C H A PT E R 4 Conceptualizing Knowledge Emergence

C H A PT E R 4
Conceptualizing Knowledge
Emergence
4.1 GATEKEEPERS,INFORMATION, STARS,AND BOUNDARY SPANNERS
The seminal work was that of Thomas J. Allen of MIT [Allen and Cohen, 1969, Allen,T.,1977] who conducted a number of studies relating to information flow in industrial and corporate R&D laboratories.Allen’s most ingenious contribution to the field was to seize upon the phenomenon that in many cases in the context of military R&D and procurement, the same contract is awarded to two different organizations to achieve the same end, typically in the case of a critical component of a larger system. Duplicative development contracts may, in fact, be very worthwhile insurance against the failure of a key component of a system. This duplication provided a wonderfully robustcontext in which to examine information flows and what distinguished the information flows in the more successful projects from the less successful.
Allen coined the term ‘Gatekeeper’ to describe the information flow stars that he discovered,the heavily connected nodes in the information flow pattern. The reason that he chose that term was that much of the development and project work that he investigated was classified military work, where there seemed to be something of a paradox, how was a team to be successful if it didn’t effectively connect with the world of information outside the organization? But how did it do that in a classified and communication restricted environment?What he discovered was that the information stars, the sociometric stars, were the answer to that paradox; they were the information channels through which external information reached the project team.That role was so crucial in the contexts that Allen typically investigated what he termed his sociometric stars “Gatekeepers.” They oversaw and guarded the gates through which external information reached the projects. Indeed, one might say that they were not just the gatekeepers, they themselves were the gates.
4.2 RESEARCH PRODUCTIVITY AND KNOWLEDGE
The ‘Gatekeepers, Information Stars & Boundary Spanner’ tradition is very consistent with a substantial body of work studying research productivity. Koenig,M. [1992a], for example, in the context of the U.S. pharmaceutical industry, studied the relationship between research productivity and the information environment in which that research was conducted. The productivity measure was, at base, simply the number of approved new drugs (new drug applications or NDAs) per millions of dollars of R&D budget. This measure, however, was refined by weighting the NDAs in regard to: 1) whether or not the Food and Drug Administration (FDA) judged the drug to be an “important therapeutic advance,” 2) the chemical novelty of the drug, and 3) the filing company’s patent position in regard to the drug, an indicator of where the bulk of the research was done. The study is compelling because of the high face validity of the measure of success, the successful introduction of new pharmaceutical agents, since that is what pharmaceutical companies are about after all, and because of the statistical robustness of the results, a consequence of the fact that the more successful companies were found to be not just twenty or thirty percent more productive than the not so successful companies, they were two or three hundred percent more productive.
The more productive companies were characterized by:
·         A relatively egalitarian managerial structure with unobtrusive status indicators in the R&D environment,
·          Less concern with protecting proprietary information,
·         Greater openness to outside information, greater use of their libraries and information centers, specifically, greater attendance by employees at professional meetings,
·         Greater information systems development effort,
·         Greater end-user use of information systems and more encouragement of browsing and serendipity. Increased time spent browsing and keeping abreast,

4.3 LACK OF RECOGNITION OFTHESE FINDINGS IN THE BUSINESS COMMUNITY
As Allen pointed out in his study, there is a surprising lack of recognition of these findings about the importance of information stars in the business community. This is, in fact, a subset of an even larger problem - the lack of recognition of or even obtuseness to the importance of information and information related managerial actions in the business community. For example, one major study that reviewed a large corpus of work on R&D innovation, [Goldhar et al., 1976], concluded that there are six characteristics of environments that are conducive to technological innovations. The three most important characteristics are all related to the information environment and information flow – specifically: 1) easy access to information by individuals; 2) free flow of information both into and out of the organizations; 3) rewards for sharing, seeking, and using “new” externally developed information sources. Note the ‘flow in and out’ and the ‘sharing, seeking, and using’. Number six is also information environment related, 6) the encouragement of mobility and interpersonal contacts. Yet in a remarkable oversight, the studies’ authors never remarked on the dramatic win, place, and show finish of information and knowledge factors.

4.4 COMMUNITY-BASEDMODELS
The Information Systems literature points to an abundance ofKMstrategies in the category of Computer Mediated Communication (CMC). Such systems provide the infrastructure for enabling the interactions needed for a group’s knowledge synergies and interactive activities [Maier, R., 2002] and may include bulletin boards, electronic meeting/conferencing, or online chat. In this model, the notion of space [Ruhleder, K., 2002], physical or otherwise, is important primarily because the meeting place or system provides an environment that allows for interactions to unfold, at the convenience of individual participants, often asynchronously. Further, such CMC interactions allow for the creation of persistent records [Robins, J., 2002] of the interactions. Chat and other kind of social media transcriptions can be preserved too as another example. To the extent that discourse occurs through such interactions, the dialectics can be archived for future reference and subsequent “reuse.” However,  asHislop, D. [2002] points out, while technology may provide the tools for interaction and communication, the application of technology alone may not be a sufficient condition for sustaining the creation and sharing of knowledge.

4.5 REPOSITORY MODEL
The knowledge management repository, a space to store and retrieve knowledge objects has long been a standard in KMprograms. It is a model that emphasizes the creation of quality knowledge content in online repositories with re-use as a goal. Markus, M. [2001] argues that the purpose and content of knowledge records in repositories often differ depending on who needs the documentation: the content producer, similar others, or dissimilar others. She emphasizes that a great deal of effort is required to produce quality content, and, as such, part of the burden of documenting and packaging knowledge objects can be transferred to intermediaries, saving time and energy of the organization’s staff. In addition, adding context is also another aspect of making content more usable. Markus proposes the roles of human intermediaries in what she terms as “repurposing” of repositories to make them more appropriate for use by others. Examples of activities that could be performed include abstracting, indexing, authoring, and sanitizing or scrubbing content. Because of the costs involved in repackaging and making repository knowledge content more usable to the knowledge seeker,Markus looks to an expanded role for technological support of core competencies of librarians, archivists, data curators, and other information professionals.

4.6 ACTIVITY-BASEDMODELS
While there has been significant work done in terms of Information Systems support for the coordination of work [Winograd,T., 1988], the next logical progression would be to link knowledge production and capture with work processes. For example, Blackler, F. [1995] considers knowledge in organizations as socially distributed collective activity systems, and emphasizes the significance of incoherence and dilemma as the key issues in social systems. Similarly, Engeström, Y. [1999] research, using activity systems as cycles of expansive learning in work practices, also points to the  importance of activities as providing the necessary context for grounding organizational knowledge. Based on such a historical-cultural perspective of activity, Hasan, H. [2003] proposed rudiments of a KM system influenced by activity-based models that would link work activities with people and content.

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