The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
Knowledge networks in the Dutch aviation industry: the proximity paradox
Open accessAbstract
The importance of geographical proximity for interaction and knowledge sharing has been discussed extensively in recent years. There is increasing consensus that geographical proximity is just one out of many types of proximities that might be relevant. We argue that proximity may be a crucial driver for agents to connect and exchange knowledge, but too much proximity between agents on any of the dimensions might harm their innovative performance at the same time. In a study on knowledge networks in the Dutch aviation industry, we test this so-called proximity paradox empirically. We found evidence that the proximity paradox holds to a considerable degree. Our study clearly showed that cognitive, social, organizational and geographical proximity were crucial for explaining the knowledge network of the Dutch aviation industry. However, we found strong evidence that too much cognitive proximity lowered firms’ innovative performance, and organizational proximity did not have an effect.
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Cited by
Villani, E., Rasmussen, E., & Grimaldi, R. (2017) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2016.06.004 · Cited by 365
Metadata
- Authors
- Broekel, T., & Boschma, R.
- Venue
- Journal of Economic Geography
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-05-26
- Volume
- 12
- Issue
- 2
- Pages
- 409-433
- ISSN
- 1468-2702 (ISSN-L)
- 1468-2710
- OpenAlex
- W2127674923
- Cited by
- 587
- References
- 53
- FWCI
- 85.90
- Type
- journal article
- Language
- en
- Open access
- green
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- Broekel, T., & Boschma, R. (2012). Knowledge networks in the Dutch aviation industry: the proximity paradox. Journal of Economic Geography. https://doi.org/10.1093/jeg/lbr010
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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.
