Chapter 4: Conceptualizing Knowledge Emergence

 GATEKEEPERS, INFORMATION, STARS,AND BOUNDARY SPANNERS

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 here 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 theinformation stars, the sociometric stars, were the answer to that paradox; they were the information channels throughwhich external information reached the project team.That rolewas 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

RESEARCH PRODUCTIVITY AND KNOWLEDGE

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.

LACKOF RECOGNITIONOFTHESE FINDINGS IN THE BUSINESS COMMUNITY

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

COMMUNITY-BASEDMODELS

The Community of Practice (CoP) is not necessarily department-based nor centered in one organization.ACoP can consist of those in chargeof human resources training, for example, in a number of organizations. These HR professionals can share what they’ve learned through experience about effective seminar scheduling and working with speakers. Reading a book about effective HR training is one way to learn, but sharing what experienced trainers know is a whole different level of learning. 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.

CONCEPTUALIZINGKNOWLEDGE EMERGENCE

A Group Decision Support System (GDSS) is able to calculate the votes and display them graphically, so that an individual attending the meeting can see if she or he were an outlier on certain issues or to determine where his or her vote stood as compared with peers. Although anonymous, each participant can have a unique code, known only to the participant, and follow voting patterns on the graphic display.These systems work well in a face-to-face situation where immediate feedback can be given and displayed. The GDSS has not migrated easily to theWeb, however, some web-based systems are available and have adapted to an asynchronous situation. Generic Decision Support Systems (DSS) that act more like expert systems with the added feature of suggesting decision options are well suited to the Web, and they are proliferating as the Web becomes the ubiquitous information and communication platform for information storage and retrieval, and for interaction as well.The range ofWeb-basedDSSs vary in quality fromthemundane (e.g., cosmetics or movie choices) to sophisticated tools such as diagnosing illnesses and suggesting appropriate drug therapies.

REPOSITORYMODEL

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.