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Record W4287509736 · doi:10.1108/ijoa-04-2022-3227

How employees leverage psychological capital and perform, even in the presence of rude co-workers: an empirical study from Pakistan

2022· article· en· W4287509736 on OpenAlexaff
Muhammad Umer Azeem, Dirk De Clercq, Inam Ul Haq

Bibliographic record

VenueInternational journal of organizational analysis · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsBrock University
Fundersnot available
KeywordsOriginalityPsychologySocial psychologyLeverage (statistics)Extant taxonInterpersonal communicationValue (mathematics)Work (physics)Social capitalWork engagementHuman resource managementIndustrial and organizational psychologyBusinessPublic relationsManagementEconomicsSociologyPolitical scienceCreativityEngineering

Abstract

fetched live from OpenAlex

Purpose This study aims to unpack the link between co-worker incivility and job performance, by detailing a mediating role of psychological detachment and a moderating role of psychological capital. Design/methodology/approach The research hypotheses are tested with three-wave, time-lagged data collected from Pakistani-based employees and their supervisors. Findings An important reason that disrespectful co-worker treatment curtails job performance, with respect to both in-role and extra-role work efforts, is that employees detach from their work environment. This mediating role of psychological detachment is less salient to the extent that employees possess high levels of psychological capital. Practical implications For organizations, this study pinpoints a key mechanism, a propensity to distance oneself from work, by which convictions that co-workers do not show respect direct employees away from productive work activities. This study also shows how this mechanism can be subdued by ensuring that employees exhibit energy-enhancing personal resources. Originality/value This study expands extant research on the dark side of interpersonal co-worker relationships by revealing pertinent factors that explain why and when co-worker incivility can escalate into diminished performance-enhancing activities.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.327
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2022
Admission routes1
Has abstractyes

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