Cited by 556Job Satisfaction and Organizational BehaviorLabor Movements and UnionsEmployee Performance and Leadership

I warn you because I like you: Voice behavior, employee identifications, and transformational leadership

Liu, Wu, Zhu, Renhong, Yang, Yongkang·2010·The Leadership Quarterly

Integrity signals

Registry

Crossref · 10.1016/j.leaqua.2009.10.014

Cites

92 of 92 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

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Authors
Liu, W., Zhu, R., & Yang, Y.
Affiliations
  • Hong Kong Polytechnic University (HK)
  • Sun Yat-sen University (CN)
  • Fudan University (CN)
Corresponding author
Liu, Wu
Venue
The Leadership Quarterly
Publisher
Elsevier BV
Published
2010-02
Volume
21
Issue
1
Pages
189-202
ISSN
1048-9843 (ISSN-L)
OpenAlex
W2150872720
Cited by
555
References
92
Citations by year
2026: 22 · 2025: 31 · 2024: 43 · 2023: 42 · 2022: 46 · 2021: 57 · 2020: 54 · 2019: 53 · 2018: 44 · 2017: 32 · 2016: 33 · 2015: 27 · 2014: 19 · 2013: 21 · 2012: 20
FWCI
17.24
Type
journal article
Language
en
Open access
closed
Locations
  • The Leadership Quarterly (publishedVersion)
  • PolyU Institutional Research Archive (Hong Kong Polytechnic University) (submittedVersion)
Topics
  • Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Job Satisfaction and Organizational Behavior
  • Social Sciences › Public Administration › Labor Movements and Unions
  • Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Employee Performance and Leadership
Keywords
voice behavior, transformational leadership, employee identification, social identification, personal identification, speaking out, speaking up, supervisor-employee relations

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.

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