Evidence map›Paper›PMID 36778174›Full record

ArticleFrontiers in psychology2022

Bad apples spoiling the metaphor? How and why self-serving leaders stir up counterproductive behaviors at work.

Yajun Zhang, Shuai Peng, Jinsong Wang, Muhammad Naseer Akhtar, Yongqi Wang

Abstract read
In one paragraph

Article in Frontiers in psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yajun ZhangSchool of Business Administration, Guizhou University of Finance and Economics, Guiyang, China.
Shuai PengSchool of Business Administration, Guizhou University of Finance and Economics, Guiyang, China.
Jinsong WangSchool of Business Administration, Guizhou University of Finance and Economics, Guiyang, China.
Muhammad Naseer AkhtarRoyal Docks School of Business and Law, University of East London, London, United Kingdom.
Yongqi WangInternational College, Guangdong University of Foreign Studies, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Self-serving leaders satisfy their self-interests at the cost of both employees and organizations, leading to declining organizational competitive advantage and performance. Drawing upon the affective events theory (AET), we constructed and examined a theoretical model of self-serving leadership influencing counterproductive work behavior (CWB), where traditionality plays a significant moderating role through the lens of anger as a mediator. Data were collected in three waves using a survey questionnaire distributed in three industries located in the Southwest district of China. Hierarchical regression analyses were conducted on a sample of 316 employees to test the hypothesized research model. The results showed that self-serving leadership triggers employee anger, which in turn causes CWB. Furthermore, traditionality plays a significant moderating role, in which employees with higher levels of traditionality feel less anger and show less CWB. Overall, research findings have clarified how and why self-serving leadership affects employees' emotions (such as anger) and behavior (such as CWB), bringing new insights into the self-serving leadership and employee behavior literature. Research implications on the management of self-serving leadership, limitations, and future recommendations of research are also discussed.

Indexed as

affective event theoryangercounterproductive work behaviorself-serving leadershiptraditionality

Identifiers

PMID36778174
PMCPMC9908574

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.