The DOI matches its Crossref record; 63 of the 63 references it cites were found in a registry or an index.
How should firms evaluate success in university–industry alliances? A performance measurement system
Abstract
While firms increasingly engage in formal alliances with universities, there is a lack of tools to assess the outcomes of such collaborations. We propose a performance measurement system for university–industry alliances. We derive a success map from existing research on university–industry relations, indicating the causal relationships underpinning successful alliances. The success map distinguishes between different process stages, including inputs, in‐process activities, outputs and impacts. We discuss specific measures for each of these stages, and how they should be deployed. The resulting framework includes both prospective and retrospective measures and subjective and objective measures. It provides research and development managers with a tool for assessing university–industry alliances that is prospective, reliable and multi‐dimensional.
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Cites
Exploration and Exploitation in Organizational Learning
March, J. G. (1991) · Organization Science · doi:10.1287/orsc.2.1.71 · Cited by 21,942 · cited 1×
“exploitation to exploration, provides a way of differentiating between types of impact (March, 1991).”
The balanced scorecard : measures that drive performance
Caplan, R. S. (1992) · Harvard business review · Cited by 12,085
Handbook of Industrial and Organizational Psychology.
Hammer, T. H., Anderson, J., Gurdon, M., Jick, T., Petit, A., Stern, R., Schwartz, H., Vardi, Y., & Dunnette, M. D. (1977) · Administrative Science Quarterly · doi:10.2307/2391755 · Cited by 11,945
Economic Welfare and the Allocation of Resources for Invention
Arrow, K. J. (1962) · The Rate and Direction of Inventive Activity · doi:10.1515/9781400879762-024 · Cited by 8,635
Interorganizational Collaboration and the Locus of Innovation: Networks of Learning in Biotechnology
Powell, W. W., Koput, K. W., & Smith-Doerr, L. (1996) · Administrative Science Quarterly · doi:10.2307/2393988 · Cited by 8,499
(1992) · PubMed · Cited by 7,979
Teece, D. J. (1986) · Research Policy · doi:10.1016/0048-7333(86)90027-2 · Cited by 7,842
Teece, D. (1993) · Research Policy · doi:10.1016/0048-7333(93)90063-n · Cited by 7,242
The Matthew Effect in Science: The reward and communication systems of science are considered.
Merton, R. K. (1968) · Science · doi:10.1126/science.159.3810.56 · Cited by 6,720 · cited 1×
“At the core of the science system is the ‘Matthew principle’, whereby the most successful researchers are able to raise the most resources, which, in turn, enables them to generate even more research outputs (Merton, 1968).”
(1968) · PubMed · Cited by 4,803
Cited by
What makes industry–university collaboration succeed? A systematic review of the literature
Rybnicek, R., & Königsgruber, R. (2019) · Journal of Business Economics · doi:10.1007/s11573-018-0916-6 · Cited by 404
Metadata
- Authors
- Perkmann, M., Neely, A., & Walsh, K.
- Venue
- R&D Management
- Publisher
- Wiley
- Published
- 2011-02-22
- Volume
- 41
- Issue
- 2
- Pages
- 202-216
- ISSN
- 0033-6807 (ISSN-L)
- 1467-9310
- OpenAlex
- W1539262115
- Cited by
- 416
- References
- 63
- FWCI
- 22.29
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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