Knowledge management (KM) represents a topic of considerable current interest. However, the majority of extant KM research treats knowledge as a static object that can be acquired, stored and retrieved through information technology. Two fundamental problems emerge from this current majority view: (1) many scholars view knowledge as distinct from information, and (2) very little attention is paid to the dynamics of knowledge—a phenomenon which many scholars term “knowledge flows. ” In this article we build upon a steady stream of research in computational organization theory to develop agent-based models of knowledge flows. Such models draw from emerging theory for multidimensional representation of the knowledge flow phenomenon, and they enable the dynamics of enterprise knowledge flows to be formalized and simulated through computational models. We illustrate this research approach and modeling environment through formal representation and simulation of knowledge flows from the domain of information systems design. 1.

Topic Maps are a knowledge representation standard. Distributed Knowledge Management describes a knowledge-based organization as network of more or less independent units (Knowledge Node) which create and exchange knowledge. This paper describes how Topic Maps can be used to model organizational and spatial structure of DKMS and interaction scenarios between Knowledge Nodes. Deployment of a runtime system is discussed and how measurements at runtime can be used to reveal unknown Knowledge Nodes and interaction pattern inside a DKMS.

Facilitating the transfer of knowledge between knowledge workers represents one of the main challenges of knowledge management. Knowledge transfer instruments, such as the experience factory concept, represent means for facilitating knowledge transfer in organizations. As past research has shown, effectiveness of knowledge transfer instruments strongly depends on their situational context, on the stakeholders involved in knowledge transfer, and on their acceptance, motivation and goals. In this paper, we introduce an agent-oriented modeling approach for analyzing the effectiveness of knowledge transfer instruments in the light of (potentially conflicting) stakeholders ’ goals. We apply this intentional approach to the experience factory concept and analyze under which conditions it can fail, and how adaptations to the Experience Factory can be explored in a structured way. 1.

Abstract. This article describes a knowledge management (KM) approach conceived from countermeasures targeted at addressing failure factors suggested in the literature. In order to counteract failure factors, the approach combines the technology of knowledge-based KM systems, with the flexibility and understanding of knowledge facilitators, and the processes of the target community. In the KM system, the approach uses knowledge engineering concepts to represent knowledge artifacts and to enforce managerial responsibilities. By imposing a strict representation format, the approach guides and helps users. It does so by determining what knowledge to contribute, by enabling knowledge collection, and by representing knowledge. The purpose of knowledge facilitators is to complement the limitations of the computerbased component by verifying the quality of submitted artifacts and by motivating members to adopt the system. The design and operation of this approach is guided by identifying the processes of the target community and the level of specificity where they are useful. The importance of this contribution is that it offers guidelines to design a KM approach that relies on conclusions from published literature. In addition, it also proposes a means to validate knowledge sharing. A conclusion of this work is that it may be easier to address failure factors of KM approaches when all members of the target community have the same technical goals, are motivated by a common interest, are organized on a flat hierarchy, and are receptive to innovation. In addition, the use of a representation of the community’s processes helps standardize capture, guide contributors, and associate existing with new artifacts. This association of artifacts can be used to validate knowledge sharing.

Algorithmic research is an established knowledge engineering process that has allowed researchers to identify new or significant problems, to better understand existing approaches and experimental results, and to obtain new, effective and efficient solutions. While algorithmic researchers regularly contribute to this knowledge base by proposing new problems and novel solutions, the processes currently used to share this knowledge are inefficient, resulting in unproductive overhead. Most of these publication-centred processes lack explicit high-level knowledge structures to support efficient knowledge management. The authors describe a problem-centred collaborative knowledge management architecture associated with Computational Problem Solving (CPS). Specifically we articulate the structure and flow of such knowledge by making in-depth analysis of the needs of algorithmic researchers, and then extract the ontology. We also propose a knowledge flow measurement methodology to provide human-centred evaluations of research activities within the knowledge structure. This measurement enables us to highlight active research topics and to identify influential researchers. The collaborative knowledge management architecture was realized by implementing an Open Computational Problem Solving (OpenCPS) Knowledge Portal, which is an open-source project accessible at http://www.opencps.org.

2. Methodology 3. Nature of knowledge flow

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Abstract—In today’s business instant availability of up-todate information is a vital prerequisite for decision making and the execution of many job tasks. Especially in service business, service job experience and information about the customer as well as the installed site equipment are key factors to deliver services efficiently and with high quality. In many cases supporting information is stored in different backend systems and it needs to be retrieved, aggregated and presented on demand. These requirements play a crucial role for contact centers, which have the first contacts with customers, as well as for the field service engineers, who have the closest contacts with the customers during executions of service jobs at the customers ’ sites. In this paper, a typical service process is presented and a case study is used to show how knowledge management technologies can provide improvement possibilities for a service business company. D I.

Abstract Requisite variety has influenced concepts of environmental relations of organization for almost half a century. This article develops the concept of ‘requisite foresight’ on the basis of its roots in cybernetics and extends its applicability to contemporary knowledge management. Organization theory incorporating a temporal aspect and reaching for ‘requisite foresight ’ challenges a dualistic and rigid interpretation of organizational environment. If considered within a network of organizations ‘distributed knowledge ’ paves the way for ‘requisite foresight’. A ‘foresight ’ approach explains prevalent perspectives in new e-business applications, like supply chain management and customer relationship management. Concluding, ‘requisite foresight’ merges strands of reasoning useful to the expansion of organizational models in the knowledge economy. 1

Peinl, Rene and Maier, Ronald, "SimKnowledge- Multi agent-based simulation of knowledge sharing " (2009). AMCIS 2009