Resumen
This paper presents a conceptual framework for use, by organizational researchers, knowledge management practitioners and business analysts, as a guide to building Knowledge Management (KM) models. This is accomplished through a careful selection of ten prominent KM models which have been discussed critically and used to deepen the theoretical understanding of KM implementation and development. A critical review of ten KM models offers practitioners, as well as researchers, an examination of the ontological and epistemological backgrounds and origins of existing models? in order to highlight the required components for composing effective KM models. There is limited research supporting the utilization, adaptation or even adoption of KM models that can assist managers seeking a competitive advantage through the implementation of KM processes. Authors of existing KM models claim to provide holistic KM models but when referring back to the central meaning of knowledge and management concepts those models do not generate a thorough coverage of the required characteristics and components. This paper has critically investigated ten widely acknowledged KM models but recognizes that there is a plethora of KM models emerging which have varied foci. The conceptual review of KM models is not an empirical investigation, moreover, a critical analysis that presents a conceptual framework for KM model building. In carrying out this research study, the paper presents the shortfalls of this theoretical research approach but nevertheless, the proposed conceptual framework is envisaged as having value to both practitioners and researchers. This paper sheds light on a series of concerns related to existing KM models, their origins, constructs, and contextualization. For organizational researchers, knowledge management practitioners and business analysts this research study elaborates on issues related to validity, applicability, and generalizability of KM models and defines a set of criteria for KM model building. The paper also impacts on the science of KM presenting perspectives, scope, and contexts in which knowledge is processed.