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Cited by 416

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

Perkmann, Markus, Neely, Andy, Walsh, Kathryn·2011·R&D Management

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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Crossref · 10.1111/j.1467-9310.2011.00637.x

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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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CoChat. (2026). Citation check: How should firms evaluate success in university–industry alliances? A performance measurement system. https://app.cochat.ai/papers/10.1111/j.1467-9310.2011.00637.x
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Perkmann, M., Neely, A., & Walsh, K. (2011). How should firms evaluate success in university–industry alliances? A performance measurement system. R&D Management. https://doi.org/10.1111/j.1467-9310.2011.00637.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.