The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Beyond Team Types and Taxonomies: A Dimensional Scaling Conceptualization for Team Description
Open accessAbstract
Research on teams has prompted the development of many alternative taxonomies but little consensus on how to differentiate team types. We show that there is greater consensus on the underlying dimensions differentiating teams than there is on how to use those dimensions to generate categorical team types. We leverage this literature to create a conceptual framework for differentiating teams that relies on a dimensional scaling approach with three underlying constructs: skill differentiation, authority differentiation, and temporal stability.
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Cites
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Self-citationDisrupted Routines: Team Learning and New Technology Implementation in Hospitals
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Cited by
A meta-analysis of shared leadership and team effectiveness
Wang, D., Waldman, D. A., & Zhang, Z. (2014) · Journal of Applied Psychology · doi:10.1037/a0034531 · Cited by 731
Challenges and barriers in virtual teams: a literature review
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Trust and team performance: A meta-analysis of main effects, moderators, and covariates.
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A century of work teams in the Journal of Applied Psychology.
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Self-citationUnderstanding and shaping the future of work with self-determination theory
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Metadata
- Authors
- Hollenbeck, J. R., Beersma, B., & Schouten, M. E.
- Venue
- Academy of Management Review
- Publisher
- Academy of Management
- Published
- 2012-01
- Volume
- 37
- Issue
- 1
- Pages
- 82-106
- ISSN
- 0363-7425 (ISSN-L)
- 1930-3807
- OpenAlex
- W2127908252
- Cited by
- 444
- References
- 14
- FWCI
- 23.19
- Type
- journal article
- Language
- en
- Open access
- green
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- Hollenbeck, J. R., Beersma, B., & Schouten, M. E. (2012). Beyond Team Types and Taxonomies: A Dimensional Scaling Conceptualization for Team Description. Academy of Management Review. https://doi.org/10.5465/amr.2010.0181
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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.
