Abstract
Knowledge is distributed unevenly through most enterprises. Hence, flows of
knowledge (e.g., across time, people, locations, organizations) are critical to
organizational efficacy and performance under a knowledge-based view of the
firm. However, supported principally by narrative textual theory in the
emerging knowledge management (KM) field, the researcher has difficulty
describing how different kinds of knowledge will flow through various parts of
an organization. This causes difficulty also for predicting the effects of alternate
approaches to dispersing knowledge that ‘clumps’ in various areas. This
problem is also manifest for the KM professional, who lacks clear theory or tools
to anticipate how any particular information technology or other managerial
intervention may enhance or impede specific knowledge flows in the
enterprise. In this expository article, we build upon a steady stream of research
in computational organization theory to develop agent-based models of
knowledge dynamics. This work draws from emerging theory for multidimensional
representation of the knowledge-flow phenomenon, which
enables the dynamics of enterprise knowledge flows to be formalized and
emulated through computational models. This approach provides the means
for knowledge-flow processes to be visualized and analyzed in new ways.
Computational experimentation enables the performance of many alternate
process designs and technological interventions to be compared through
examination of dynamic models, before committing to a specific approach in
practice. We illustrate this research method and modeling environment
through semi-formal representation and agent-based emulation of several
knowledge-flow processes from the domain of software development. We also
outline key directions for the new kinds of KM research and practice elucidated
by this work.
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