CCCI metrics for the measurement of quality of e-service

The growing development in web-based trust and reputation systems in the 21st century will have powerful social and economic impact on all business entities, and will make transparent quality assessment and customer assurance realities in the distributed web-based service oriented environments. The growth in web-based trust and reputation systems will be the foundation for web intelligence in the future. Trust and Reputation systems help capture business intelligence through establishing customer relationships, learning consumer behaviour, capturing market reaction on products and services, disseminating customer feedback, buyers? opinions and end-user recommendations, and revealing dishonest services, unfair trading, biased assessment, discriminatory actions, fraudulent behaviours, and un-true advertising. The continuing development of these technologies will help in the improvement of professional business behaviour, sales, reputation of sellers, providers, products and services. In this paper, we present a new methodology known as CCCI (Correlation, Commitment, Clarity, and Influence) for trustworthiness measure that is used in the Trust and Reputation System. The methodology is based on determining the correlation between the originally committed services and the services actually delivered by a Trusted Agent in a business interaction over the service oriented networks to determine the trustworthiness of the Trusted Agent

ORPMS: An ontology-based real-time project monitoring system in the cloud

Project monitoring plays a crucial role in project management, which is a part of every stage of a project’s life-cycle. Nevertheless, along with the increasing ratio of outsourcing in many companies’ strategic plans, project monitoring has been challenged by geographically dispersed project teams and culturally diverse team members. Furthermore, because of the lack of a uniform standard, data exchange between various project monitoring software becomes an impossible mission. These factors together lead to the issue of ambiguity in project monitoring processes. Ontology is a form of knowledge representation with the purpose of disambiguation. Consequently, in this paper, we propose the framework of an ontology-based real-time project monitoring system (ORPSM), in order to, by means of ontologies, solve the ambiguity issue in project monitoring processes caused by multiple factors. The framework incorporates a series of ontologies for knowledge capture, storage, sharing and term disambiguation in project monitoring processes, and a series of metrics for assisting management of project organizations to better monitor projects. We propose to configure the ORPMS framework in a cloud environment, aiming at providing the project monitoring service to geographically distributed and dynamic project members with great flexibility, scalability and security. A case study is conducted on a prototype of the ORPMS in order to evaluate the framework

Knowledge sharing framework for sustainability of knowledge capital

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