The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Knowledge Flows Within Multinational Corporations: Explaining Subsidiary Isolation and Its Performance Implications
Open accessAbstract
Applying a new theoretical and empirical approach to intrafirm knowledge transfers, this paper provides some initial insight to the little-researched phenomenon of why some subsidiaries are isolated from knowledge-transfer activities within the multinational corporation (MNC). Knowledge transfer is framed as a problemistic search process initiated by the recipient unit. We show that knowledge flows from units that are perceived to be highly capable to units that perceive themselves to be highly capable. Knowledge flows are also associated with existing levels of communication and reciprocity. Taken together, these findings suggest that knowledge transfers in MNCs typically occur between highly capable members of an “in crowd,” and the isolated minority rarely, if ever, engages in knowledge-sharing activities. Finally, we show that the isolated minority underperforms other subsidiaries, suggesting the possibility of a “liability of internal isolation.”
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Rugman, A., Verbeke, A., & Yuan, W. (2011) · Journal of Management Studies · doi:10.1111/j.1467-6486.2010.00969.x · Cited by 299
The world economy will need even more globalization in the post-pandemic 2021 decade
Contractor, F. J. (2022) · Journal of International Business Studies · doi:10.1057/s41267-020-00394-y · Cited by 225
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Metadata
- Authors
- Monteiro, L. F., Arvidsson, N., & Birkinshaw, J.
- Venue
- Organization Science
- Published
- 2008-02
- Volume
- 19
- Issue
- 1
- Pages
- 90-107
- ISSN
- 1047-7039 (ISSN-L)
- 1526-5455
- OpenAlex
- W2127189704
- Cited by
- 458
- References
- 15
- FWCI
- 43.01
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
