A Hierarchical Model for Knowledge Management

Knowledge management (KM) is a multidisciplinary subject, with contributions from such disciplines as information systems (IS) and information technology (IT), strategic management, organizational theory, human-resource management, education science, psychology, cognitive science, and artificial intelligence. In order to take full advantage of these various contributions, the necessity of a multidisciplinary approach to KM is currently widely acknowledged, particularly in the IS and IT, management, and artificial-intelligence communities (Alavi & Leidner, 2001; Dieng-Kuntz et al., 2001; Grover & Davenport, 2001; Nonaka & Konno, 1998; O’Leary & Studer, 2001; Zacklad & Grundstein, 2001). Several KM models have been proposed in the literature. These models reflect the diversity of disciplines contributing to KM. By describing KM concepts and investigating their relationships, they provide a useful conceptual tool for KM research and practice. However, they suffer from three major limitations. • They are often incomplete. This may be intentional (in the case of models focusing on a specific aspect of KM) or reflect disproportionate emphasis on one of the disciplines contributing to KM, for example, IS and IT. • They are inappropriate for navigating between abstraction levels of KM topics (“drill down” or “drill up”). • They do not provide a structure for the quantitative assessment of KM research and/or practice (e.g., for auditing KM practice in a specific company).