Designing information and communication technologies (ICT) for knowledge work is a primary challenge in research and practice of knowledge management. Knowledge workers supposedly organize and manage their workplaces, at least partly themselves, which needs to be considered when designing ICT for supporting their daily knowledge-intense activities. It is considered useful for designers of knowledge management systems (KMS) to look into the results of behavioral science in information systems concerning the adoption, acceptance and assimilation of ICT. Thus, this paper proposes a model that contributes to bridging the gap between design science and behavioral science in the domain of knowledge management. In this regard, widely recognized behavioral models that aim at explaining organizational and human behavior in conjunction with ICT are analyzed in order to extract important factors influencing the successful application of KMS with respect to the adoption by an organization or organizational unit, acceptance by individual knowledge workers, and assimilation into knowledge processes and practices. By combining, categorizing, and structuring these factors, we developed a comprehensive model to be taken into account in software design and evaluation processes from various perspectives. Moreover, we discuss a case example in which this model is applied to the design of a KMS.
In knowledge intensive companies intellectual capital assumes a crucial role in the organizational strategy and, as any other strategical asset, it needs to be scheduled to achieve sustainable competitive advantage. When the required knowledge is a resource available inside the company, its assignment represents a key success factor, which many research efforts are devoted to. On the other side, when the needed competence is unavailable within the company, training programs may be seen as methods to strengthen such a strategic asset. In this paper we show a semantic-based integrated system aimed at supporting both the assignment of available intellectual resources in three different multiplicity scenarios and the search for training programs ad-hoc composed to fill possible knowledge gaps.
The interaction between a knowledge management systems and the users requires well-adapted visualization tools with graphical formalization of knowledge. The formalization is often theoretically based on graph-models. Yet, the best associated visual representations use trees but may be more limited than those with graphs. This paper gives an introduction to Atanor, a knowledge management system, whose graphical model for visualizing knowledge is tree-based. However this approach entails vertex redundancies. Consequently, we develop a new approach based on a layered digraph to solve this problem. Finally, we draw a comparison on an industrial example showing the advantages of the new model.
In many areas of the medical domain, the decision process i.e. reasoning, involving health care professionals is distributed, cooperative and complex. Computer based decision support systems has usually been focusing on the outcome of the decision making and treated it as a single task. In this paper a framework for a Clinical Reasoning Knowledge Warehouse (CRKW) is presented, intended to support the reasoning process, by providing the decision participants with an analysis platform that captures and enhances information and knowledge. The CRKW mixes theories and models from Artificial Intelligence, Knowledge Management Systems and Business Intelligence to make context sensitive, patient case specific analysis and knowledge management. The knowledge base consists of patient health records, reasoning process information and clinical guidelines. Patient specific information and knowledge is continually enhanced by adding results of analysis. Context sensitive analysis is done by retrieving similar patient cases and guidelines from the knowledge base in a case based fashion.
People need information to create new knowledge. For each piece of information obtained, a range of previous knowledge, competences, beliefs and own concept definitions significantly influence personal perception and one’s knowledge creation. This in turn, affects the ability to remember, reason, solve problems and interpret information. These issues have to be considered when planning knowledge management systems, in which information retrieval and handling, reuse, people interaction, knowledge interchange and dissemination comprise its characteristics. This paper is based on the Knowledge Object definition from Merrill and proposes an approach which more precisely enables Knowledge Object representation, taking into account the domain in which a KO is used, a range of previous knowledge, competences, beliefs, concept definitions, user profile and recommendation from community users.