for what its worth, at an anecdotal level, the network metaphor appeals to those of us drawn to characterizations of a global world where the notion of six degrees of separation evokes the charm of a mathematical logic of linkages coupled with a certain degree of disordered chance and randomness. But however diverse the theoretical concerns of the small world theorists or the network society advocates, the underlying metaphor of the network unifies these at a fundamental level in a quest to explain the dynamic and structural properties of different networks.
Contractorâ€™s work (2006; 2003; 2002) focuses on the dynamic properties of social networks rather than purely biological or technological networks. In arguing for a multi theoretical multi level perspective to the study of communicative, organizational and social networks, Monge and Contractor (2003) critique the existing body of network research as predominantly atheoretcial and operating from a single level of analysis. Further, they find that most network research does not adequately take into account the structural complexity of network configurations while contextualizing their relationships with other networks and lacks valid inferential statistical measures for testing network hypotheses or for generalization. In order to address these shortcomings, the MTML model posits an integrative three-tiered look at network research grounded in a theoretical analysis of network components and combines this with an attribute analysis of its nodes in relation with their components as well as other levels of the network. Finally, the third tier postulates a multiplex approach, one that integrates spatial as well as temporal properties of network relations.
A significant contribution of the MTML approach to the study of networks is that it privileges a priori the theoretical groundings of networks, using â€œsocial theories to identify theoretical mechanisms relevant to network realizationsâ€ (Monge & Contractor, 2003, pg. 298). In doing so, the MTML model is able to integrate a multi-disciplinary framework of theories in conceptualizing the structural properties of networks at different levels of analysis (Contractor, Zink, & Chan, 1998; Hollingshead & Contractor, 2006). This is especially significant as it enables network researchers to evaluate emergent networks through different theoretical lens, thus allowing systematic evaluation of specific network configurations. For example, the logic of collective action theories is utilized to explore the communication networks that explain the emergence of the collective. Theoretically grounding such questions helps in exploring research questions at different levels, from examining how many linkages it may take for an actor to find an appropriate knowledge node to studying the dynamic nature of such networks. For example, it would help to look at the adaptive or reorganizing mechanisms within knowledge networks, and how these relate to different knowledge goals of the network. By doing so, the approach enables a conceptualization of solutions that direct organizational efficiencies inherent in the specific network form towards specifically targeted organizational goals.
Monge and Contractor (2002) conceptualize a knowledge management (KM) network through a breadth of social and communicative theories ranging from theories of self-interest to cognitive theories and exchange and dependency theories in order to â€œunderstand the psychological, social, and communicative mechanisms by which knowledge network ties are created, maintained, dissolved, or reconstitutedâ€ (pg. 350). In examining the network linkages chosen to achieve certain goals through different theoretical perspectives, the knowledge management network assumes greater importance in an age of different forms of P2P infrastructures (see Contractor, 2003 for conceptual definition). Here greater autonomy and choice in information seeking highlights the relevance of questions such as who knows what? Or who is perceived as knowing who knows what? and so on in deciding how information is sought and from whom under what conditions. Therefore, in a context where knowledge as a function of information access, integration, and synthesis is fundamentally connected to the network nodes, actors, and linkages (as distributed knowledge, cognitive knowledge networks, etc) network analysis provides â€œa framework to analyze the state and co-evolution of knowledge networksâ€ (Contractor, Zink, & Chan, 1998, pg. 204) integrating the perceptual, cognitive, and functional aspects of knowledge management among the actors.
As the MTML model takes the level of analysis into account alongside the configuration of the network, at a systemic level it forms a useful model in integrating local knowledge with global systems. One of the imperatives of a globalized world is access to information that may be available at local nodes in order to assimilate or analyze it for different goals at another level. At a system level, such linkages have been explored in different ways (and with different organizational imperatives) by global social movements, multi national corporations, and other transnational agencies. The relationship of the underlying information architecture with the emergent knowledge network form, efficiencies, and functionality is also important in exploring knowledge networks. Monge and Contractor (2003) describe the properties of the P2P infrastructure in enabling peer to peer interactions. The MTML model applied to the knowledge network integratively explores different facets of organization, structure, and form with the process of forming knowledge linkages. In this regard, it helps in examining the mechanisms explaining the co-evolution of the knowledge network with the underlying architectural form. While small network theorists have explored the different geometries of networks (lattice form, star form, etc) the relationship of specific architectural forms with different kinds of knowledge management networks becomes important. The knowledge management network also draws on the ability of different nodes to be â€œactivatedâ€ when need be, or the ability to draw on available knowledge resources efficiently. Integrating network research with theory facilitates the analysis of the communicative, organizational, or social dimensions of such interactions and linkages.
Theoretically, given a potential possibility of achieving connectedness with resources, individuals, knowledge bases at different geographic, cultural, or otherwise dispersed levels, the knowledge management network research proposes a systematic framework of evaluation of such possibilities. It appeals to researchers and practitioners alike- maybe from evolutionary biologists like those who believe in the gaia approach, taking the earth as a single living networked organism, to small network theorists or those who may want to study the emergence of simplicity from complex systems, or yet others who may want to maximize knowledge efficiencies at a functional level in an organization.
Castells, M. (2000). The rise of the network society. The Information Age: Economy, Society, and Culture, Volume I. Malden, MA: Blackwell Publishing.
Contractor, N. (2002). Introduction: New Media and Organizingâ€ In Leah Lievrouw & Sonia Livingstone (Eds), Handbook of New Media: Social Shaping and Consequences of ICTs (pp. 201-205). London: Sage.
Contractor, N. S., & Monge, P. R. (2002). Managing knowledge networks. Management Communication Quarterly, 16, 249-258.
Contractor, N. (2003). Peer to peer. In S. Jones (Ed.), Encyclopedia of New Media (pp. 367-369). Thousand Oaks, CA: Sage.
Garton, L., Haythornwaite, C., & Wellman, B. (1999). Studying on-line social networks. In Seve Jones (Ed.), Doing Internet Research: Critical Issues and Methods for Examining the Net, pp. 75- 106. Thousand Oaks, CA: Sage
Hollingshead, A. B., & Contractor, N. S. (2006). New media and small group organizing. In S. Livingstone & L. Lievrouw (Eds.), Handbook of New Media: Student Edition. (pp. 114-133). London: Sage.
Monge, P. R., & Contractor, N. (2003). Multitheoretical, Multilevel Models of Communication and Other Organizational Networks . In Theories of Communication Networks (pp. 293-327). New York: Oxford University Press.
Watts, D. J. (1999). Networks, dynamics, and the small-world phenomenon. American Journal of Sociology, 105(2): 493-527.
Watts, D. J. & Strogatz, S. H. (1998). Collective dynamics of â€˜small-worldâ€™ networks. Nature, 393(4): 440- 442.