Improving the Knowledge Management Processes Through a Multi-agent Knowledge Audit Framework

• Main Authors: Mostafa S.A., Gunasekaran S.S., Khaleefah S.H., Ahmad M.S., Mohammed M.A., Hassan M.H., Jubair M.A.
• Other Authors: 37036085800
• Format: Conference Paper
• Published: Springer Science and Business Media Deutschland GmbH 2023

Recently, intelligent algorithms are deployed for dynamic decision-making in Knowledge Audit (KA) frameworks to improve Knowledge Management (KM) in organizations. This paper attempts to advance a viewpoint on the importance of investigating KA in business units. Subsequently, it proposes a Multi-agent Knowledge Audit (MAKA) framework to assist decision-making executives. The MAKA framework�s focal point is on examining the speculations made on the appropriation of the KA System and Knowledge Inventory in organizations. The examination encompasses the functions of KA in the establishment of utilization and gains. However, its application is highly dependent on the investigated system. This work considers KA from the viewpoint of getting at the effect of the hierarchical change in an organization. As a major aspect of its examination, so as to achieve objectivity, the investigation has come up with a structure for expense gains examination. We implement the framework in a case study of the Information Communication Technology (ICT), Information Technology, and Multimedia Services (ITMS) units of Universiti Tenaga National (UNITEN). The MAKA framework's completed examination results propose some recommendations that generally need to be looked into while implementing ITMS�s KM advancements. The proposals extensively focus on changing a hierarchical standpoint and conducting a far-reaching capital gains investigation. � 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.