Knowledge sharing framework for sustainability of knowledge capital
MetadataShow full item record
Knowledge sharing is one of the most critical elements in a knowledgebased society. With huge concentration on communication facilities, there is a major shift in world-wide access to codified knowledge. Although communication technologies have made great strides in the development of instruments for accessing required knowledge and improving the level of knowledge sharing, there are still many obstacles which diminish the effectiveness of knowledge sharing in an organization or a community. The current challenges include: identification of the most important variables in knowledge sharing, development of an effective knowledge sharing measurement model, development of an effective mechanism for knowledge sharing reporting and calculating knowledge capital that can be created by knowledge sharing. The ability and willingness of individuals to share both their codified and uncodified knowledge have emerged as significant variables in knowledge sharing in an environment where all people have access to communication instruments and have the choice of either sharing their own knowledge or keeping it to themselves.This thesis addresses knowledge sharing variables and identifies the key variables as: willingness to share or gain knowledge, ability to share or gain knowledge, complexity or transferability of the shared knowledge. Different mechanisms are used to measure these key variables. Trust mechanisms are used to measure the willingness and ability of individuals to share or acquire knowledge. By using trust mechanisms, one can rate the behavior of the parties engaged in knowledge sharing and subsequently assign a value to the willingness and ability of individuals to share or obtain knowledge. Also, ontology mechanisms are used to measure the complexity and transferability of a particular knowledge in the knowledge sharing process. The level of similarity between sender and receiver ontologies is used to measure the transferability of a particular knowledge between knowledge sender and receiver. Ontology structure is used to measure the complexity of the knowledge transmitted between knowledge sharing parties.A knowledge sharing framework provides a measurement model for calculating knowledge sharing levels based on trust and ontology mechanisms. It calculates knowledge sharing levels numerically and also uses a Business Intelligence Simulation Model (BISIM) to simulate a community and report the knowledge sharing level between members of the simulated community. The simulated model is able to calculate and report the knowledge sharing and knowledge acquisition levels of each member in addition to the total knowledge sharing level in the community.Finally, in order to determine the advantages of knowledge sharing for a community, capital that can be created by knowledge sharing is calculated by using intellectual capital measurement mechanisms. Created capital is based on knowledge and is related to the role of knowledge sharing in increasing the embedded knowledge of individuals (human capital), improving connections, and embedding knowledge within connections (social capital). Also, market components (such as customers) play a major role in business, and knowledge sharing improves the embedded knowledge within market components that is defined as market capital in this thesis. All these categories of intellectual capital are measured and reported in the knowledge sharing framework.
Showing items related by title, author, creator and subject.
Chikolwa, Bwembya C (2008)According to the Reserve Bank of Australia (2006) the increased supply of Commercial Mortgage-Backed Securities (CMBS), with a range of subordination, has broadened the investor base in real estate debt markets and reduced ...
Methodology for capturing environmental, social and economic implications of industrial symbiosis in heavy industrial areasKurup, Biji R. (2007)Industrial operations have been attributed to causing social and environmental problems such as: acid rain; greenhouse gas emissions, air, water and soil pollution; plus health problems to neighbourhood communities. With ...
Entries and exits from homelessness: A dynamic analysis of the relationship between structural conditions and individual characteristicsJohnson, G.; Scutella, R.; Tseng, Y.; Wood, Gavin; Guy, J.; Rosanna, S.; Yi-Ping, T.; Gavin, W. (2015)This report examines the relationship between structural factors, individual characteristics and homelessness. Our interest in the interaction of structural conditions and individual characteristics gives rise to two ...