Leader Inconsistency, Subjective Ambivalence, and Follower Outcomes
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Research has shown that leaders who display both positive and negative leadership behaviors can induce detrimental impacts on followers.
“For instance, research has shown that leaders who display both positive and negative leadership behaviors can induce detrimental impacts on followers (Ch ´ enard-Poirier et al., 2022; Suurd Ralph & Barling, 2023).”
From The evolution of leadership: Past insights, present trends, and future directions (2025) · cites this paper as Suurd Ralph & Barling, 2023
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“However, this was unavoidable as subjective ambivalence represents a psychological process that cannot be observed directly, and would be difficult to manipulate (Spencer et al., 2005).”
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Flagged first, then by citations
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- Authors
- Suurd Ralph, C., & Barling, J.
- Affiliations
- Queen's University (CA)
- Corresponding author
- Barling, Julian
- Venue
- Journal of Business and Psychology
- Published
- 2022-11-08
- Volume
- 38
- Issue
- 5
- Pages
- 1003-1021
- ISSN
- 0889-3268 (ISSN-L)
- 1573-353X
- OpenAlex
- W4308569963
- Cited by
- 16
- References
- 151
- Citations by year
- 2026: 4 · 2025: 5 · 2024: 6 · 2023: 1
- FWCI
- 2.83
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Journal of Business and Psychology (publishedVersion)
- Funders
- Social Sciences and Humanities Research Council
- Topics
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Job Satisfaction and Organizational Behavior
- Social Sciences › Business, Management and Accounting › Strategy and Management › Leadership and Management in Organizations
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Employee Performance and Leadership
- Keywords
- follower outcomes, workplace attitudes, employee well-being, uncertainty management theory, leadership behavior, follower perceptions, conditional indirect effect
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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