Knowledge complexity and the performance of inter‐unit knowledge replication structures

Sungho Kim and Jaideep (Jay) Anand

Strategic Management Journal, 2018, vol. 39, issue 7, 1959-1989

Abstract: Research Summary: Intra‐firm replication of complex knowledge is difficult yet critical to firm growth and the exploitation of competitive advantage. Inter‐unit organizational structures can facilitate the replication of complex knowledge between a source unit and a recipient unit. This study examines how inter‐unit organizational structures perform at different levels of knowledge complexity. We dimensionalize the patterns of information‐processing interactions according to three specific factors: the degree of inter‐unit connectivity, the extent of mirroring between the structure and the knowledge configuration, and coordination mechanisms. Simulation analyses offer a set of novel findings on how the information‐processing and bounded‐rationality concerns of organizational design impact the replication performance of the structures. We derive optimal structures for different levels of knowledge complexity, and articulate their theoretical and practical implications. Managerial Summary: The growth of firms often involves redeployment of their complex knowledge to new subunits or markets, in the context of acquisitions, alliances, or the creation of multinational subsidiaries. Complex knowledge is difficult to imitate, and thus, serves as a source of competitive advantage. However, it is also challenging to replicate within a firm, which limits firms’ ability to redeploy their capabilities in pursuit of new opportunities. A proper design of inter‐unit structures can facilitate the replication of complex knowledge between intra‐firm units. This study examines how the design of inter‐unit structures affects the outcome of this replication. Our results suggest that managers in charge of redeployment efforts should be mindful of the connectivity among units, coordination mechanisms, information overload, and the level of knowledge complexity.

Date: 2018
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