Signifying ontology complexity for knowledge sharing

Ontologies are used in widespread application areas particularly to provide a shared semantically domain knowledge in a declarative formalism for intelligent reasoning. Even ontology enables knowledge sharing however complexity of knowledge being conceptualized in the ontology is critical to the success of knowledge sharing efforts. Other factor like trust in the source of knowledge can also affect knowledge transfer. In this paper we propose metrics to measure the complexity of ontology for knowledge sharing. We have chosen Software Engineering Ontology as our case study

Knowledge and trust issues for intellectual capital measurement

Trust in intellectual capital has become an increasingly important factor. External trust such as trust between business and customer(B to B and B to C), business and supplier, and trust between customer to customer, also internal trust such as trust between employees vertically and horizontally is seen as crucial to the expansion of intellectual capital in a business. Although there is an interest in measuring and reporting the relationship between intellectual capital and business performance and some measurement models have been proposed, in most of these models such as BSC, Skandia, IC audit, Intangible asset monitor, MVA and EVA, Knowledge and an asset produced by the knowledge are assumed as the fundamental sources of wealth and the role of trust has not been investigated. The concept of trust indicates business component faith to the shared knowledge between them. The key to success in business is obtaining and maintaining the trust (internal and external) of the participants in the markets. Trust also affects on knowledge sharing and in order to increase knowledge sharing, the participants must have good faith to the shared knowledge resources. Otherwise, participants are more likely to share knowledge with the business competitors. In this paper, we extend the value of intellectual capital from the knowledge to ?knowledge and trust? as the two important variables in intellectual capital. Sustainable business performance will be discussed and demonstrated the platform of this sustainability can be created by the knowledge and trust.Additionally, most current intellectual capital measurement models are assessing the business performance in static environment. However, the intellectual assets consist mainly of dynamic elements. Knowledge and trust are dynamic elements and we should discuss them in a dynamic environment and in a specific time slot. Therefore, in this paper variables are analysed in dynamic modelling systems. Also, in current business performance models most of the data resources are internal where external data resources are also important. We point out in this paper that improving external variables such as trust within customers can affect on business performance

Ontology based approach in knowledge sharing measurement

For many years, physical asset indicators were the main evidence of an organization’s successful performance. However, the situation has changed following the revolution of information technology in the knowledge-based economy and in the new ideas in economy; knowledge assets are a critical strategic resource in economy. Knowledge management [KM] tools have become very important and in order to gain a competitive advantage, it is necessary to create, store, share and apply knowledge. Knowledge sharing is one of the key issues in knowledge management. One of the main challenges facing pioneer firms is to provide an effective strategy to exchange knowledge formally or informally. In this paper, we will discuss the effectiveness of knowledge sharing and our proposal for an effective knowledge sharing strategy. Based on a review of knowledge sharing literature, we will focus more on the trust and knowledge contexts as key issues in knowledge sharing.Trust is the most important issue when creating a relationship, knowledge sharing and partnership. Moreover, there are a number of forms that trust can take in these relationships and the most regularly cited forms are competence and benevolence trust. In this paper, we will explore these two forms of trust and will examine their role in knowledge sharing and how they can be defined and measured. On the other hand, we will apply ontologies to explore the knowledge context. Ontologies are used in widespread application areas particularly to provide a semantically shared domain knowledge in a declarative formalism for intelligent reasoning. Even ontology enables knowledge sharing; however, the complexity of knowledge being conceptualized in the ontology is critical to the success of knowledge sharing efforts. Other factors like trust in the source of knowledge can also affect knowledge transfer. In this paper, we propose metrics to measure the complexity of ontology for knowledge sharing. Finally, the effectiveness of our proposed knowledge sharing methodology is presented both using a fuzzy-inference engine and a crisp system

Fuzzy logic based model to measure knowledge sharing

Nowadays, trust is one of the most important variables in business. Lack of trust has a direct impact on business components confidence, trustworthiness can create value and leads business to obtain high market share. Trust is also the most important variable in knowledge sharing on the basis of the knowledge context. Different kinds of trust requires in knowledge sharing. Complexity and structured level of knowledge are the two important factors in knowledge classification. In this paper competence-based trust and benevolence-based trust will be discussed and knowledge sharing will be compared in different knowledge context and in different trust types. Effective knowledge sharing can be encouraged by improving the different types of trust. It is essential we discuss about trust definition and trust measurement in knowledge sharing

Knowledge sharing effectiveness measurement

Knowledge would be considered as important element in knowledge-based economy and it makes a strong competitive advantage in dynamic business environment. In knowledge management, knowledge sharing is the most critical elements of effective knowledge processing. Several studies have been done to explain why people share knowledge and some of them have been mentioned in this paper. The next issue is how knowledge sharing can be improved and how it can be measured. Different models from different view points such as social and psychological aspect or economic benefit aspect have been proposed to analyse and measure knowledge sharing effectiveness. In this paper, we will review some of the main models in knowledge sharing effectiveness and will explain a new method to measure knowledge sharing effectiveness among individuals

A model based on Game theory to measure the effect of sustainable development variables

Sustainable development is becoming one of the main challenges in human development. The notion of coordinating actions between economy, society and environment in order to optimise sustainability of ecosystems is the aim of this paper. Traditionally, relations between economy, society and the environment are win-lose relations; however, to achieve sustainable development they should change to win-win relations. In this paper, we propose a game-theory approach to show the lack of balance between the parts of sustainable development. We present a mathematical model in order to change uncooperative behaviour. Ontology, a particular type of knowledge based technology, is used to define the variables affected on the relations. Ontology helps to understand how those variables affect an economy, society and environment. Generally speaking, ontology is used to explicitly express how sustainable variables are defined in economy, society and environment. Due to the qualitative entity of some of the variables, fuzzy logic is used to measure the variables and TOPSIS methodology is anticipated as a methodology to find optimum answers. It is a suitable way to predict the effect of some solutions, such as emission trading, on the environment, and society as well as the economy. The sensitivity of changes in variables can be analysed. We propose a methodology on the basis of the Game theory to measure sustainability and effects of changing each variable in the relations between sustainable development actors to other variables