The DOI matches its Crossref record; 102 of the 102 references it cites were found in a registry or an index.
Power in Top Management Teams: Dimensions, Measurement, and Validation
Abstract
Top managers' power plays a key role in strategic decision making. However, although numerous scholars have recognized its importance, very few have attempted to measure the phenomenon. In this article, I present a set of dimensions measuring top managers' power and suggest a measurement methodology to facilitate empirical inquiry. Data from a group of 1,763 top managers in three industries were used to assess the validity and reliability of the power dimensions in three studies. Results demonstrate strong support for the proposed power dimensions.
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“In the past, management theories emphasized managers' domain expertise, which granted them expert power and status in their organizations (Finkelstein, 1992).”
From Artificial Intelligence and Management: The Automation–Augmentation Paradox (2021) · cites this paper as Finkelstein, 1992
Citations
Cites
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Exchange and Power in Social Life
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External Control of Organizations: Resource Dependence Perspective
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Upper Echelons: The Organization as a Reflection of Its Top Managers
Hambrick, D. C., & Mason, P. A. (1984) · The Academy of Management Review · doi:10.5465/amr.1984.4277628 · Cited by 10,220
The Population Ecology of Organizations
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A Behavioral Theory of the FirmPreprint
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Cited by
Upper Echelons Theory: An Update
Hambrick, D. C. (2007) · Academy of Management Review · doi:10.5465/amr.2007.24345254 · Cited by 4,911
What Makes Teams Work: Group Effectiveness Research from the Shop Floor to the Executive Suite
Cohen, S. G., & Bailey, D. E. (1997) · Journal of Management · doi:10.1177/014920639702300303 · Cited by 3,526
Artificial Intelligence and Management: The Automation–Augmentation Paradox
Raisch, S., & Krakowski, S. (2021) · Academy of Management Review · doi:10.5465/amr.2018.0072 · Cited by 2,755
Amason, A. C. (1996) · Academy of Management Journal · doi:10.2307/256633 · Cited by 2,584
8 Social Hierarchy: The Self‐Reinforcing Nature of Power and Status
Magee, J. C., & Galinsky, A. D. (2008) · Academy of Management Annals · doi:10.5465/19416520802211628 · Cited by 2,385
Metadata
- Authors
- Finkelstein, S.
- Affiliations
- University of Southern California (US)
- Corresponding author
- Finkelstein, S.
- ORCID
- Finkelstein, S.
- Venue
- Academy of Management Journal
- Publisher
- Academy of Management
- Published
- 1992-08-01
- Volume
- 35
- Issue
- 3
- Pages
- 505-538
- ISSN
- 0001-4273 (ISSN-L)
- 1948-0989
- OpenAlex
- W2168930496
- Cited by
- 2,389
- References
- 102
- Citations by year
- 2026: 112 · 2025: 147 · 2024: 153 · 2023: 170 · 2022: 144 · 2021: 144 · 2020: 142 · 2019: 124 · 2018: 117 · 2017: 100 · 2016: 104 · 2015: 109 · 2014: 97 · 2013: 84 · 2012: 87
- FWCI
- 54.45
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Academy of Management Journal (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Social Power and Status Dynamics
- Social Sciences › Psychology › Social Psychology › Team Dynamics and Performance
- Social Sciences › Gender Studies › Gender Diversity and Inequality
- Keywords
- top management teams, managerial power, power measurement, strategic decision-making, measurement validity, reliability statistics, top managers
- MeSH terms
- Workforce, Administrative Personnel, Commerce, Data Collection, Decision Making, Organizational, Humans, Institutional Management Teams, Leadership, Power, Psychological, United States
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- CoChat. (2026). Citation check: Power in Top Management Teams: Dimensions, Measurement, and Validation. https://app.cochat.ai/papers/10.5465/256485
- The paper
- Finkelstein, S. (1992). Power in Top Management Teams: Dimensions, Measurement, and Validation. Academy of Management Journal. https://doi.org/10.5465/256485
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.