Managing knowledge assets within organizations role of incentives and information systems /

by Zhang, Zuopeng.

Incentives and information systems are two major enablers for managing organizational knowledge assets. Prior research in knowledge management focuses either on managerial or technical perspectives, independently. On the one hand, various studies investigate the knowledge management strategies and influential factors for knowledge diffusion. On the other hand, research is abundant in the construction and mechanisms of knowledge management systems. Our research studies the joint role of incentives and information systems in facilitating knowledge sharing and learning within organizations in three closely related essays. The first study demonstrates that incentive rewards for knowledge sharing and learning can be offered in linear proportion to the sharing and learning amounts to achieve knowledge-sharing(learning) alignment, full-knowledge sharing, and truthful reporting of knowledge levels. In addition, the adoption of appropriate knowledgetransfer policies, either mandatory learning(ML) or voluntary learning(VL), depends on the level of information systems. This framework is then extended to the analysis about how to properly allocate internal knowledge assets so that knowledge discoveries can be successfully created, retained, and disseminated to improve organizational productivity, maximizing profits. The equilibria among knowledge pioneers who engage in knowledge innovation are investigated under two incentive policies: individual winner reward(IWR) and aggregate team reward(ATR). Information systems are found to assume the critical role of facilitating knowledge innovation and increasing organizational profitability in the knowledge creation, retention, and diffusion processes. The third model examines the design of reward structures for participants in the internal knowledge market as well as its IT support in diffusing organizational knowledge. The knowledge providers’ signalling strategy and the firm’s optimal design of reward structures are shown based on different types of knowledge recipients. iii