Universities have traditionally provide teaching, research and consultancy supports in the development and advancement of various industries. Such supports are manifested in the tacit knowledge of academic staff with which they accomplish teaching, research, and consulting activities. Articles are the major explicit knowledge resources that improve the tacit knowledge levels of academic staff in order to enhance the performance of teaching, research, and consulting activities. The main challenge that faces academic staff is the difficulty of sharing accurate or valuable articles based on the working contexts due to the large number of articles published in various sources. Consequently, the main aim of this paper is to evaluate the knowledgeability level of articles based on several measurement variables. We identify and analyze the measurement methods and variables using two main data collection methods which are literature review and interview with experts in knowledge management field. We formulate the proposed model in this paper based on several components (i.e. variables, attributes, and formulas). The results show that the proposed model is useful in distinguishing the knowledgeability levels of articles.
|Number of pages||10|
|Journal||Journal of Theoretical and Applied Information Technology|
|Publication status||Published - 10 Jun 2016|
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)