The role of different levels of leadership in predicting self- and collective efficacy: Evidence for discontinuity.
Abstract
This study identified potential discontinuities in the antecedents of efficacy beliefs across levels of analysis, with a particular focus on the role of leadership climate at different organizational levels. Random coefficient modeling analyses conducted on data collected from 2,585 soldiers in 86 combat units confirmed that soldiers' experience, role clarity, and psychological strain predicted self-efficacy to a greater extent than did leadership climate. Also, leadership climate at a higher organizational level related to self-efficacy through role clarity, whereas leadership climate at a lower organizational level related to self-efficacy through psychological strain. Group-level analyses identified leadership climate at a higher organizational level as the strongest predictor of collective efficacy. Theoretical and practical implications and directions for future research are discussed.
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Cited by (22)
- Enhancing the Effectiveness of Work Groups and TeamsKozlowski, Steve W.J., Ilgen, Daniel R. · 2006 · Psychological Science in the Public Interest
- How to SHIFT Consumer Behaviors to be More Sustainable: A Literature Review and Guiding FrameworkWhite, Katherine, Habib, Rishad, Hardisty, David J. · 2019 · Journal of Marketing
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
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- CoChat. (2026). Citation check: The role of different levels of leadership in predicting self- and collective efficacy: Evidence for discontinuity. https://app.cochat.ai/papers/10.1037//0021-9010.87.3.549
- The paper
- Chen, G., & Bliese, P. D. (2002). The role of different levels of leadership in predicting self- and collective efficacy: Evidence for discontinuity. Journal of Applied Psychology. https://doi.org/10.1037//0021-9010.87.3.549
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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.