The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
The role of multilevel synergistic interplay among team mastery climate, knowledge hiding, and job characteristics in stimulating innovative work behavior
Open accessAbstract
This study investigates the multilevel interplay among team‐level, job‐related, and individual characteristics in stimulating employees' innovative work behavior (IWB) based on the theoretical frameworks of achievement goal theory (AGT) and job characteristics theory (JCT). A multilevel two‐source study of 240 employees and their 34 direct supervisors in two medium‐sized Slovenian companies revealed significant two‐ and three‐way interactions, where a mastery climate, task interdependence, and decision autonomy moderated the relationship between knowledge hiding and IWB. When employees hide knowledge, a team mastery climate only facilitates high levels of IWB if accompanied by either high task interdependence or high decision autonomy. In the absence of one of these job characteristics, knowledge hiding prevents higher levels of IWB even in the case of strong team mastery climate. The results suggest that multiple job design antecedents are necessary to neutralize the negative influence of knowledge hiding on micro‐innovation processes within organizations.
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Cited by
Bunjak, A., Černe, M., & Popovič, A. (2021) · Information & Management · doi:10.1016/j.im.2021.103533 · Cited by 127
Self-citation
Metadata
- Authors
- Černe, M., Hernaus, T., Dysvik, A., & Škerlavaj, M.
- Venue
- Human Resource Management Journal
- Publisher
- Wiley
- Published
- 2017-04
- Volume
- 27
- Issue
- 2
- Pages
- 281-299
- ISSN
- 0954-5395 (ISSN-L)
- 1748-8583
- OpenAlex
- W2604988970
- Cited by
- 351
- References
- 7
- FWCI
- 53.02
- Type
- journal article
- Language
- en
- Open access
- green
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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.
