|InterJournal Complex Systems, 1063
|Manuscript Number: |
Submission Date: 2004
|Permeable Boundaries in Organizational Learning: Computational Modeling Explorations|
The nature of the organizational boundary is investigated in the context of organizational learning. Using the Organizational Learning Systems Model (OLSM) (Schwandt, 1997) and building upon computational organizational theory (Carley & Prietula, 1994b), we precisely define boundary permeability for an organization with respect to the amount of new information obtained in the environment and the number of agent interactions inside the organization’s boundary. We then decompose boundary permeability into constituent parts: information-gathering efficiency, search intensity, and knowledge diffusion effectiveness. Hypotheses are developed about the relationship between these factors and the survival of agents within the organization. These hypotheses are tested using data from 5,500 artificial organizations that were allowed to randomly evolve under controlled conditions. We find strong support for the usefulness of boundary permeability as a predictor of organizational learning and agents’ survival and suggest ways to operationalize this construct in future laboratory and field studies.
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