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Entrepreneurial Team Composition Characteristics and New Venture Performance: A Meta–Analysis
Abstract
Upper echelon theory highlights the importance of top management teams in large and established firms; however, effects are not always clear outside of this context. Due to the unique nature of new ventures, the composition of entrepreneurial teams and its effects on performance is worthy of investigation. Accordingly, we meta–analyze the effect of three characteristics of entrepreneurial team composition (i.e., aggregated, heterogeneity, team size) on new venture performance. Our meta–analysis, which includes 55 empirical samples and 8,892 observations, finds significant and unique effects of entrepreneurial team characteristics on new ventures. Based on our findings, we derive avenues for future research.
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Metadata
- Authors
- Jin, L., Madison, K., Kraiczy, N. D., Kellermanns, F. W., Crook, T. R., & Xi, J.
- Venue
- Entrepreneurship Theory and Practice
- Publisher
- SAGE Publications
- Published
- 2017-09
- Volume
- 41
- Issue
- 5
- Pages
- 743-771
- ISSN
- 1042-2587 (ISSN-L)
- 1540-6520
- OpenAlex
- W2345504508
- Cited by
- 339
- References
- 134
- FWCI
- 29.69
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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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.