The DOI matches its Crossref record; 59 of the 59 references it cites were found in a registry or an index.
HRM as a predictor of innovation
Abstract
There is growing evidence available to suggest that HR practice is an important predictor of organisational performance. In this article, we argue that HR practices also have the potential to promote organisational innovation. We describe a longitudinal study of 22 UK manufacturing companies and examine the relationship between such practices and product and technological innovation. Results reveal that training, induction, team working, appraisal and exploratory learning focus are all predictors of innovation. Contingent reward, applied in conjunction with an exploratory learning focus, is positively associated with innovation in technical systems. Furthermore, training, appraisal and induction, combined with exploratory learning focus, explain variation between companies in product and technological innovation above and beyond the main effects observed.
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Cites
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Cited by
Albrecht, S. L., Bakker, A. B., Gruman, J. A., Macey, W. H., & Saks, A. M. (2015) · Journal of Organizational Effectiveness: People and Performance · doi:10.1108/joepp-08-2014-0042 · Cited by 727
Organizational Culture and Innovation: A Meta‐Analytic Review
Büschgens, T., Bausch, A., & Balkin, D. B. (2013) · Journal of Product Innovation Management · doi:10.1111/jpim.12021 · Cited by 649
Carmeli, A., Gelbard, R., & Reiter‐Palmon, R. (2013) · Human Resource Management · doi:10.1002/hrm.21514 · Cited by 450
HRM and innovative work behaviour: A systematic literature review
Bos-Nehles, A., Renkema, M., & Janssen, M. (2017) · Personnel Review · doi:10.1108/pr-09-2016-0257 · Cited by 430
Strategic Human Resource Practices and Product Innovation
Beugelsdijk, S. (2008) · Organization Studies · doi:10.1177/0170840608090530 · Cited by 403
Metadata
- Authors
- Shipton, H., West, M. A., Dawson, J., Birdi, K., & Patterson, M.
- Venue
- Human Resource Management Journal
- Publisher
- Wiley
- Published
- 2006-01
- Volume
- 16
- Issue
- 1
- Pages
- 3-27
- ISSN
- 0954-5395 (ISSN-L)
- 1748-8583
- OpenAlex
- W2162618845
- Cited by
- 498
- References
- 59
- FWCI
- 25.62
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
