Skip to content Skip to navigation

Dynamic Models of Knowledge-Flow Dynamics

TitleDynamic Models of Knowledge-Flow Dynamics
Publication TypeWorking Paper
Year of Publication2002
AuthorsNissen, M, Levitt, RE
IssueWP076
Date Published11/2002
PublisherCIFE
Publication Languageeng
Keywordsartificial intelligence, Center for Integrated Facility Engineering, CIFE, Computational Organization Theory, Knowledge Flow, Knowledge Management, Knowledge Representation, Organizational Learning, Simulation, Software, Stanford University
AbstractKnowledge is unevenly distributed through most enterprises, so knowledge flow (e.g., across time, location, organization) is critical to organizational efficacy and performance under a knowledge-based view of the firm. Although knowledge flow is an inherently dynamic concept, however, the corresponding phenomenon remains poorly understood, and extant approaches to its modeling and description (e.g., natural language texts and figures) are fundamentally static and largely ambiguous. In this research, we build upon emerging theory for multidimensional conceptualization of the knowledge-flow phenomenon to develop dynamic models of knowledge-flow dynamics. Drawing from recent advances in computational organization theory, we describe a research approach and modeling environment that enables the dynamics of enterprise knowledge flows to be formalized through computational models. Particularly when compared to extant descriptive theory articulated through natural language, such formal models are considerably less ambiguous, more reliable and quite explicit. We illustrate this research approach and modeling environment through formal representation and simulation of several knowledge-flow processes from the domain of software development. When used in conjunction with current theory, the new insight into and understanding of knowledge-flow dynamics revealed through this research is compelling and represents a contribution to the information systems literature. The article closes with key new directions for the kind of research elucidated by this work.
URLhttps://purl.stanford.edu/kp176bm2488
PDF Linkhttps://stacks.stanford.edu/file/druid:kp176bm2488/WP076.pdf
Citation Key918