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

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  • Sungho Kim
  • Jaideep (Jay) Anand

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.

Suggested Citation

  • Sungho Kim & Jaideep (Jay) Anand, 2018. "Knowledge complexity and the performance of inter‐unit knowledge replication structures," Strategic Management Journal, Wiley Blackwell, vol. 39(7), pages 1959-1989, July.
  • Handle: RePEc:bla:stratm:v:39:y:2018:i:7:p:1959-1989
    DOI: 10.1002/smj.2899
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    Cited by:

    1. Mo Chen & Aseem Kaul & Brian Wu, 2019. "Adaptation across multiple landscapes: Relatedness, complexity, and the long run effects of coordination in diversified firms," Strategic Management Journal, Wiley Blackwell, vol. 40(11), pages 1791-1821, November.
    2. Celo, Sokol & Lehrer, Mark, 2022. "How much lateral collaboration is optimal? Insights from computer simulations of MNEs as complex adaptive systems," Journal of World Business, Elsevier, vol. 57(3).
    3. Jaideep Anand & Gerald McDermott & Ram Mudambi & Rajneesh Narula, 2021. "Innovation in and from emerging economies: New insights and lessons for international business research," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 52(4), pages 545-559, June.
    4. Tom Broekel, 2019. "Using structural diversity to measure the complexity of technologies," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-23, May.
    5. Jie Mi & Zaiyang Xie & Shaojie Lv, 2023. "Star-studded or equalitarianism: how does the distribution of creative stars affect exploration–exploitation balance?," Computational and Mathematical Organization Theory, Springer, vol. 29(2), pages 336-362, June.
    6. Chen, Feiqiong & Liu, Huiqian & Ge, Yuhao, 2021. "How does integration affect industrial innovation through networks in technology-sourcing overseas M&A? A comparison between China and the US," Journal of Business Research, Elsevier, vol. 122(C), pages 281-292.

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