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Journal Article

Knowledge use and Sharing into a Medical Community of Practice; the Role of Virtual Agents (Knowbots)  pp64-81

Virginia Maracine, Luca Iandoli, Emil Scarlat, Adriana Sarah Nica

© Jan 2012 Volume 10 Issue 1, ECKM 2011, Editor: Franz Lehner, pp1 - 109

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Knowledge‑oriented organizations are bricks for the knowledge‑based society construction. Building knowledge‑based society and economy suppose challenging transition processes from the classical structure of an organization to new organizational forms that help to fill the gap between actual society and the future knowledge‑based society and economy. This transition generates new issues in knowledge creation and sharing processes, related to the particularities of the new organizational forms. Therefore, in the last few years, our researches are oriented to developing and testing a number of forms of organization designed to facilitate an efficient and effective transition toward the knowledge‑based society, like communities of practice, (virtual) networks of professionals or knowledge ecosystems (KE). Under this general frame, this paper presents the results of our research aiming to capture the necessary changes that a medical organization specialized in rehabilitation (the National Institute of Rehabilitation and Physical Medicine from Bucharest, Romania ‑ INRMFB) has to undertake for converting its classical structure into a new knowledge‑oriented one, possible and easily to being integrated into a Virtual Network for Home Health Rehabilitation of the impaired people – the meta goal of our research in recent years. Specifically, within its five sections, the paper outlines: 1. An introduction in the macro and micro‑level empirical setting in which the study is carried out; 2. The methodological approach based on Social Network Analysis (SNA). Although quit often used in the medical field, as we will see in the second section of the paper, the SNA methods and models aren’t used yet in the particular area of health rehabilitation; 3. The objectives of the empirical study that can be summarized as follows: Mapping of the knowledge flows & needs in the target community of practice. The aim of this step is to produce an accurate picture of the knowledge flows that the target community identified at the INRMFB actually enacts in the accomplishment of its organizational objectives. Analysis & Diagnosis: Identification of critical aspects and areas of improvements (e.g. knowledge needs, knowledge bottlenecks, structural determinants of inefficiency or of poor performance). Design: definition of the functional specifications for redesigning the agents, network and of the functionalities of Knowbots. 4. The survey we have designed for data collection. According with the particularities of the macro and micro‑level in which our study is carried out, we have designed a survey that will help us both for diagnosing the knowledge‑sharing‑structure of INRMFB, and for finding adequate solutions for potential critical aspects identified in this medical facility.; 5. A set of conclusions and recommendations for the new knowledge‑oriented organizational structure to be created within the INRMFB. Alongside with performing SNA in the health rehabilitation field, an important output of our study is to find answer to the following questions: Cans the classical organizational structure of the INRMFB be transformed into a knowledge‑based one, by reengineering the knowledge flows and agent’s roles? If and where within the actual structure a virtual knowledge agent (knowbot) can and should be integrated? Our paper is a consequent continuation of our work in the KE area, contributing to the completion of an integrate vision over the role of the KM techniques, human and virtual agents in the emerging of knowledge‑based society. It presents a work still in progress, the final results of our study going to be presented within the ECKM2011 conference.


Keywords: community of practice, healthcare knowledge ecosystems, social network analysis, knowledge agent, Knowbot, collective learning, knowledge-based organization.


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