Integrating Knowledge Management in the Context of Evidence Based Learning: Two Concept Models Aimed at Facilitating the Assessment and Acquisition of Job Knowledge

Within the field of Human Resource Management (HRM), the role of individual knowledge has received limited research attention despite offering the promise of superior job performance and improved managerial decision-making. In part, this lack of research may be attributed to the difficulty and laboriousness inherent to the adequate and accurate modeling of job relevant knowledge, particularly since such knowledge by definition varies from job to job. Despite this caveat, there is much to be gained from a knowledge based approach to (managing) human resources. The current paper presents two ontology based concepts for modeling job relevant knowledge, namely Meta-Practitioner and Med-Assess. The former focuses on availing to a practitioner audience the evidence that has accumulated in the academic literature, whereas the latter focuses on the facilitation of personnel selection and training in the medical field through a detailed assessment of individual job knowledge and general mental ability. Ultimately both concepts are aimed at knowledge provision to job applicants and incumbents alike. Having discussed the concepts, the paper summarizes the gains that may be expected from their implementation by presenting an integrated framework. The framework focuses on integrating aspects of Knowledge Management (KM) in the context of Evidence Based Learning (EBL) for business organizations. The paper concludes by addressing the challenges that lie ahead, highlighting some of the limitations of this approach and offering suggestions for further research.