Systems Dynamics and Activity-Based Modeling to Blueprint Generative Knowledge Management Systems

Abstract

The predicted embracing of thriving knowledge societies is increasingly compromised by threatening perceptions of information overload and attention poverty, opportunity divides and career uncertainties. By integrating system dynamics, discrete-event, and agent-based modeling, this paper traces the roots of these symptoms back to their causes of information entropy and structural holes, invisible private and undiscoverable public knowledge which together characterize the sad state of our current knowledge management (KM) and creation practices. Looking forward, it proposes a decentralized generative KM approach that prioritizes the capacity development of autonomous individual knowledge workers not at the expense but as a viable means to foster a fruitful co-evolution with traditional organizational KM systems. As part of an ongoing design science research and prototyping project, this systems thinking and hybrid model perspective complements a succession of prior multidisciplinary publications on the subject.