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Record W2945620210 · doi:10.5430/ijfr.v10n3p88

The Influence of Work Overload, Time Pressure and Social Influence Pressure on Auditors’ Job Performance

2019· article· en· W2945620210 on OpenAlexvenueno aff
Razana Juhaida Johari, Nordayana Sri Ridzoan, Arumega Zarefar

Bibliographic record

VenueInternational Journal of Financial Research · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsAuditGovernment (linguistics)PsychologyBusinessWork (physics)Job performanceApplied psychologyAccountingPublic relationsJob satisfactionSocial psychologyPolitical scienceEngineering

Abstract

fetched live from OpenAlex

Auditing is considered a stressful occupation as the job is always characterized by heavy workloads, many deadlines, time pressure, social pressure and commitment towards the organization. Public auditors are often under pressure to produce quality audit, and yet may be under serious work pressure or continually dealing with auditees in stressful situations. Work stress faced by public auditors also may lead to mental and physical distress which resulted to decrease in job performance. This study examines which potential factors of pressure that have a significant relationship to government auditors’ job performance. Factors to be test in this study are work overload, time pressure and social influence pressure. This current study contributes information and ideas to the management and academician in the theoretical and practical aspects. The respondents in this study are 203 government auditorsfrom government auditors in National Audit Department of Malaysia. The result of this study shows that there is no significant relationship on work overload to auditors’ job performance. However the result of this study found that factor of time pressure shown a positive significant relation on auditors’ job performance, while social influence pressure shown a negative significant relationship on auditors’ job performance.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

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

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 head0.013
GPT teacher head0.289
Teacher spread0.276 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations52
Published2019
Admission routes1
Has abstractyes

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