In resource based learning settings learners have to cope with a multitude of resources. One big challenge for learners is managing the knowledge contained in these resources appropriately. We discuss some existing knowledge modeling methods and related tools with regard to learning scenarios. This paper focuses on presenting a knowledge modeling approach based on personal knowledge networks. Aggregation and mapping of these personal networks can form a community network supporting exchange of knowledge. Furthermore a proof-of-concept is described.
Various studies focus on general networks within and between organizations, but strongly focused studies on knowledge sharing through social networks and communities within specific domains that are of critical relevance to the R&D organization are hard to find. Therefore, the argument presented here is explored through an empirical case study on inter-organizational knowledge community building between different research institutes of the Fraunhofer-Gesellschaft, a large German organization for contract research in all fields of the applied engineering sciences. Expert knowledge communication and networking processes are evaluated by a multi-level approach. Institutionalization of knowledge transfer is studied with regard to the development of the informal contacts between the community members and the inter-organizational linkages on an aggregated level. The main focus is put on the relationships of knowledge exchange between the formal organizational boundaries and the informal interorganizational network structures. Finally, this case study aims at further supporting the adaptation of methods from social network analysis for purposes of organization and management practice.
Intellectual capital reports usually consist of descriptions of various non-financial capital forms, such as for example “relational capital”. Considering relational capital as knowledge networks we explain the creation, transformation and re-use of knowledge with the help of the theory of social systems where knowledge is seen as a cooperative social construction. As a method for visualizing and analyzing relational capital based on co-authorships and co-content, respectively, we present BibTechMonTM and conclude with suggestions how the results of the knowledge network analysis may be utilized in organizations.
A well-functioning Knowledge Management (KM) is a competitive advantage for enterprises that act in co-operative and distributed networks with knowledge intensive production processes. A KM approach for distributed and dynamic entrepreneurial networks is currently missing. This paper presents a description model that comprises the relevant entities for an approach to KM in networks that integrates both new Information and Communication Technology driven organisational concepts and human-oriented approaches with KM methodologies and instruments.
This paper focuses on knowledge management in organizations going beyond traditional boundaries, through collaborations based on intangible assets. The analysis has been focused on the implications generated from the blend between the network organizational structure and knowledge management. A theoretical framework is provided in order to evaluate the impact of knowledge networks on knowledge management systems, identifying the most appropriate knowledge management strategies and processes, on the basis of network characteristics.
In many organisations, conservation of specialised expertise is picked out as a central theme only after experienced members have already left. The paper presents the SELaKT method, a method for Sustainable Expert Localisation and Knowledge Transfer based on social network analysis (SNA). It has been developed during a project co-operation between the Department of Information Science at the Institute for Media and Communication Studies, Free University Berlin, and the Fraunhofer Institute for Production Systems and Design Technology IPK, Berlin. The SELaKT method uses recent insights into network analysis and pragmatically adapts SNA to suit organisational practice. Thus it provides a strategic tool to localise experts, to identify knowledge communities and to analyse the structure of knowledge flows within and between organisations. The SELaKT method shows its advances and increasing relevance for practical use by integration of specific organisational conditions and requirements into the process of analysis.
This paper reports on long-term research work of recycling networks in Germany and Austria from a knowledge-based perspective. Using data from expert interviews, we
discuss the key determinants of inter-organizational knowledge transfer within networks. In particular, we highlight the factor of mutual trust as important determinant of knowledge transfer in company recycling networks. One important goal of our empirical research is the institutionalization of knowledge transfer through the implementation of a central recycling agency in order to build core capabilities and to create intellectual capital.