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Cited by 573

The DOI matches its Crossref record; 86 of the 86 references it cites were found in a registry or an index.

R&D Collaborations and Product Innovation*

Un, C. Annique, Cuervo‐Cazurra, Alvaro, Asakawa, Kazuhiro·2010·Journal of Product Innovation Management

Abstract

This paper studies the relative impact on product innovation of research and development (R&D) collaborations with universities, suppliers, customers, and competitors. It argues that each type of R&D collaboration differs in terms of the breadth of new knowledge provided to the firm and in the ease of access of this new knowledge, resulting in a different impact on product innovation. As a result, it proposes that R&D collaborations with universities are likely to have the highest impact on product innovation, followed by R&D collaborations with suppliers, customers, and, finally, competitors. These arguments are tested on the R&D collaborations undertaken by a sample of 781 manufacturing firms during 1998–2002. The tests find that R&D collaborations with suppliers have the highest positive impact on product innovation, followed by collaborations with universities. Surprisingly, R&D collaborations with customers do not appear to affect product innovation, and collaborations with competitors appear to harm it. Moreover, the positive influence of R&D collaborations with universities and suppliers is sustained over the long‐term, but the negative influence of R&D collaborations with competitors is, fortunately, short‐lived. These findings indicate that ease of knowledge access, rather than breadth of knowledge, appears to drive the success of R&D collaborations for product innovation. R&D collaborations with suppliers or universities, which are characterized by relatively easy knowledge access, have a positive influence on product innovation, whereas R&D collaborations with customers or competitors, which are characterized by reduced ease in knowledge access, are not related or are even negatively related to product innovation. Moreover, to achieve product innovation with the help of R&D collaborations, it appears that the collaboration must first have mechanisms in place to facilitate the transfer of knowledge; once these are in place, it is better if the partner has a relatively narrow knowledge base. Thus, while R&D collaborations with both suppliers and universities are positively related to product innovation, the narrow knowledge base provided by collaborations with suppliers appears to have a larger positive impact on product innovation than the wider knowledge base provided by collaborations with universities. These arguments and findings are important and novel. The paper is one of the first to theoretically explain and empirically show that various types of collaborations have a differential influence on product innovation. It goes beyond previous literature by providing a theoretical logic for ranking the likely impact of types of collaborations on product innovation. The study also suggests to managers to carefully select the partners for their firms' R&D collaborations. Collaborations with suppliers appear to be the most promising for product innovation, followed by collaborations with universities, whereas collaborations with competitors may be detrimental to product innovation.

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Crossref · 10.1111/j.1540-5885.2010.00744.x

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Metadata

Authors
Un, C. A., Cuervo‐Cazurra, A., & Asakawa, K.
Venue
Journal of Product Innovation Management
Publisher
Wiley
Published
2010-07-07
Volume
27
Issue
5
Pages
673-689
ISSN
  • 0737-6782 (ISSN-L)
  • 1540-5885
OpenAlex
W3123753940
Cited by
573
References
86
FWCI
74.92
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: R&D Collaborations and Product Innovation*. https://app.cochat.ai/papers/10.1111/j.1540-5885.2010.00744.x
The paper
Un, C. A., Cuervo‐Cazurra, A., & Asakawa, K. (2010). R&D Collaborations and Product Innovation*. Journal of Product Innovation Management. https://doi.org/10.1111/j.1540-5885.2010.00744.x

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.