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Cited by 351

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Gender diversity within R&D teams: Its impact on radicalness of innovation

Díaz-García, Cristina, González-Moreno, Angela, Jose Sáez-Martínez, Francisco·2013·Innovation

Abstract

Literature on diversity in organisations is limited and even fewer studies investigate its impact on innovation. Therefore, the aim of this research is to study how gender diversity within R&D teams, among other factors, impacts innovation, drawing on data from an innovation survey in Spain. Our findings support the assertion that gender diversity within R&D teams generates certain dynamics that foster novel solutions leading to radical innovation. The results indicate that gender diversity is positively related to radical innovation. However it does not promote incremental innovation in the same way. The positive relation occurs under particular conditions of the task (a higher degree of novelty), as the two types of innovation might require different skills for their effective performance. These results have several implications for academics, politicians and practitioners.

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Metadata

Authors
Díaz-García, C., González-Moreno, A., & Jose Sáez-Martínez, F.
Venue
Innovation
Published
2013-06
Volume
15
Issue
2
Pages
149-160
ISSN
  • 1447-9338 (ISSN-L)
  • 2204-0226
OpenAlex
W4241696707
Cited by
351
References
3
FWCI
10.39
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Gender diversity within R&D teams: Its impact on radicalness of innovation. https://app.cochat.ai/papers/10.5172/impp.2013.15.2.149
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Díaz-García, C., González-Moreno, A., & Jose Sáez-Martínez, F. (2013). Gender diversity within R&D teams: Its impact on radicalness of innovation. Innovation. https://doi.org/10.5172/impp.2013.15.2.149

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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.