The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.
Knowledge transfer in university–industry research partnerships: a review
Open accessAbstract
This paper identifies practices that can facilitate knowledge transfer in university–industry (U–I) research partnerships by systematically reviewing extant literature. We aim to contribute to the theoretical development in the field of academic engagement and propose that knowledge transfer provides a valuable perspective. We started our review with identifying barriers and facilitators of knowledge transfer. Extant literature identified knowledge differences and differences in goals resulting from different institutional cultures as important barriers to knowledge transfer. They result in ambiguity, problems with knowledge absorption and difficulties with the application of knowledge. Trust, communication, the use of intermediaries and experience are found as facilitators for knowledge transfer that help to resolve the identified barriers. Our analysis offers practical advice for the management of academic engagement. Finally, we identified questions for future research based on inconsistencies in extant research and open questions we encountered during our analysis.
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Cites
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Metadata
- Authors
- de Wit-de Vries, E., Dolfsma, W. A., van der Windt, H. J., & Gerkema, M. P.
- Venue
- The Journal of Technology Transfer
- Published
- 2018-03-28
- Volume
- 44
- Issue
- 4
- Pages
- 1236-1255
- ISSN
- 0892-9912 (ISSN-L)
- 1573-7047
- OpenAlex
- W2782544489
- Cited by
- 426
- References
- 61
- FWCI
- 39.24
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- de Wit-de Vries, E., Dolfsma, W. A., van der Windt, H. J., & Gerkema, M. P. (2019). Knowledge transfer in university–industry research partnerships: a review. The Journal of Technology Transfer. https://doi.org/10.1007/s10961-018-9660-x
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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.
