Organizations and universities alike depend on the collection of the data pertaining to the purpose (Curtis, 1999) of the domain in which they operate. Internally, each functional part of the organization works with data collected from the different types of systems used (Laudon & Laudon, 2000). Organizations, therefore, use technology to collect and store data (Whitten, Bentley, & Barlow, 1994) to be processed by the rules formulated to produce valuable information (Connelly, Begg & Strachan, 1996) and eventually knowledge. Universities, too, collect data, processes them, and endow them with relevance and importance (Drucker, 1993). Most organizations use knowledge, for example, regarding their target audience, to gain a competitive advantage. Knowledge and knowledge workers are theoretically the “products” produced by universities. However, they face the same dilemma as the majority of firms, that is, too much data and information but not enough knowledge. Information can be described as explicit knowledge, the significance of which is that information has meaning and it is clearly understood. Knowledge is regarded as volumes of relevant information but, importantly, in addition to experience (tacit knowledge) in the form of an expert (Avison & Fitzgerald, 1995). An expert, to be effective, must use extensively both formal (quantitative) and informal (qualitative) information in decision making. Knowledge is regarded as a strategic asset and therefore the creation of which is often an enterprise-wide goal. Alavi and Leidner (1999) argued that the importance of knowledge is based on the hypothesis that the barriers to the transfer and duplication of knowledge award it with enormous strategic importance. Universities, with the technological capability necessary, are developing systems that can collect and manage knowledge. The combination or integration along with the capability to combine an expert’s experience in the form of a system is regarded as a strategic tool. Systems capable of combining both explicit and tacit knowledge are referred to as knowledge management systems (KMSs). Research in this area is not very detailed due to the fact that organizations, not universities, have only been implementing the systems in the last few years. These systems are used to acquire and manage knowledge and distribute it among the different functional units as well as with any external collaborating groups. The idea of disseminating knowledge is not a new concept, be it in education or in industry. Like the classroom, the traditional approach, such as paper-based knowledge sharing, and the virtual are used, depending on factors such as the number of students or the type of decisions to be made. An organization creates a knowledge base to reduce the level of experience needed by managers and to improve the effectiveness of their decisions (Peterson & Davie, 1996). Industry invests an enormous amount of capital in the training of its employees and therefore in the creation of so called “experts in the field”; a “true” knowledge base will allow the acquisition of the experience of experts to reduce the loss of investment should the employee leave (Curtis, 1999).