The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Value of Strong Ties to Disconnected Others: Examining Knowledge Creation in Biomedicine
Abstract
Knowledge creation requires the combination and exchange of diverse and overlapping knowledge inputs as individuals interact with exchange partners to create new knowledge. In this study, we examine knowledge creation among university research scientists as a function of their professional (ego) networks—those others with whom they collaborate for the purpose of creating new knowledge. We propose that knowledge creation relies, in part, on two attributes of a researcher's professional network structure—average tie strength and ego network density—and we provide insights into how these attributes jointly affect knowledge creation. Our study of over 7,300 scientific publications by 177 research scientists working with more than 14,000 others over an 11-year period provides evidence that the relationship between a research scientist's professional network and knowledge creation depends on both ego network density and average tie strength. Our evidence suggests that both attributes affect knowledge creation. Moreover, average tie strength interacts with density to affect knowledge creation such that researchers who maintain mostly strong ties with research collaborators who themselves comprise a sparse network have the highest levels of new knowledge creation.
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Citations
Cites
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“This idea is consistent with Nonaka (1994), who contended that overlapping knowledge is essential at the development stage of knowledge creation as it bridges knowledge sets between exchange partners, forming a critical precondition for knowledge creation.”
BackgroundToward a knowledge-based theory of the firm
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Hansen, M. T. (1999) · Administrative Science Quarterly · doi:10.2307/2667032 · Cited by 5,809 · cited 8×
“Hansen (1999) found that weak ties transfer codified knowledge efficiently and accelerate project completion when the needed knowledge is not complex.”
BackgroundMethodInfluentialStructural Holes and Good Ideas
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“Network density provides insights about the resources a researcher might obtain through exchange partners (Bian 2003, Lin 2001) as well as potential constraints that the network might impose (Coleman 1988, Gargiulo and Benassi 1999, Portes and Sensenbrenner 1993).”
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Cited by
Organizational Learning: From Experience to Knowledge
Argote, L., & Miron-Spektor, E. (2011) · Organization Science · doi:10.1287/orsc.1100.0621 · Cited by 1,917
From creativity to innovation: The social network drivers of the four phases of the idea journey
Perry-Smith, J. E., & Mannucci, P. V. (2017) · Academy of Management Review · doi:10.5465/amr.2014.0462 · Cited by 1,121
Guan, J., & Liu, N. (2016) · Research Policy · doi:10.1016/j.respol.2015.08.002 · Cited by 734
The Role of Ego Networks in Manufacturing Joint Venture Formations
Carnovale, S., & Yeniyurt, S. (2014) · Journal of Supply Chain Management · doi:10.1111/jscm.12015 · Cited by 70
When does brokerage matter? Citation impact of research teams in an emerging academic field
Collet, F., Robertson, D. A., & Lup, D. (2014) · Strategic Organization · doi:10.1177/1476127014530124 · Cited by 32
Metadata
- Authors
- McFadyen, M. A., Semadeni, M., & Cannella, A. A.
- Venue
- Organization Science
- Published
- 2009-06
- Volume
- 20
- Issue
- 3
- Pages
- 552-564
- ISSN
- 1047-7039 (ISSN-L)
- 1526-5455
- OpenAlex
- W2101917504
- Cited by
- 299
- References
- 13
- FWCI
- 33.70
- Type
- journal article
- Language
- en
- Open access
- closed
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- McFadyen, M. A., Semadeni, M., & Cannella, A. A. (2009). Value of Strong Ties to Disconnected Others: Examining Knowledge Creation in Biomedicine. Organization Science. https://doi.org/10.1287/orsc.1080.0388
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.