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

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

The Role of Knowledge Dynamics in Developing a Medical Community of Practice

This research investigates the dynamics of communities of practice (CoP) seen as an essential elements of up surging knowledge societies. The concept of CoP has received much attention from researchers and practitioners in KM. In this context, CoPs are seen as voluntary associations of people who choose to improve their skills and problem solving capabilities by collectively generating and processing knowledge. These organisational settings must be, at least in part, set free to evolve and self\u2010organise in some way, in order to ensure an effective sharing of tacit knowledge which is the essential goal of a CoP. The problem of managing the formation and evolution of a CoP is, therefore, to investigate the conditions under which self organisation mechanisms can make CoPs improve their performance. The paper investigates this issue by adopting the approach of computational intelligence. Particularly, it uses genetic algorithms to model and simulate the formation and evolution of a CoP. It is assumed that a CoP evolves thanks to the interactions between independent agents (i.e. the members) that share knowledge for decision making. The genetic algorithms are used to investigate if there are conditions or configurations that can enable the CoP to develop and improve in terms of performance. An experimental study of a CoP\u2019s structure optimisation is conducted, based on real data collected from a medical facility. The capability of the genetic algorithms to identify producing optimal restructuring of a set of CoP agents (in our case medical staff involved in the rehabilitation of the impaired patients) is tested. By aggregating and re\u2010aggregating the members in different ways, it is analysed how a performance index that measures the CoP performance can be improved. The method proves to be useful to understand the possible mechanisms by which a CoP can develop, and provides suggestions for its managemen