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Record W4381930637 · doi:10.1108/pr-11-2022-0764

How employee pandemic fears may escalate into a lateness attitude, and how a safe organizational climate can mitigate this challenge

2023· article· en· W4381930637 on OpenAlexaff
Dirk De Clercq, Mohammed Aboramadan, Yasir Mansoor Kundi

Bibliographic record

VenuePersonnel Review · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsBrock University
Fundersnot available
KeywordsHuman resource managementOriginalityPunctualityPsychologyPublic relationsBusinessEmotional exhaustionOrganizational commitmentPerceptionWork (physics)MarketingSocial psychologyBurnoutManagementPolitical scienceEconomics

Abstract

fetched live from OpenAlex

Purpose This study aims to understand how and when employees' pandemic fears influence their lateness attitude, with a particular focus on how this influence is mediated by emotional exhaustion and moderated by a perceived safety climate. Design/methodology/approach Survey data were collected among employees in the retail sector. Findings A core mechanism that explains the escalation of pandemic fears into beliefs that tardiness is acceptable is employees' sense that employees are emotionally overextended by work. The extent to which employees perceive that their organization prioritizes safety issues subdues this detrimental process though. Practical implications For human resource management (HRM) practice, the findings point to the notable danger that employees who cannot stop ruminating about an external crisis, and feel emotionally overburdened as a result, might compromise their own organizational standing by devoting less effort to punctuality. To disrupt this dynamic, HR managers can create organizational climates that emphasize safety practices. Originality/value This study adds to HRM research by revealing a pertinent source of personal adversity, pandemic fears, and how the fears affects tendencies to embrace tardiness at work. The study explicates how emotional exhaustion functions as a core conduit that connects this resource-draining condition with propensities to show up late, as well as how safety climate perceptions can buffer this translation.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.654
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.066
GPT teacher head0.278
Teacher spread0.212 · 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
Published2023
Admission routes1
Has abstractyes

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